workplace ethics research paper

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How to Develop a Strong Work Ethic

  • Tutti Taygerly

workplace ethics research paper

Hiring managers want to see your motivation, can-do attitude, and dedication.

In our early career years, it can be challenging to figure out what behaviors are and are not acceptable in different professional environments. Employers are now expecting more of entry-level workers and they want to see that you have good work ethic. So what is work ethic?

  • Work ethic refers to a set of moral principles, values, and attitudes around how to act at work. It often surrounds what behaviors are commonly acceptable and appropriate (or not).
  • Qualities like reliability, productivity, ownership and team support all demonstrate professional integrity, or a strong commitment to ethical behavior at work. In contrast, low-quality work, tardiness, or lack of attention to details demonstrates bad work ethic.
  • If you’re new to the workplace, a good way to start is by observing. Pay attention to how your coworkers behave in meetings to gain a better understanding of their “etiquette,” as well as the communication styles of different people and teams. Another essential part of building good work ethic is adopting a “do it like you own it” attitude. You can do this by being proactive in small, but powerful, ways.

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Where your work meets your life. See more from Ascend here .

Have you ever wondered about how to behave appropriately at work? Throughout your career, and especially in the early years, it’s challenging to figure out what behaviors and attitudes are and are not acceptable in different professional environments. The more you traverse companies and industries, the clearer your understanding will become. When you’re just starting out, though, it can be hard to pin down these behaviors.

  • Tutti Taygerly is a leadership and executive coach with 20+ years of design experience across large companies, design agencies and startups.

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Steps to Strengthen Ethics in Organizations: Research Findings, Ethics Placebos, and What Works

Kenneth s. pope.

a Licensed Psychologist in Independent Practice, Norwalk , Connecticut, USA

Research shows that many organizations overlook needs and opportunities to strengthen ethics. Barriers can make it hard to see the need for stronger ethics and even harder to take effective action. These barriers include the organization’s misleading use of language, misuse of an ethics code, culture of silence, strategies of justification, institutional betrayal, and ethical fallacies. Ethics placebos tend to take the place of steps to see, solve, and prevent problems. This article reviews relevant research and specific steps that create change.

We live in an age rich with opportunities to make organizational ethics stronger. Striking betrayals of ethics and trust grab headlines:

  • In 2014, General Motors (GM) admitted that since 2001 it had hidden a potentially fatal design defect. GM engineers, investigators, and lawyers knew, but the company decided that recalling cars would cost too much. Instead, they kept the flaw secret for more than a decade. They kept selling risky cars while the deaths and injuries piled up (Bennett, 2014a , 2014b , 2014c ; Consumer Reports, 2014 ; Ivory & Abrams, 2014 ; Plungis & Higgins, 2014 ; Viscusi, 2015 ; Young, 2014 ).
  • Famous for its football program’s integrity, Penn State covered up child abuse for years, allowing the abuser to continue committing crimes. The university-commissioned report stressed “the total and consistent disregard by the most senior leaders at Penn State for the safety and welfare of Sandusky’s child victims” (Freeh, Sporken, & Sullivan, LLP, 2012 , p. 14).
  • California had repealed its “compulsory sterilization laws [that] targeted minorities, the poor, the disabled, the mentally ill and criminals” (Johnson, 2014 ) that allowed the state to force sterilization on more than 20,000 citizens in state-run institutions (Stern, 2005 ; Wellerstein, 2011 ), but the California State Auditor ( 2014 ) reported that between 2005 and 2013 the state prison system had continued to sterilize some female prisoners, violating both the law and women’s right to informed consent.
  • Many Veterans Administration (VA) executives pocketed hefty bonuses for making sure that sick veterans got prompt care, but it was a con. Hospitals reported that they were giving all veterans prompt care when needed but were shunting tens of thousands of veterans to secret waiting lists where they languished without care for months and some died without care (Bronstein & Griffin, 2014 ; Daly & Tang, 2014 ; Hoyer & Zoroya, 2014 ; Oppel & Shear, 2014 ; VA Office of the Inspector General, 2014 ; Wagner, 2014a , 2014b ).

Studies suggest that many organizations violate basic ethical standards and betray our trust:

  • Huberts ( 2014 ) noted that almost half of U.S. workers reported seeing one or more acts of wrongdoing (e.g., accepting kickbacks or bribes, offering bribes to public officials, lying to outside stakeholders, environmental violations) on the job within the past year.
  • A study of full-time U.S. workers found that almost three fourths reported encountering ethical lapses at work, with one tenth believing that the lapse could create a scandal or business disruption (LRN, 2007 ).
  • According to Stevens ( 2013 ), “Confidence in the ethics of the U.S. business executive remains fairly low on the Gallup Poll surveys and the U.S. has declined on the CPI (Consumer Price Index) and Edelman Trust Barometer” (p. 361).
  • In the introduction to a special issue of the Journal of Law, Medicine & Ethics, Rodwin ( 2013 ) wrote that “today, the goals of pharmaceutical policy and medical practice are often undermined due to institutional corruption—that is, widespread or systemic practices, usually legal, that undermine an institution’s objectives or integrity” (p. 544). Elliott ( 2014 ) noted that in 2010 the pharmaceutical industry eclipsed the defense industry as the biggest defrauder of the U.S. government.
  • A study found that campus judicial systems tend to give light sentences (e.g., writing an essay) for serious violations such as sexual assaults, physical attacks causing serious injuries, robberies, and other violent felonies, leaving many students reporting that “the system is unfair” and that the campus “has betrayed them” (Binkley, Wagner, Riepenhoff, & Gregory, 2014 ).
  • Twenge, Campbell, and Carter ( 2014 ) reported that “confidence in institutions … reached historic lows among Americans” (p. 1920). They emphasized that the loss of trust and confidence extends across a wide array of institutions: “The trend is not limited to distrust in government; the declines also appear in Americans’ confidence in institutions unconnected to the government, such as medicine, religion, the news media, and TV” (p. 1921).

This article suggests three steps to strengthen ethics in organizations.


Organizations often point with pride to their ethics codes, highlighting high ideals and clear prohibitions of questionable conduct. Codes can communicate basic standards and admirable aspirations. But ethics codes—including those backed by good-faith enforcement—often fall short of fostering an ethically strong organization. Unethical acts may go unnoticed, noticed acts may go unreported, reported acts may not be fully and fairly investigated, and investigation findings may not be adequately acted on.

Enron’s famous 84-page organizational code illustrates the illusions that codes out of context can create. Enron required every employee to read and sign the code, which was widely praised for years as a model for other groups wishing to achieve Enron’s reputation for integrity, innovation, and profitability. Years later, Enron’s code of ethics shifted from fame to notoriety as prosecutors used it to cross-examine employees in trials that convicted 21 felons after the company collapsed into bankruptcy and caused investors to lose $74 billion, with losses due to fraud up to $45 billion (Arbogast, 2013 ; Axtman, 2005 ; McLean & Elkind, 2013 ; Pasha, 2006 ; Watkins, 2013 ).

Lease ( 2006 ) wrote that “the literature supports … the contention that an ethical organizational culture cannot be created through the imposition of a code” (p. 29) but that a code can play a key role if those at the top provide ethical leadership by modeling ethical behavior and creating a culture of commitment to ethics throughout the organization.

Kish-Gephart, Harrison, and Treviño’s ( 2010 ) meta-analysis found that the “mere existence of a code of conduct has no detectable impact on unethical choices, despite the considerable amount of statistical power that comes from doing a meta-analytic summary” (p. 21). However, the study also found “a strong, negative link … between code enforcement and unethical choice” (p. 13).

Weaver ( 2014 ) noted that “empirical research has been clear” that organizational codes per se have “limited, if any, influence on ethical behavior” (p. 293) but must be part of an organization climate in which ethical issues are discussed on an everyday basis and become an ordinary aspect of decision making and behavior (see also Nicholson, 2008 ; Weiss, 2014 ). The organization’s ethical culture becomes internalized as part of each individual’s personal values (Hill, Jones, & Schilling, 2014 ).

These and other studies suggest that most ethics codes are little more than an ethics placebo. Codes work to prompt ethical thinking and action when rooted in an ecology of strong ethical leadership, effective enforcement, and a culture of ethical concern. Ethics questions can rise for everyone to the level of daily concern often devoted to questions of profits, promotions, and will this meeting ever end? To make ethics stronger in any organization, a reasonable first step is surveying all employees, members, and other stakeholders about current leadership, enforcement, and culture; asking them about needed changes; and opening up discussions.


When it comes to ethics, none of us is perfect. We all fall short, miss red flags, face risky moments of weakness and temptation. How do we mask, reinterpret, or justify our unethical acts to ourselves and, when needed, to others? Each of us likely has our own set of go-to strategies when we find it hard to pass up temptation. Pope and Vasquez ( 2011 ) discussed ways to recognize and avoid some of the most common means—including eight tricks of language, 22 cognitive strategies of justification, and 22 logical fallacies in ethical reasoning—of spinning ethically questionable or objectionable options into seemingly acceptable choices.

These ethical spins deny or downplay the true costs of our unethical acts. The costs of betraying ethics range from seemingly minor wrongs to people dying, as in the GM example. In betraying ethics, GM betrayed its customers, who trusted and relied on the company’s honesty, integrity, and good faith. As a result, some GM customers died. Others suffered needless catastrophic injuries. Families suddenly lost a mother, a father, a child, or another loved one. These are the true costs of deciding that fixing a design flaw is “not worth the cost” (Viscusi, 2015 , p. 7).

Research supports the idea that betrayal per se can cause harm and may deepen the response to other bad acts. Rachman ( 2010 ) noted that betrayal’s effects may include “shock, loss and grief, morbid pre-occupation, damaged self-esteem, self-doubting, anger” and sometimes “life-altering changes” (p. 304). Koehler and Gershoff’s (2003) set of experiments “found that people reacted more strongly … to acts of betrayal than to identical bad acts that do not violate a duty or promise to protect” (p. 244; see also Beamish, 2001 ).

Research also supports the idea that when betrayal happens within organizational dynamics, it may cause institutional betrayal trauma (Freyd, Klest, & Allard, 2005 ; Smith & Freyd, 2013 ). Organizations often betray customers, students, parishioners, prisoners, and others who are not employees, but organizations can also betray their own employees. Kirschman, Kamena, and Fay ( 2013 ), for example, described organizational betrayal that many police officers experience. They wrote that when this betrayal occurs, it “complicates traumatic reactions by creating huge doubts about the future” (p. 73) and “makes everything else worse” (p. 57). Surís, Lind, Kashner, and Borman ( 2007 , p. 179; see also Surís, Lind, Kashner, Borman, & Petty, 2004 ) found that when female solders were sexually assaulted within the context of the military organization (i.e., by officers or other military personnel), there were “additional negative consequences above and beyond the effects of [civilian sexual assault].”

Ethically strong organizations work to avoid the many tricks of language, cognitive strategies, and logical fallacies mentioned earlier that hide betrayals and their true costs. To appreciate the ability of such a common event as betrayal to stay out of sight, it may be helpful to remember that psychology itself was slow to recognize it as topic of study. The PsycNET database includes millions of articles in psychology journals dating back to 1900, but a study—or article of any kind—with the term betrayal in the title did not appear in a psychology journal until a single article was published during the 1960s, followed by an average of less than one each year for the next two decades. It was not until 1992, when a special double issue (Volume 8, Issues 3–4) of Psychotherapy Patient published seven articles focusing on betrayal, and 1994, when Freyd published “Betrayal Trauma: Traumatic Amnesia as an Adaptive Response to Childhood Abuse,” which was followed by Betrayal Trauma: The Logic of Forgetting Childhood Abuse in 1996, that a significant body of published research, theory, and thoughtful discussions began to appear.

The anonymous survey and open discussion recommended previously might include the following questions:

  • How has the organization betrayed—or seemed at risk for betraying—ethical standards or aspirations, the organization’s employees or members, and others affected by the organization’s behavior?
  • How has the organization denied or downplayed betrayals and their consequences?
  • How has the organization failed to assume responsibility for its betrayals?
  • What changes would be helpful, and who should make them?


Prior sections suggest an anonymous survey as a starting point. Why? Because organizational culture often silences concerns that the organization’s leadership, culture, code enforcement, or behavior are questionable, somewhat flawed, or worse. Kish-Gephart, Detert, Treviño, and Edmondson ( 2009 ) wrote, “In every organization, individual members have the potential to speak up about important issues, but a growing body of research suggests that they often remain silent instead, out of fear of negative personal and professional consequences” (p. 163; see also Milliken, Morrison, & Hewlin, 2003 ). Detert and Treviño ( 2010 ) noted that many employees believe from the time they set foot in the door that part of their organizational role is to “‘tread lightly’ around those in power” (p. 264).

Sometimes the belief that speaking up achieves nothing compels those concerned to keep their mouths shut. In some organizations, people in power turn a deaf ear to unwelcome questions, concerns, or reports (see, e.g., Peirce, Rosen, & Smolinski, 1998 ; Pinder & Harlos, 2001 ).

Stakeholders may also lack confidence that ethics concerns or complaints will be met with fairness and justice (Cropanzana, Bowen, & Gilliland, 2007 ; Dunford, Jackson, Boss, Tay, & Boss, 2014 ; Qin, Ren, Zhang, & Johnson, 2014 ). Koocher ( 2014 ) provided a detailed report of an executive director of the American Psychological Association (APA) who acted secretly in regard to a formal ethics complaint against a prominent APA member, later “professed no knowledge” (p. 3273) to the Board of Directors about action that he himself had taken, and only years later told others of his “personal belief that an ethics investigation of a high profile psychological scientist at that time in APA’s history would have severely damaged the organization” (p. 3274). If members of any organization believe that there is one system of ethical accountability and discipline for high-status members and a different system for everyone else, it may create a climate in which high-status members trust that those in power will find creative ways to shield them from accountability or even investigations, and others learn that voicing ethical questions or concerns about those who enjoy high status will at best come to nothing.

Research suggests that those who choose to act as whistleblowers must overcome concerns that they will face retaliation or that the risks they take will be in vain (Mayer, Nurmohamed, Treviño, Shapiro, & Schminke, 2013 ; Mesmer-Magnus & Viswesvaran, 2005 ; Miceli, Near, & Dworkin, 2013 ). These concerns are often well placed. Dyer ( 2014 ), for example, reported that “more than half the whistleblowers who contacted the UK charity Public Concern at Work for advice in 2012 were sacked or resigned after raising concerns about wrongdoing, risk, or malpractice” (p. 6285). An additional 22% were disciplined or punished in other ways. Only 6% reported that their speaking up led to improvements in the workplace.

Rothschild and Miethe ( 1999 ) found that whistleblowers tend to “suffer severe retaliation from management, especially when their information proves significant” (p. 107). McDonald and Ahern ( 2000 ) found that nurse whistleblowers tended to suffer severe consequences, whereas those who kept silent experienced few negative effects. The

official reprisals included demotion (4%), reprimand (11%), and referral to a psychiatrist (9%). Whistleblowers also reported that they received professional reprisals in the form of threats (16%), rejection by peers (14%), pressure to resign (7%), and being treated as a traitor (14%). Ten per cent reported that they felt their career had been halted. (McDonald & Ahern, 2000 , p. 313)

Sherron Watkins ( 2013 ), formerly of Enron, described how blowing the whistle on questionable activities can derail a career. The media provided positive coverage of her insider disclosures of Enron’s wrongdoing and her testifying as a key prosecution witness in the criminal and civil trials. She shared the cover of Time with two other whistleblowers from other organizations as Time ’s “Person of the Year.” The corporate world, however, took a dimmer view. A decade later she wrote that “the label Enron whistleblower means I will not work in Corporate America again” (p. ix).

Jackall ( 1988 ) gathered the rules of organizational silence into a series of five warnings:

(1) You never go around your boss. (2) You tell your boss what he wants to hear, even when your boss claims that he wants dissenting views. (3) If your boss wants something dropped, you drop it. (4) You are sensitive to your boss’s wishes so that you anticipate what he wants; you don’t force him, in other words, to act as boss. (5) Your job is not to report something that your boss does not want reported, but rather to cover it up. You do what your job requires, and you keep your mouth shut. (p. 115)

A culture of silence and silencing can close off many routes to better organizational ethics. An anonymous survey might begin by asking the following: If you were to raise concerns about ethics or blow the whistle on unethical behavior, how do you think your colleagues and those higher up in the organization would respond, what would happen to your concerns, and what would happen to you? But if the organization’s culture lacks trust, those asked to fill out the survey may wonder: Will they recognize my identity in some way? Are the forms coded? If I go to all the trouble of filling it out, will anyone even read it? Take it seriously? Treat it fairly? Use it to make things better?

In some cases, it may make more sense to simply start looking for ways to change the culture and dynamics of silencing. What immediate steps would encourage and support speaking up and show that valid criticism is heard, valued, and acted on with fairness and justice? Can the costs of speaking up be eliminated or at least minimized?


Any steps to make organizational ethics stronger can succeed only if we actually take the steps. Taking action requires us to leave our role as passive bystanders (aka enablers) when we learn of questionable or unacceptable behavior, especially when the welfare of others is at stake. We must often teach ourselves how to leave the comfort and safety of “it’s not my problem,” “someone else will take care of this,” “it’s probably not as bad as it looks,” or “speaking up won’t make any difference.” However, formal programs show promise in teaching and encouraging bystanders to take action in a range of situations such as theft, sexual harassment, interpersonal or systemic racism, bullying, or sexual assault (Chiose, 2014 ; Guerette, Flexon, & Marquez, 2013 ; Kleinsasser, Jouriles, McDonald, & Rosenfield, 2014 ; Nelson, Dunn, & Paradies, 2011 ; Nickerson, Aloe, Livingston, & Feeley, 2014 ; Palm Reed, Hines, Armstrong, & Cameron, 2014 ; Salmivalli, 2014 ; van Bommel, van Prooijen, Elffers, & van Lange, 2014 ; Wonderling, 2013 ).

Serrat ( 2010 ) described moral courage: “At its most basic, moral courage helps cultivate mindful organizational environments that, among others, offset groupthink; mitigate hypocrisy and ‘nod-and-wink’ cultures; educate mechanical conformity and compliance; bridge organizational silos; and check irregularities, misconduct, injustice, and corruption” (p. 2; see also Hannah, Avolio, & Walumbwa, 2011 ; Osswald, Greitemeyer, Fischer, & Frey, 2010 ; Simola, 2014 ). It often takes moral courage to take action—whether action means using a survey to find out what changes might make organizational ethics stronger, trying to help bring about those changes, or blowing the whistle inside or outside the organization.

Finally, even if we are concerned about, committed to, and focused on taking steps to prevent questionable or objectionable practices on an individual and organizational level, our lives may be so textured with tight schedules, heavy responsibilities, and constant distractions that we miss chances to make a difference. Darley and Batson ( 1973 ) conducted an experiment showing how a lack of attention to our immediate surroundings—the here and now—can lead to missed opportunities. Princeton Theological Seminary students participated in an experiment in which they were given time to prepare a brief talk in one locale and then had to give the talk in another building. As the students walked through an alley between the buildings, each found someone pretending to be a victim in need of help—slumped over in a doorway, eyes shut, head down, unmoving. The victim coughed and groaned. Half of the students prepared a talk on the parable of the Good Samaritan, and yet many did not stop to help the victim. Those who were about to talk about the importance of acting like the Good Samaritan were no more likely to stop to help than those who were assigned to talk about another topic. To save time, some stepped over the victim rather than going around.

As we go about taking steps to make ethics stronger in organizations, this study reminds us that a chance to make a difference can come at an inconvenient time and catch us off guard by appearing in forms we did not expect, that we can pass by it without noticing, and that we need to pay attention to what shows up unannounced at every step.


Special thanks to Raymond Arsenault, Loralie Lawson, and Karen Olio, who provided helpful comments on a previous draft of this article.

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Research Article

Relationships between work ethic and motivation to work from the point of view of the self-determination theory

Contributed equally to this work with: Damian Grabowski, Agata Chudzicka-Czupała, Katarzyna Stapor

Roles Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Software, Writing – original draft, Writing – review & editing

Affiliation Faculty of Psychology, Department of Social and Organizational Behavior, SWPS University of Social Sciences and Humanities, Katowice, Poland

Roles Conceptualization, Data curation, Investigation, Project administration, Validation, Visualization, Writing – original draft, Writing – review & editing

Roles Formal analysis, Investigation, Methodology, Resources, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, Gliwice, Poland

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  • Damian Grabowski, 
  • Agata Chudzicka-Czupała, 
  • Katarzyna Stapor


  • Published: July 1, 2021
  • Reader Comments

Table 1

Most studies on motivation to work concentrate on its environmental and situational antecedents. Individual values are not the point of interest of empirical analyses. The aim of the research described in the paper was to seek possible relationships between work ethic and motivation to work. A hypothesis was put forward that work ethic, in the classical Weberian approach, is connected with motivation to work, from the point of view of Ryan’s and Deci’s self-determination theory. The study on a sample of 405 Polish employees was conducted with use of the Polish version of Multidimensional Work Ethic Profile MWEP-PL and Work Extrinsic and Intrinsic Motivation Scale , in the Polish adaptation WEIMS-PL. The Canonical Correlation Analysis was used to assess the simultaneous interrelationships between two sets of the variables measured. The results show that selected dimensions of work ethic, such as centrality of work, valuing hard work, perceiving work as an obligation, anti-leisure sentiment and delay of gratification are positively related to autonomous dimensions of motivation: intrinsic motivation, integration and identification, and non-autonomous introjection. Attributing a high value to hard work, including the conviction that it leads to success, aversion to wasting time and self-reliance correlate positively with taking up work for extrinsic rewards and with the desire to acquire a positive opinion about oneself as well as gain approval and recognition from others. Work ethic is connected on the one hand with autonomous motivation, including in particular intrinsic motivation, and on the other hand with extrinsic motivation, with the striving for success, which is the result of work. After empirical verification the findings could become a base for training programs and shape the way of influencing people’s motivation, morale, attitude towards work and job satisfaction. They can result in the way employees are managed and selected for different tasks.

Citation: Grabowski D, Chudzicka-Czupała A, Stapor K (2021) Relationships between work ethic and motivation to work from the point of view of the self-determination theory. PLoS ONE 16(7): e0253145.

Editor: Godfred O. Boateng, University of Texas at Arlington, UNITED STATES

Received: October 31, 2020; Accepted: May 31, 2021; Published: July 1, 2021

Copyright: © 2021 Grabowski et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: Authors AC, DG, and KS received funding for Open access from the Ministry of Science and Higher Education in Poland under the 2019-2022 program „Regional Initiative of Excellence", project number 012 / RID / 2018/19. Authors AC and DG received funding from the SWPS University of Social Sciences and Humanities, Warsaw, Poland, project No. 1571-BST/WZK/2018/A/06 entitled “Development of standards for the assessment of social and ethical aspects of employees’ way of functioning”, . The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.


Most empirical studies on work motivation and occupational behavior focus on the importance of environmental and situational characteristics such as working conditions and pay, organizational structure, job characteristics, task characteristics, working time flexibility, role of the manager and being subject to the latter’s control, as well as organizational climate [ 1 – 4 ]. Research also relates motivation to stressful environmental factors [ 1 ]. Some researchers point out that the external context in which an individual performs a task influences the intrinsic motivation to perform it, which may contribute to creative achievements [ 5 ]. Research was also conducted on motivational potential of meaningful work [ 6 ]. Some studies show how work-related and individual factors are related to psychological work ability and job mobility motivation in specific age, e.g. in later adulthood [ 7 ]. The relationships between motivation to work on the one hand and satisfaction with its performance and occupational burnout on the other hand was subject of studies as well [ 8 ].

Our review shows that research is still lacking that would connect individual predisposition or values subscribed to with motivation to work. The few empirical analyses carried out in this area prove the existence of relationships between affective organizational attachment, interest in work, acceptance of risk connected with its performance, perceived own competences and motivation to work [ 9 ], as well as between locus of control and motivation [ 10 ], and between agreeableness, conscientiousness, commitment to work, including attributing a high value to work, and motivation to learn, supposed to improve the quality of work [ 11 ].

Although the number of studies linking beliefs and values to motivation is not large, many scholars clearly pointed to the existence of interrelationships. Rokeach [ 12 , 13 ] has already presented values and beliefs as an inseparable element of motivation. Similarly, Lewin [ 14 ] considered values to be an important “guides” of behavior, because they trigger the goals to which one aspires. The self-concordance model of motivation [ 15 ] suggests that people are more inclined to pursue goals consistent with their autonomous values. The authors of this model, which measures intrinsic motivation, are guided by the assumption that people are intrinsically motivated by goals that result from the values they hold in high regard.

Studying motivation to work in the context of work-related values and work-related beliefs is rare [ 11 ]. There is a particular lack of research on the relationships between work ethic, understood as a multidimensional attitude towards work, which is a value in itself, and intrinsic and extrinsic motivation described by the self-determination theory. Few analyses point to the existence of certain relationships between the components of work ethic and intrinsic motivation, although work ethic in this case was studied in an Islamic version. However, study by Hayati and Caniago [ 16 ] on the Islamic work ethic and its relation to intrinsic motivation treated work ethic and intrinsic motivation as single dimension. Many studies highlight the importance of work ethic in business and in the capitalist economy [ 17 – 19 ]. This study aimed to check for potential relationships between the motivation to work and the dimensions of work ethic, reflecting human beliefs concerning work, the attitude towards being rewarded for work, leisure time, or the ability to rely on oneself in various activities, was designed to fill the gap in research into the area. We believe it is important for both cognitive and practical reasons to find an answer to the question as to whether any relationships between the variables mentioned above exist. Finding out about the strength and direction of these relationships may help to make a more effective impact on employees, to increase their motivation enabling them to act effectively and to achieve self-satisfaction and job satisfaction. It may also make it possible to prepare professionals better for training interventions. Knowledge about the relationships between the different components of both variables makes it possible to obtain better insight into the meaning of an individual’s autonomous values, attitudes, beliefs and needs, as well as into the nature and sources of their motivation. The findings presented in this study are exploratory in nature and their effects may require the construction of a more extensive model of dependencies. In fact, we do not know if and how work ethic, understood as a syndrome of different attitudes and beliefs about work, is connected with motivation to work.

Work ethic as a system of attitudes and beliefs

Work ethic means attributing value to hard work and industriousness, stigmatizing idleness, fulfilling the obligations, and the belief that work should be done in the best possible way [ 20 ]. To fulfill the obligations means here a moral duty, while industriousness is considered a virtue, i.e. a desirable moral quality [ 21 ]. This term describes the cult of work, manifested in the respectful treatment of, or even reverence for work [ 22 ]. Work ethic involves perceiving and treating work as a duty or obligation and as a moral value. It consists of norms, prohibitions and orders, beliefs, attitudes and behaviors, both desirable and undesirable, connected with work valuation [ 20 , 23 ].

In the psychological sense, work ethic is a syndrome of attitudes and beliefs, with strongly outlined emotional-judgmental components. Miller [ 24 ] described seven dimensions of the syndrome, on the basis of analyses by Furnham [ 21 ]:

  • Belief in the sense of hard work, the conviction that it leads to success and that it is a recipe for problems and difficulties in life;
  • Centrality of work, the conviction that it is the basic activity in life–“but the most important thing was that even beyond that labor came to be considered in itself the end of life”;
  • Distaste for wasting time, tendency to treat time as a valuable resource–“waste of time is thus the first and in principle the deadliest of sins”;
  • Distaste for leisure, i.e. the conviction that free time activities are less valuable: “not leisure and enjoyment, but only activity serves to increase the glory of God”;
  • Delay of gratification, recognizing the value of rewards one has to wait for “the idea of expectant waiting for the Spirit to descend”), with importance attached also to work without rewards–the assumption that work in itself is a reward;
  • Independence, self-reliance at work, individualism;
  • Morality and ethics, i.e. placing emphasis on honesty in relationships with others, the assumption that honest conduct should be the content of the work [ 20 ] (p. 96–105).

These components can be put in order and structured. The core of a high work ethic is the conviction that work is a central value in life, so it should be done in a perfect and honest manner. Doing work well means devoting a considerable amount of effort and sufficient time to it. Therefore, the components of work ethic are deemed to include the requirement to save time, reduce leisure time, as well as the precept not to consume rewards, as they change people’s attitude towards other values. Also, worth mentioning are new research results on studies regarding the relationship of ethical culture and leadership with employees’ innovation [ 25 , 26 ].

Work ethic and motivation to work. Self-determination theory

In the concept of work ethic, one can see descriptions of energy-related components, such as the requirement to increase effort and the high value given to it, i.e. emphasis on the importance of hard work. A job well done is also an efficient and effective action. The conceptualization and operationalization of work ethic performed by Mann [ 27 ] emphasize the importance of striving to improve oneself, looking after the quality of work and persistently pursuing of goals, i.e. factors which may be associated with motivation. Work ethic, by underscoring the importance and strengthening the training of independence, also triggers the motivation to achieve, conducive to economic development [ 21 ], and therefore these variables can be interrelated. Few studies also indicate the relationship between the work ethic syndrome and intrinsic motivation [ 16 ].

Cassidy and Lynn [ 28 ], in their conceptualization of achievement motivation, treat work ethic, defined as the performance of work for the sake of work itself, the desire to work hard and to derive satisfaction from such activity, as a component of motivation. Ethic understood in this way is placed here alongside other components of motivation, such as the desire to have and earn money, the need for dominance/power, the pursuit of perfection, the desire to achieve high standards, the tendency to compete and to perform better than others, as well as the desire to achieve a high status and prestige. Among the dimensions of motivation, the authors mentioned above also list the tendency to achieve mastery, which they understand as focusing on new challenges and situations that require one to master new skills.

Story and colleagues [ 29 ] suggested that work ethic, striving for perfection and mastery should be treated as components of the intrinsic motivation to achieve, while striving to have and to earn, the need for dominance, striving to compete and the desire to gain prestige should be treated as the extrinsic motivation to achieve. It should be noted, however, that in some samples an intrinsically motivating work ethic correlates with extrinsically motivating material needs, identified with earning money, the need for dominance and the need for prestige [ 28 ].

The division into intrinsic and extrinsic motivation has existed for a long time in the field of labor psychology, but only the emergence of a macro theory in the form of the self-determination theory [ 30 ] brought a new quality to research into work motivation. The self-determination theory, apart from the central division into autonomous and controlled motivation, postulates a multidimensional conceptualization of motivation. Ryan and Deci [ 30 ], assuming that each individual develops in relation to the actions he or she takes, and following many years of research, propose a macro theory which places emphasis mainly on the organic mechanisms of involving the internal resources of a human individual in his or her development, and more precisely in the development of personality and in self-regulation of behavior. According to these authors, the key process supporting the optimal functioning of people is their natural striving to improve and develop, manifested in the satisfaction of universal basic needs like social relationships and intimacy, competence and autonomy. They underline the role of behaviour in accordance with one’s own interests and values.

Autonomy understood in this way should not be confused with independence, although they may be interrelated. As a consequence, an individual satisfying such needs may feel pleasure and contentment. Research has shown that these needs are natural, but also that their properties are subject to situational influences that trigger intrinsic or extrinsic motivation, depending on the integrated orientation of the respective individual’s life goals [ 31 – 33 ].

The traditional conceptualization of intrinsic motivation assumes that this motivation refers to a situation in which behavior is triggered by different activities of the individual, interesting in themselves, causing spontaneous satisfaction and joy. At the same time, extrinsic motivation is clearly separated, as motivation triggering activities which are not interesting or satisfying in themselves for the individual, but which as a consequence lead to the valued effects. In this approach, extrinsic motivation is instrumental. In the context of work, however, extrinsic motivation has a dominant position and a wider range of types, contributing to the satisfaction of different needs, but according to Ryan and Deci [ 34 ], it is intrinsic, immanent motivation that represents the natural tendency an individual has to seek new challenges, learn and improve, based on enthusiasm, interests and passions. Intrinsic motivation understood in this way is a manifestation of a completely autonomous, self-determined, immanent motivation connected with the individual experiencing positive emotions [ 30 , 35 , 36 ]. The opposite of intrinsic motivation is extrinsic motivation in the form of external regulation, although in the self-determination theory there is also amotivation.

Amotivation is a state characteristic of non-autonomous behaviors, consisting in lack of regulation and reluctance to act. In the subject literature, it is compared to Seligman’s learned helplessness [ 37 ]. In the case of amotivation and external regulation, human behavior is completely independent of the individual, and it is controlled by external factors. Proper extrinsic motivation is a continuum of states regulated both extrinsically and intrinsically. It may vary in its intensity–from external regulation, through introjection and identification, to integration. Introjection is accompanied by involvement of the Ego, and behavior is partially controlled by the individual here, while in the case of identification and integration and of proper intrinsic motivation, the individual manifests fully autonomously regulated behavior. The differences in these three levels of motivation consist in the varying degree of internalization of values and goals underlying the behavior. Introjection is regulation consisting in taking action to gain self-approval and approval of those around the individual, for example by doing work to enhance one’s self-esteem, increase one’s prestige, and avoid shame. In the case of identification, the individual identifies with a set of values and meanings, accepting them as his or her own, while in the case of integration, the specific value or meaning becomes part of the system of definitions of the Self, creating the basis for autonomous regulation of behavior [ 38 , 39 ]. Therefore, identification and integration are still part of the system of extrinsic motivation, but one which is already regulated autonomously, and fully autonomous in the case of identification. The difference between autonomous regulation and integration, in the case of intrinsic motivation, boils down to activation of emotions, and in the case of integration–to cognitive activity [ 40 ].

Autonomous regulation, referring to intrinsic motivation, integration and identification, is associated with qualities such as resourcefulness and courage. Controlled regulation, i.e. introjection and external regulation mechanisms, provides the basis for industriousness, regularity, perseverance, strong will and prudence. Striving to improve oneself and implementing standards leading to an ideal image of the self represents the autonomous regulation perspective, while striving to achieve what should be achieved according to others is a manifestation of controlled regulation [ 33 ].

Work ethic involves both resourcefulness and industriousness, as well as prudence [ 21 ] and the realization of a perfect image of oneself [ 27 ]. Hence, it may be assumed that work ethic as a syndrome of beliefs which value work is associated both with autonomous motivation and with controlled, non-autonomous regulation. Traditionally, in line with the definition of work ethic, work means coercion and obligation. However, the definition of work ethic also implies the importance of individual independence, the need to rely on oneself and to strive to achieve [ 21 ]. Recent conceptualizations of work ethic also include the pursuit of excellence and mastery, which guarantee high-quality work [ 27 ].

The findings of the studies by Cassidy and Lynn [ 28 ] quoted above showed that intrinsically motivating work ethic correlates with extrinsically motivating needs, such as earning money and striving for dominance and prestige. These findings are also consistent with the research conducted by Wollack [ 41 ], in which it turned out that work ethic referred to the attitude towards pay, i.e. attributing a high value to earning money at work. The research also proved the existence of links between work ethic and social status, defining one’s position among the others and both self-perception of this status and the perception of that status by the social environment, friends, relatives and co-workers, which is associated with prestige. The work ethic conceptualization built by Wollack [ 41 ] also includes the pursuit of promotion. Status, prestige and pursuit of promotion are connected with introjection, and earning money is connected with external regulation.

Finally, some recent developments in SDT theory should be cited. In [ 42 ] the Authors studied public employee’s motivation for a public service career and developed a SDT-based measurement instrument that captures different motivations for it. A meta-analytic review [ 43 ] of almost 100 studies examining the antecedents and consequences of basic need satisfaction at work provides interesting and new contributions and challenges to the SDT literature. Through the lens of SDT in [ 44 ] the Authors tested the mediating effect of autonomy, how internal sources of innovations (i.e. emanating from an agency’s senior leadership/employee workgroups) affect employees’ job satisfaction.

Thus, if both work ethics and intrinsic motivation are associated with job satisfaction and innovation [ 21 , 25 , 44 ], it can be assumed that the work ethic and motivation also show significant relationships. The important question is which components of ethics are most strongly associated with intrinsic motivation and which are weaker.

Research questions and hypotheses.

We asked the research questions about the possible relationships between work ethic dimensions and the motivation to work, i.e. between autonomous and controlled regulation, and about the nature of them. Research questions were also put forward concerning the existence and strength of the relationship between work ethic dimensions and the individual methods of regulation, i.e. autonomous and non-autonomous regulation, as well as about whether and how work ethic dimensions correlate with amotivation.

On the basis of the considerations presented above, we hypothesize that:

H1. Positive relationships exist between the dimensions of work ethic (work as moral value and obligation, hard work, centrality of work, wasted time, anti-leisure sentiment, delay of gratification, self-reliance and morality/ethics) and autonomously regulated motivation (intrinsic motivation, integration, identification) as well as non-autonomous introjection.

H2. Positive relationships exist between the dimensions of work ethic that involve attributing value to success and to the ways of achieving it (work as moral value and obligation, wasted time and self-reliance) and non-autonomously regulated motivation (introjection and external regulation).

Materials and methods

Study sample and procedure.

A quota sampling [ 1 ] being a non-probabilistic version of stratified sampling was used to obtain a sample of participants for our study. A population was first segmented into 4 sub-groups according to the size of employment (micro-enterprises, small, medium and large businesses) based on the structure obtained from the Central Statistical Office in Poland. Samples of participants were then selected from each subgroup based on the specified proportion [ 45 ].

The sample consisted of 405 individuals working in various organizations in southern Poland. The sample included 227 women (56%) and 178 men (44%). The study covered a group of people aged 19 to 71. The average age of the respondents was over 35.23 ( SD = 12.05, Range = 19–71) years. The sample included people with different educational backgrounds. The largest number of respondents had secondary education (194 individuals, 48% of the sample), higher education (160 individuals, 39% of the sample) and vocational education (51 individuals, 13% of the sample). The study covered 90 individuals working in micro-enterprises (employing up to 9 people) (22% of the sample), 107 employees of small businesses, employing up to 49 people (26% of the sample), 84 employees of medium-sized businesses employing up to 249 people (21% of the sample), and 124 employees of large businesses (employing over 250 people) (31% of the sample).

The study subjects included individuals pursuing different professions (administrative support (105 individuals, 26% of the sample), accounting/financial (95 individuals, 23% of the sample), technology (105 individuals, 26% of the sample), health/safety (100 individuals, 25% of the sample)) and employed in various industries (manufacturing (150 individuals, 37% of the sample), services (130 individuals, 32% of the sample), retail (125 individuals, 31% of the sample)). The majority of the study subjects (283 individuals, 70% of the sample) worked under an employment contract, full-time, 57 individuals (14% of the sample) were self-employed, and 65 individuals (16% of the sample) worked under civil law contracts. The majority were employees of businesses with nationwide reach (302 individuals, 75% of the sample), while the remaining group of 103 individuals (25% of the sample) worked in companies with international reach. The average length of service being 12.94 ( SD = 11.64, Range = 0.5–45) years.

Efforts were made to examine people of different ages, both women and men, employees working for a given company for at least six months in various industries.

The research was conducted in 2018, from June to December. The respondents did not receive any remuneration for their participation in the survey and filled out a set of questionnaires using the paper and pencil form.

The research was conducted in compliance with the ethical standards in line with the provisions of the Declaration of Helsinki. The Departmental Research Ethics Committee of Faculty of Psychology at SWPS University of Social Sciences and Humanities (Katowice, Poland) (Ref. number: WKEB63/05/2020/Human participants, project title: Relationships between work ethic and motivation to work from the point of view of the self-determination theory) approved the research proposal and the consent procedure. The respondents agreed to participate voluntarily, they were informed about its purpose, assured about its complete anonymity, and obtained information about the possibility of withdrawing from it at any time.

To measure work ethic we used the Polish version of Multidimensional Work Ethic Profile (MWEP), an abridged version of the MWEP questionnaire created by Miller [ 24 ], adapted by Grabowski and Chudzicka-Czupała [ 23 , 46 ], and abridged by Grabowski [ 47 ]. The questionnaire is composed of 35 items and 7 scales (or 7 subscales) (with 5 items in each scale), which correspond with 7 dimensions of work ethic: belief in the sense of hard work (Hard work), Centrality of work, distaste for wasting time (Wasted time), distaste for leisure (Anti-leisure sentiment), Delay of gratification, Self-reliance and morality and ethics (Morality/Ethics). Five statements were added to the list of 35 items mentioned above, related to the conviction that work is a value and a moral obligation (Work as moral obligation—WMO scale).

Participants indicated their attitudes toward statements using a 1 (“I strongly disagree”) to 5 (“I strongly agree”) scale. Statistical analyses also used an index constituting the sum of all the seven subscales, i.e. MWEP-total, without the WMO scale.

To study motivation to work, the Work Extrinsic and Intrinsic Motivation Scale (WEIMS) was used, built by Canadian psychologists [ 48 ], in the Polish adaptation by Chrupała-Pniak and Grabowski [ 49 ]. Both the original tool and the Polish adaptation demonstrate satisfactory psychometric properties. The scale represents an operationalization of the individual regulations of motivation, taken into account in the self-determination theory, i.e. intrinsic motivation, integration, identification, introjection, external regulation and amotivation. The original tool consists of 18 items, with 3 scale items corresponding to each of the six regulations (six scales or subscales of WEIMS). A 24-item method was used in the study, with one statement added to each scale (subscale).

The respondents’ task was to take a position on the items using a seven-point scale from 1 to 7 (with 1 meaning “This statement doesn’t describe me at all”, 3 –“This statement describes me in rather moderately”, 7 –“This statement describes me absolutely accurately”).

The Work Self-Determination Index (WSDI) was also used in the calculations. This index is calculated using the following formula: -3*amotivation + -2* external regulation + -1*introjection + 1*identification + 2*integration + 3*intrinsic motivation; and it simply means the degree of self-determination of behavior at work [ 48 , 49 ].

Table 1 presents descriptive statistics and the reliability coefficients i.e. Cronbach’s alpha and McDonald’s omega of Multidimensional Work Ethic Profile (MWEP), Work Extrinsic and Intrinsic Motivation Scale (WEIMS) subscales and global indices (MWEP, the sum of 7 dimensions, Work Self-Determination Index WSDI).


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The amotivation scale obtained a lower Cronbach’s α value in these studies, just like in previous studies, by the way, both on Polish and on Canadian samples [ 48 ], and its revision should be considered in the future.

The validity of the modified WEIMS version, which includes 24 items, was also checked by means of confirmatory factor analysis. A confirmatory factor analysis demonstrated that the WEIMS scale achieved satisfactory measures of fit of the six-factor model to the data (comprising four positions in each scale): χ2 (df) = 789.49 (237), RMSEA = 0.076, CFI = 0.96, sRMR = 0.071, NFI = 0.95 [ 49 , 50 ].

Data analysis.

Descriptive statistics, reliability coefficients and correlations were calculated with JASP (v0.12.2), a Confirmatory Factor Analysis (CFA) conducted using JASP (v0.12.2) and the Lisrel (v9.2) software, and Canonical Correlation Analysis (CCA) was conducted using STATISTICA (v12.0).

Canonical correlation analysis.

We used the multivariate statistical method, Canonical Correlation Analysis (CCA) [ 51 , 52 ] to verify the two hypothesis and to investigate the magnitude and sign of the relationships between two sets of variables, one comprising the dimensions of work ethic construct and referred to as independent variables, and the second composed of factors from work extrinsic and intrinsic motivation, considered here as dependent variables.

The main goal of CCA is an assessment of the simultaneous interrelationships between two sets of variables. CCA focuses on the correlation between two new synthetic variables, called canonical variates , one is a linear combination of variables from the first set and the other is a linear combination of the variables of the second set. CCA constructs a canonical function that maximizes the canonical correlation coefficient which measures the strength of the overall relationship (correlational) between the two canonical variates. CCA develops multiple canonical functions, each is independent from the other canonical functions so that they represent different relationships found among the sets of dependent and independent variables. Each canonical variate is interpreted with canonical loadings , the correlation of the individual variables and their respective variates. Redundancy index is an amount of variance in a canonical variate (dependent or independent) explained by the other/opposite canonical variate in the canonical function. These may be summed to reveal an overall redundancy index .

Preliminary analyses

Table 2 presents the correlation coefficients between individual dimensions of work ethic and motivation together with global indices (MWEP, the sum of 7 dimensions, Work Self-Determination Index WSDI).


It follows from the Table 2 , as expected, that dimensions of work ethic are positively correlated, weak (about 0.1), moderate (0.2 or 0.3) and average (0.4) with motivation that is regulated autonomously (identification, integration and intrinsic motivation) as well as the non-autonomous introjection. The strongest correlations of the mentioned regulations exist with the Centrality of work, the moderate—with the Work as moral obligation, Hard work and Anti-leisure. Amotivation is correlated with the dimensions of work ethic very weakly, rather negatively and not significant, except from Morality/ethics.

Results of Canonical Correlation Analysis (CCA)

Table 3 presents the results of the CCA. The results of tests of significance prove that only the first two canonical functions ((U1, V1), (U2, V2)) were statistically significant with p -values < 0.001 of the testing procedure of the canonical correlations (as implemented in STATISTICA package). The independent canonical variates U1, U2 are linear combinations of variables from the first set of variables defining work ethic construct, while the canonical variates V1, V2 are linear combinations of variables from the second set of variables defining work motivation (see Table 3 ).


Results of CCA for two canonical functions: canonical correlations, loadings, shared variance and redundancy analysis of independent and dependent canonical variates.

To assess the contributions of the variables defining work ethic and motivation canonical variates in the canonical correlation, we used canonical loadings (assuming here that a loading greater than 0.4 proves that correlation between a corresponding variable and a variate is significant).

The first canonical correlation between the independent variate U1, being a linear combination of work ethic variables and V1, the dependent variate—a linear combination of work motivation variables is quite strong and equals to 0.585.

In the dependent variate V1, the highest and positive canonical loadings had intrinsic motivation (0.931), integration (0.858), introjection (0.782) and identification (0.620). According to the self-determination theory, the intrinsic motivation, integration and identification constitute the components of an autonomous motivation. This fact supports naming the canonical variate V1 as the “ high autonomous motivation ”. Moreover, it should be seen a strong positive correlation of variate V1 with introjection (0.782), which means that autonomous motivation is associated with striving after self and other approbations, thereby being a sense of duty. It caused to name the variate V1 of the first canonical function, the “ high autonomous motivation and duty ”. It should be noted that an amotivation variable had low negative correlation with the variate V1 and an external regulation is not correlated with it. The corresponding to V1, dependent variate U1 we call “ centrality of work in life ” because its highest canonical loading is that of Centrality of work (0.920). The remaining variables from the first set of work ethic construct, except for Hard work (0.585), show almost half the correlations, although still high: Anti-leisure (0.448), Work as moral obligation (0.412), Delay of gratification (0.405).

The canonical variate U1 in the first canonical function, explains 25.3% of the variance in the set of work ethic variables, and the associated variate V1–43.6% of the variance in the set of work motivation variables (see Table 2 for the shared variances).The independent canonical variate U1 for work ethic in the first canonical correlation “ centrality of work in life ”->“ high autonomous motivation and duty ” explains almost 15% (14.9%) of the variance in the dependent set of variables from work motivation (see Table 3 for redundancy index in dependent set).

In summary, the results of this study allow for the conclusion that people with high autonomous motivation and conviction that work is a duty, treat the work as a central value in their life more often, while the remaining activities could be less important.

In the second canonical function, the correlation between the independent variate U2, being a linear combination of work ethic variables and the dependent variate V2—a linear combination of work motivation variables is somewhat weaker and equals to 0.362.

We call the canonical variate U2 “ hard work ” as the canonical loading of the variable hard work is the highest (0.619). Simultaneously, we observe quite strong canonical loadings from the following variables defining work ethic: self-reliance and wasted time (0.532 and 0.531, respectively). This is equivalent to a conviction that hard, intensive work, self-reliance and saving time lead to a success, or ensure a prosperity in life. The highest canonical loading in the second, dependent variate V2 had external regulation (0.807), which is equivalent to a regulation controlled by awards and penalties. Simultaneously, the lowest canonical loadings in the variate V2 come from intrinsic motivation (0.122) which is an evidence of an autonomous regulation. This fact allows to name the canonical variate V2 as “ external control ”. At the same time, there is quite strong correlation with the variable introjection (0.451), which means that hard work motivated by a wish to gain approval from others is connected with obtaining through a work such awards like money.

The canonical variate U2 in the second canonical function, explains 15.6% of the variance in the set of work ethic variables, and the associated variate U1–18.3% of the variance in the set of work motivation variables (see Table 2 for the shared variances). The independent canonical variate U2 for work ethic in the second canonical correlation “ hard work ” -> “ external control ” explains only 2.4% of the variance in the dependent set of variables from work motivation (see Table 3 for redundancy index in dependent set).

The overall redundancy of dependent set of variables is equal to 18.2%. This means that 18.2% of variance in work motivation variables can be explained by the whole set of independent work ethic variables (i.e. predictors).

Discussion and conclusions

The main aim of this exploratory research was to determine whether any relationships could be found between work ethic dimensions and motivation to work described by the self-determination theory, i.e. relationships with autonomous and controlled regulation. These regulations characterize human activity during the performance of work.

The research findings show that there are positive relationships between work ethic on the one hand and autonomous motivation and striving for recognition (including recognition from other people and self-satisfaction) on the other hand. There is a significant positive correlation between the dimension of centrality of work on the one hand and autonomous motivation and duty on the other hand. In other words, individuals who insist on the centrality of work, who value it highly, also in the moral sense, and who are convinced of the value of hard work, are at the same time highly motivated to do work they find exciting, as a component of their identity. At the same time, these individuals are also convinced that work should be done well and accurately. On the one hand, they find work exciting, interesting and challenging, on the other hand they believe that one should strive towards mastery when performing it, and treat this as a duty.

Individuals displaying autonomous motivation at work may treat good performance of the latter as a duty. This is one of the possible interpretations of the relationship between autonomous motivation and non-autonomous introjection. It can also be noted that high scores on the introjection scale do not have to indicate only actions resulting from the desire to gain recognition. It may also be a result of the fact that individuals motivated to perform work autonomously satisfy their general need to have positive relationships with other people [ 29 ]. Striving to be recognized and respected by others is a way of satisfying this need, and at the same time achieving this proves that the duty has been performed well. In other words, high scores on the introjection scale can mean that the individual motivated to a large extent intrinsically wants to win interest and approval from the environment because of the good performance of tasks.

Research has also shown that high value given to hard work, the conviction that it leads to success, combined with the belief that one needs to rely on oneself and avoid being dependent on others, is at the same time associated with the will to work for material rewards and with the pursuit of approval. These are extrinsic factors that are important for the performance of work. Although surprising, this result is consistent with the classical Protestant work ethic approach, in which we find both encouragement to do work out of duty, because work is an obligation, and affirmation of the pursuit of success, positive valuation of extrinsic indicators of success, such as the desire to earn money [ 21 ]. This result is also consistent with the research by Cassidy and Lynn [ 26 ] and the earlier studies by Wollack [ 41 ]. On the basis of the results obtained, hypotheses 1 and 2 can be accepted. The results also show that amotivation correlates negatively and weakly with the dimensions of work ethic.

To recapitulate, individuals with high autonomous motivation, a high need for recognition, and high intensity of introjection treat work much more often as a central value in their lives, while other activities are less important for them. Performance of interesting work which they like most probably makes it easy for them to value it highly, which co-occurs with their intrinsic need to take up and do work and their desire to maintain a good opinion of themselves as an employee and at the same time gain a positive opinion of their environment. Autonomous motivation co-occurs with introjection. An individual with autonomous motivation, having a high intrinsic motivation, treats good performance of work as his or her duty. Secondly, interesting work can be a source of high status and prestige, which is associated with activity being driven by the motivation to gain approval. This is also in line with earlier research results [ 22 , 28 ].

High scores on the introjection scale may generally indicate the fact that individuals autonomously motivated to work satisfy the need for positive relationships with others and for gaining recognition from others. According to the self-determination theory, controlled regulation, including introjection and external regulation, means striving to satisfy the need for positive relationships with others and for competence. Autonomous regulation, apart from satisfying these two needs, also makes it possible to satisfy the need for autonomy [ 31 ]. Intrinsic motivation combines all these motives, including those assigned to the other types of motivation, i.e. striving for integration, identification, introjection and external regulation. Only amotivation, or impersonal regulation, points to a lack of desire to satisfy these three needs. Amotivation also demonstrates a relationship with extrinsic control, i.e. controlled regulation. The results of the study described here show that activity based on extrinsic rewards may lead to amotivation. In the results of canonical analysis, this is proven by the weak positive correlation between amotivation and external regulation, and more precisely with the extrinsic control factor [ 35 , 36 , 53 ].

The study has a few limitations. First is the Polish context of our research. Work is less valued in Poland than, for example, in the United States [ 46 ], but more than in other countries [ 21 , 22 ]. It can therefore be assumed that Poles may have a lower work ethic than the inhabitants of post-Protestant countries. That is why our findings may not be generalized to other cultural settings, particularly outside of the Eastern Europe.Only the cross-cultural study would make it possible to compare Polish employees’ responses with the attitudes of representatives from other countries. Another limitation is that the study was based on self-assessment questionnaires. Their use resulted from the lack of other tools for measuring the studied variables as well as from the nature and definition of these variables, based on subjective judgment. However, these were accurate and reliable tools. Only the operationalization of specific regulation styles may be considered questionable due to the high correlations of introjection with identification, integration and intrinsic motivation [ 43 ]. It should be recalled, however, that within the self-determination theory itself, intrinsic (autonomous) motivation is based on mechanisms reserved for controlled regulation. Autonomous motivation leads to the satisfaction of three basic needs, while controlled motivation leads to the satisfaction of two needs [ 31 ].

Although the respondents were assured of anonymity, the responses might also be falsified due to the effect of the study subjects responding in accordance with what they imagine to be the socially desirable content, which in turn may have affected the final results of the study. However, an attempt was made to counteract this phenomenon by providing appropriate instructions and by assuring the respondents about the complete confidentiality of the data.

The research methodology could be improved and broadened by adding qualitative methods such as interviews and analyses based on interpretative phenomenological analysis (IPA). This would provide a deeper insight into the respondents’ feelings and into their experiences, and could definitely expand knowledge about the relationships between work ethic and motivation. Further research should also focus on the importance of other variables. It is worth checking the level of selected variables that may be relevant here, such as e.g. temperamental and personality determinants, other psychological characteristics, or characteristics related to morality. It may also be significant to take into account simultaneously the characteristics of the working environment and the organizational climate. Another significant development might involve controlling for the level of the respondents’ satisfaction with their professional work. It would be worth comparing in the future the dependencies existing within the group of managers, entrepreneurs and non-managers, as one may expect that the relationships between work ethic, attitude towards work and motivation might be more distinct in individuals with considerable autonomy, and that senior-level managers or entrepreneurs with considerable freedom of action are less likely to be forced to act under coercion.

In future research, it would be worthwhile controlling also for employee behavior that may be related to work ethic and result from motivation, or be connected to amotivation, such as civic organizational behavior, counterproductive behavior, and unethical pro-organizational behavior. Additionally, it could be interesting to consider the importance of work ethic and motivation to perform work in ethical or strategic decision-making within the company, e.g. in the way of implementing the CSR strategy, with simultaneous control for dispositional and environmental variables.

Research implications suggest that the findings may be important for the practice. We imagine workshops on work ethic and motivation, participation in which would let the individuals obtain better insight into the meaning of their own values, needs, and attitudes connected with work and into sources of their own motivation. It would be advisable to train individuals by focusing on the strengthening of their motivation, basing on their specific beliefs about work.

On the basis of the research findings, it can be assumed that a high work ethic characterizes more often individuals who display high intrinsic motivation, are motivated to perform interesting work, and strive to achieve high standards in it. The results may also point to the satisfaction of the need to have a positive opinion about oneself, as well as to the need for recognition and prestige, by individuals autonomously motivated to work. Attributing high value to hard work, the belief that it leads to success, and self-reliance are also related to the willingness to work for external, material rewards, and may result from the pursuit of positive relationships with others.

Research into the relationships between work ethic and motivation to work is in the exploratory phase, so both theoretical models and potential causal models require further empirical research. We firmly believe that despite these limitations and the lack of final theoretical conclusions, the research presented here contributes to a more complete understanding of human attitude towards work and points to important sources of motivation to work, as well as constitutes an important step towards building a more complete model of the interrelationships between the two variables.

Supporting information

S1 table. descriptive statistics and reliability coefficients of work ethic dimensions (mwep) and components of motivation to work (weims)..

M = Mean value, SD = Standard deviation, MWEP–Multidimensional work ethic profile, α = Cronbach’s α , ω = McDonald’s ω —reliability coefficients.

S2 Table. Correlations between dimensions of work ethic and components of motivation to work.

MWEP–Multidimensional work ethic profile, *** p < .001; ** p < .01; * p < .05.

S3 Table. Work ethic and motivation.

Results of CCA for two canonical functions: canonical correlations, loadings, shared variance and redundancy analysis of independent and dependent canonical variates. *** p < .001.


The authors gratefully acknowledge the cooperation and efforts of different organizations who assisted in data gathering. We would like to express our gratitude to all of the participants of the study and to all the persons managing the institutions where the research took place for their help.

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Impact of academic integrity on workplace ethical behaviour

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International Journal for Educational Integrity volume  16 , Article number:  2 ( 2020 ) Cite this article

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Corruption is a serious problem in Mexico and the available information regarding the levels of academic dishonesty in Mexico is not very encouraging. Academic integrity is essential in any teaching-learning process focussed on achieving the highest standards of excellence and learning. Promoting and experiencing academic integrity within the university context has a twofold purpose: to achieve the necessary learnings and skills to appropriately perform a specific profession and to develop an ethical perspective which leads to correct decision making. The objective of this study is to explore the relationship between academic integrity and ethical behaviour, particularly workplace behaviour. The study adopts a quantitative, hypothetical and deductive approach. A questionnaire was applied to 1203 college students to gather information regarding the frequency in which they undertake acts of dishonesty in different environments and in regards to the severity they assign to each type of infraction. The results reflect that students who report committing acts against academic integrity also report being involved in dishonest activities in other contexts, and that students who consider academic breaches less serious, report being engaged in academic misconduct more frequently in different contexts. In view of these results, it is unavoidable to reflect on the role that educational institutions and businesses can adopt in the development of programmes to promote a culture of academic integrity which: design educational experiences to foster learning, better prepare students to fully meet their academic obligations, highlight the benefits of doing so, prevent the severity and consequences of dishonest actions, discourage cheating and establish clear and efficient processes to sanction those students who are found responsible for academic breaches.


Corruption and dishonesty are deeply rooted problems and have a long history in many countries and communities and Mexico is no exception. There is usually more attention given to corrupt activities perpetrated by government authorities and public officers. The fact that many of these instances of corruption are carried out with the collusion of private sector businesses and individuals is largely ignored. Private citizens themselves are usually involved in corrupt activities where they can gain a personal benefit through the abuse of their position of power or authority (Rose-Ackerman and Palifka 2016 ).

Rose-Ackerman and Palifka ( 2016 ) affirm that personal ethical standards are one of the three categories of causes that promote corruption. This moral “compass” develops through a long and complex educational process which starts at home and, we could say, ends with death. Education becomes one of the key elements in the global strategy for the promotion of a culture of integrity and the fight against corruption. It is difficult to think that education can contribute efficiently if the phenomenon of academic dishonesty exists within the educational sphere. To develop a moral compass, it is not enough to know what has to be done, it is essential to do good (Amilburu 2005 ).

In almost every educational system in the world, it is a widely held view that all people must receive mandatory basic education, thus, almost all children and youths are subject to experience -or not experience- academic integrity during their education, a period that is long enough to develop habits. Daily behaviours during these mainly formative years may be considered as the standard that can perpetuate itself over time (Programa de las Naciones Unidas para el Desarrollo 2015 ).

In addition to the work carried out by the basic educational system, the university must fully form and develop the moral vision and purpose of its students, since it is not possible to consider professional education separate from ethical formation. Being a professional must include not only mastery of technical, practical and/or theoretical competencies, but also personal integrity and ethical professional behaviour that helps to give an ethical meaning to all university endeavours (Bolívar 2005 ). In so doing, academic integrity is necessary to learn and an essential requirement of academic quality.

Academic integrity is much more than avoiding dishonest practices such as copying during exams, plagiarizing or contract cheating; it implies an engagement with learning and work which is well done, complete, and focused on a good purpose – learning. It also involves using appropriate means, genuine effort and good skills. Mainly it implies diligently taking advantage of all learning experiences. From this perspective, experiencing and promoting academic integrity in the university context has a twofold purpose: achieving the learning intended to develop the necessary competencies and skills for a specific profession and, more importantly, developing an ethical perspective for principled decision making applicable to any context (Bolívar 2005 ).

Orosz et al. ( 2018 ) identified a strong relationship between academic dishonesty and the level of corruption of a country. Other studies (Blankenship and Whitley 2000 ; Harding et al. 2004 ; Laduke 2013 ; Nonis and Swift 2001 ; Sims 1993 ) demonstrate that students who engage in dishonest activities in the academic context, particularly undergraduate students, are more likely to demonstrate inappropriate behaviours during their professional life and vice versa.

From this point of view one can say that: the individual who is used to cheating in college, has a higher probability of doing so in the professional and work fields (Harding et al. 2004 ; Payan et al. 2010 ; Sims 1993 ).

Taking these studies in other parts of the world as a reference, the objective of the current work is to determine the relationship between the most frequent academic dishonesty practices, or lack of academic integrity amongst college students, and their predisposition to demonstrate ethical behaviour at work and in their daily lives within the Mexican context.

This research paper is divided into four sections. The first one presents a brief review of literature on academic integrity, academic dishonesty and its relationship with workplace ethical behaviour. The second section presents the methodology followed during the study, considering the design and validation of the instrument, data gathering, and the generation of academic dishonesty and ethical behaviour indexes. The third section shows the results of the analysis and its discussion. The last section displays a series of conclusions for the research presented, as well as its limitations and scope.

Literature review

  • Academic integrity

According to Bosch and Cavallotti ( 2016 ), the term integrity has four common elements that are included in the different ways to describe it: justice, coherence, ethical principles and appropriate motivation. Thus, a definition in accordance to this concept would be to act with justice and coherence, following ethical principles and a motivation focused on good purposes. In the educational context, academic integrity could be understood as the habit of studying and carrying out academic work with justice and coherence, seeking to learn and to be motivated by the service that this learning can provide others. However, there has been a wide variety of interpretations about this concept (Fishman 2016 ).

The International Center for Academic Integrity (ICAI), conceptualizes academic integrity as a series of basic principles which are the foundation for success in any aspect of life and represent essential elements that allow achievement of the necessary learning which enable the future student to face and overcome any personal and professional challenges (International Center for Academic Integrity 2014 ).

Academic integrity is considered a fundamental quality for every academic endeavour, essential in any teaching-learning process focused on achieving the highest standards of excellence and learning and thus, it must represent a goal to which every academic institution, seriously engaged in quality, must aspire to (Bertram-Gallant 2016 ). Enacting academic integrity means taking action with responsibility, honesty, respect, trust, fairness, and courage in any activity related to academic work and avoiding any kind of cheating or dishonest action even when the work is especially difficult (International Center for Academic Integrity 2014 ).

The current approaches to academic integrity provide ideas offering a conceptual framework, but there is still the need to specify concrete academic integrity behaviours characteristic of students such as: speaking the truth, complying with classes and assignments, carrying out activities by their own efforts, following the instructions given, providing answers on exams with only the material approved, citing and giving credit to others’ work, and collaborating fairly during teamwork assignments (Hall and Kuh 1998 ; Von Dran et al. 2001 ). To these “observable” behaviours we must add a condition: that they must be preceded by the desire to learn in order to call them genuine manifestations of academic integrity (Olt 2002 ; Sultana 2018 ).

Despite the importance of the academic integrity concept, in most cases it is common to find an explanation of the concept in more negative terms that refers to behaviours that should be avoided. The general idea expressed in most honor codes is that academic integrity is to do academic work avoiding dishonesty, fraud or misconduct.

Dishonesty and academic fraud

Stephens ( 2016 ) argues that the problem of cheating is endemic and is at the root of human nature, thus it should not be surprising that it occurs. It is a strategy, conscious or not, used by humans to solve a problem. However, recognizing that cheating has always existed should not foster a passive and pessimistic attitude since human beings have a conscience that enables them to discern ethical behaviours from those that are not.

Understanding the phenomenon of dishonesty is important since the strategies used to try to counteract it will depend on this. For example, if dishonesty is considered a genetic disorder that some people suffer, the way to deal with it would be to identify those who suffer from it, supervise them, segregate them and/or try to “treat” them. If it is a common deficiency that everyone experiences to a greater or smaller degree, other kinds of tactics should be used to counteract it (Ariely 2013 ).

In general terms, there are different types of academic dishonesty that may be grouped into four major categories:

Copying. Copying or attempting to copy from a classmate during an examination or assessment.

Plagiarism. Copying, paraphrasing or using another author’s ideas without citing or giving the corresponding credit to them.

Collusion. Collaboration with someone else’s dishonesty, and includes not reporting dishonest actions which have been witnessed. The most representative actions of this type of misconduct are: submitting assignments on behalf of classmates, allowing others to copy from you during an exam and including the names of people who did not participate in teamwork assignments or projects.

Cheating. Among the most common actions in this category we find: using notes, technology or other forbidden materials during an exam; including non-consulted references; inventing or making up data in assignments or lab reports; contract cheating; distributing or commercializing exams or assignments; submitting apocryphal documents; impersonating another student’s identity; stealing exams; altering grades; bribing individuals to improve grades.

The list is not exhaustive since it does not include every possible type of dishonesty. Every situation creates unique circumstances and different nuances so it should not be surprising that the emergence of “new” ways to threaten academic integrity arise (Bertram-Gallant 2016 ). Students’ creativity and the continual development of technology will cause different manifestations of academic fraud (Gino and Ariely 2012 ), a fact that has been documented in university contexts in the past.

The results of recent research show that 66% of students have engaged in some type of academic misconduct at least once during their university education (Lang 2013 ). There are similar results in other studies carried out around the world. In the Mexican case, 84% of students in a Mexican university have witnessed a dishonest action during their education (UDEM 2018 ), and 6 out of 10 at another university have engaged in some kind of copying (UNAM 2013 ). In Colombia, a private university reported that 63% of the students accepted the addition of the name of a classmate that did not collaborate actively on a team assignment (EAFIT 2016 ). In England, half of the students would be willing to buy an assignment (Rigby et al. 2015 ). In Ukraine, 82% of students have used non-authorized support during exams (Stephens et al. 2010 ). While in China, 71% of students at one university admit to having copied a homework assignment from his/her classmates (Ma et al. 2013 ).

Academic dishonesty and its relationship with the lack of ethical professional behaviour

Establishing a relationship between the level of corruption in a country and the level of academic dishonesty in its educational institutions is a difficult task to carry out since fraud and corruption have many different forms and causes, particularly in complex contexts such as the social dynamics of a country (International Transparency 2017 ). However, it can be established that academic dishonesty is a manifestation of a culture in which it is easy and common to break rules and where integrity is not as valued as it should be. Under this logic, it is possible to establish a certain relationship between a poor civic culture and academic dishonesty (García-Villegas et al. 2016 ).

This poor civic culture tends to be reflected in the daily activities of the citizens, particularly within organizations, where a relationship between students who cheat and unethical behaviour in the workplace has been identified (Winrow 2015 ). From this point of view, integrity and ethical behaviour, expressed in different terms such as decision making, conflict resolution or accountability, is one of the competencies most requested by employers (Kavanagh and Drennan 2008 ) and one of the critical factors needed to efficiently develop inter-organizational relationships of trust (Connelly et al. 2018 ). This is the reason behind the study, the understanding of this relationship.

A study carried out with 1051 students from six North American universities concluded that students who considered academic dishonesty as acceptable tended to engage in such activities and the same individuals tended to show unethical behaviour later during their professional lives (Nonis and Swift 2001 ). In another study with Engineering students, it was found that those who self-reported having engaged in dishonest actions, also carried it out in the professional field, which suggests that unethical behaviour shown at the college level continued into professional life (Harding et al. 2004 ). Findings of another study carried out at a nursing school demonstrated that students who showed academic dishonesty had a greater incidence of dishonest behaviour once they worked as health professionals (Laduke 2013 ).

In a study carried out with 284 psychology students who reported having engaged in some kind of academic dishonesty, specifically having copied during exams and lying in order to meet their obligations during their college education, also reported participating in actions considered illegal or unethical within the context of the research, specifically those related to substance abuse - alcohol and drugs, risky driving, lying and other sort of illegal behaviours. This data suggests that, besides the contextual factors, there are also individual causes such as attitudes, perceptions and personality traits that can influence the individual’s behaviour in different aspects of their lives (Blankenship and Whitley 2000 ).

In one of the most recent studies, where data from 40 countries was collected, a strong relationship was identified between the self-reporting “copying in exams” of the student population and the level of corruption of the country, expressed in the corruption perception index published by Transparency International (Orosz et al. 2018 ).

Despite the increase in the number of studies related to academic integrity and ethical behaviour in the companies in different parts of the world since the 1990s, it has not been possible to identify any research in Mexico that explores the relationship between the ethical behaviour of an individual in his/her different life stages, as a college student and as a professional; or to put it differently, between academic integrity and ethical performance in the workplace.


This study followed a quantitative approach under a hypothetic - deductive approach. Since there is no suitable instrument available that explores the relationship between academic integrity and ethical behaviour, one designed for this study was used. It was based on questions from previous research instruments.

The “International Center for Academic Integrity” (ICAI) perception survey, created by Donald McCabe and applied to more than 90,000 students in the United States and Canada (McCabe 2016 ) was adapted with the addition of a section of questions related to personal and workplace ethical behaviour.

The McCabe survey ( 2016 ) consists of 35 questions that can be grouped into four sections. The first one explores the characteristics of the academic integrity programme, the educational atmosphere in general and the way in which the community is informed and trained in regards to current regulations. The second one requests information about the students’ behaviour. It specifically asks about the frequency with which students are involved in dishonest activities at the moment and in previous academic levels, how severe they considered each kind of misconduct and their perception in regards to the level of peer participation in actions against integrity. The third section collects the opinions of the students regarding different statements related to academic work, faculty and students’ engagement in the development of an academic integrity culture, strategies to fight dishonesty, the degree of social approval towards academic fraud, its impact and the perception of fairness in managing the cases of misconduct. The last group included demographic questions that contained basic information about the person answering the survey. The students were asked to provide their age, gender, marital status, nationality, place of residence, accumulated grade point average (GPA), programme he/she studies and the number of years at the university.

A section was added to this survey (Additional file  1 ) addressing the professional ethical behavioural construct. In this section, items from questionnaires described in Table  1 were used; all related to self-reporting of ethical behaviour. An additional validation was carried out for this instrument section through the assessment of experts from the internal control area of different companies and industries.

Except for a couple of open questions, the rest of the items used responses built under a five-point Likert scale to categorize their judgments in regards to the statements suggested. There are two types of responses used specifically: from totally agree to totally disagree about the perceptions and opinions; and always or never in the case of self-reported behaviours.

The responses were recorded automatically in the data base of the SurveyMonkey technology tool and values were assigned to each one of the responses in order to calculate an index per response, assigning a value of 5 to “Totally agree” and 1 to “Totally disagree” in a positive or favorable statement, and vice-versa, 1 and 5 respectively, in a negative or unfavorable statement.

The sample considers 1203 undergraduate and graduate students from a private university in northern Mexico who chose to respond to their professors’ invitations to answer the survey as part of a diagnostic exercise that the university carries out periodically to learn about the students’ perceptions regarding the degree of academic integrity culture on their campus. The participants were 51% women and 49% men. From them, 31% were in their first year, 25% the second year, 26% the third year, 11% the fourth year and only 7% had been studying for five or more years. Nearly 70% of the students still lived in their parents’ homes and 42% reported having a good or outstanding average grade (higher than 80 over 100).

Once the data was collected, the internal validation of the instrument was done and indexes were generated for each one of the variables introduced into the model, through a factorial analysis of the main components. This type of analysis studies the relationship between a set of indicators or variables observed and one or more factors related to the research to obtain evidence and thus, validate the theoretical model (Hayton et al. 2004 ).

In order to define the indexes related to academic fraud and ethical behaviour there were three factorial analyses carried out, which took as selection criteria eigenvalues higher than one and varimax component rotation with the purpose to maximize the variances explained for each response and identify the items that represented the factors identified by the analysis itself in a linear way (Thompson 2004 ).

The first analysis considered questions related to the level of frequency with which specific dishonest actions were carried out. It included 27 items or questions in total, and five components accounted for 66.33% of the variance, with a KMO (Kaiser, Meyer and Olkin) of 0.955 and being significant for the Bartlett’s sphericity test, a fact that shows the internal consistency of the indicator and its statistical validity. The five components were classified according to the weight that each question had in the rotated and stored components matrix such as regression variables to generate an indicator for each of them (Table 5 in Appendix). These indicators were defined as frequency in: 1) cheating in general, 2) copying in any way, 3) falsifying information, 4) using unauthorized support, and 5) plagiarizing or paraphrasing without citing.

The second analysis took the same criteria of the latter, but it only included the 27 questions related to how severe the misconduct or academic dishonesty was considered. The result was three components that accounted for 67.66% of the variance observed, with a KMO of 0.962 and the Bartlett’s sphericity test was significant. The rotated components were classified and kept as a regression to generate three indicators, related to the perceived severity of: 1) cheating in general, 2) plagiarizing or copying and paraphrasing without citing, and 3) using unauthorized support (Table  6 in Appendix ).

The third factorial analysis included the 47 questions related to the behaviour or ethical attitude of the respondents. This analysis generated six components that accounted for 64.54% of the variance observed, a KMO of 0.963 and the Bartlett’s sphericity test was significant. When analyzing the components generated by the analysis, it was observed that four of them had only two questions with a weight greater than 0.4 in the rotated component matrix. Considering this situation, it was decided to eliminate these questions and a new factorial analysis was carried out considering only 39 questions. The result was two main components that accounted for 58.66% of the variance observed, with a KMO of 0.965 and the Bartlett’s sphericity test was significant. The two components were classified into two indicators: 1) workplace ethical behaviour and, 2) personal ethical behaviour (Table  7 in Appendix ).

Once the indicators for frequency and perceived severity of dishonesty or academic fraud, as well as those related to the behaviour or self-reported ethical attitude (workplace and personal) were generated, a linear regression analysis was carried out to determine how academic dishonesty influences a specific ethical behaviour.

The linear regression analysis took as dependent variables the ones related to ethical behaviour self-reported by the respondents, and the frequency and severity of the academic dishonesty acts reported by the respondents as the independent variables. This analysis was carried out in two stages; the first one considered only the variable of the frequency with which academic dishonesty was reported, and the second one considered the variables related to the severity with which the respondents perceived these actions.

The first analysis took as independent variables the frequency of each component of self-reported academic misconduct: cheating in general, copying in any way, falsifying information, using unauthorized support, and plagiarizing or paraphrasing without citing. The result of the model was significant for the case of workplace ethical behaviour (sig. = 0.001), accounting for only 3.4% of the variance observed (Table  2 ). In terms of analysis by variables, it was found that only the frequency of carrying out any kind of cheating, and copying in any way, had a significant impact on the workplace ethical behaviour of the respondents. The negative coefficient in both cases shows that a frequency reduction in academic misconduct, increased the self-reported workplace ethical behaviour (Table 2 ). The variables for falsifying information, using unauthorized support and plagiarizing didn’t show significance.

In terms of personal ethical behaviour, the model proved significant (sig. = 0.000) explaining 9% of the variance (Table 2 ) thus it may be stated that the severity of academic dishonesty influences personal ethical behaviour. In regards to the impact level that the variables have on personal ethical behaviour, we found that only using unauthorized support did not prove significant. The remaining variables were significant and with negative coefficients, thus we may conclude that the lower the frequency of academic dishonesty reported by the respondents, the higher the reported personal ethical behaviour. In this sense, the variable of cheating in general had a greater weight in this kind of behaviour, followed by falsifying information and lastly plagiarizing.

The obtained results indicate that engaging in academic dishonesty with a greater frequency is directly and negatively related to the respondent’s ethical behaviour and attitude. Therefore, it can be assumed that discouraging students from carrying out academic dishonesty will have a positive effect on their ethical behaviour, both in the work context as well as in their daily lives. In the same way, it was also found that respondents who performed academic dishonest activities less frequently, tended to have better ethical behaviour in general.

It is interesting to observe that the model does little to explain workplace ethical behaviour and that only the variable of cheating in general and copying had significant impacts on this behaviour. While in the case of personal ethical behaviour, academic dishonesty practices occurred more frequently and only the use of unauthorized support had no significant impact. This situation allows us to assume that academic dishonesty practices have a greater impact on daily ethical behaviour but less so in the workplace. This situation can be explained by the fact that organizations have codes of ethics and programmes which guide actions to be carried out by their personnel that are based on specific ethical and moral rules of conduct.

The second regression analysis took as independent variables the ones related to the perceived severity of the respondents in regards to cheating in general, copying and plagiarizing, and using unauthorized support. As in the previous case, the dependent variables were the ones related to the behaviour or ethical attitude in the workplace and in personal contexts. In regards to the workplace, we found that the model proved significant (sig. = 0.000), explaining 10% of the variance observed (Table 3 ). Despite this result, the variable analysis showed that only the cheating in general variable had a significant impact on such behaviour with a positive coefficient, which means that the greater the perceived severity of the misconduct, the better the ethical behaviour within the organization.

In the case of personal ethical behaviour, the model also proved significant (sig. = 0.001), explaining only 5% of the variance observed in the indicator. In the case of workplace ethical behaviour, only the perceived severity of cheating in general variable had a significant impact on personal ethical behaviour. The positive coefficient of this variable enables us to establish that when any type of cheating was rated as severe, respondents tended to have better personal ethical behaviour (Table 3 ).

The findings enable us to recognize the impact that the perceived severity towards cheating in general has on the ethical behaviour of the respondents, since it is the only variable that proved significant in the model. Hence, the extent to which students perceived the committing of any kind of cheating within the university as severe, their behaviour, both inside and outside the workplace, was more ethical.

Additionally, it is interesting to observe that the perception of the severity of cheating, plagiarizing or using any kind of unauthorized help does not have a significant impact on the ethical behaviour self-reported by the respondents. Therefore, it can be assumed that it is not as important to point out the severity of a specific act of academic dishonesty to influence the ethical behaviour of students and professionals, but rather to emphasize the severity of the misconduct that is associated with any act of academic dishonesty.

With the aim to identify the relationship that exists among all the variables of the model (frequency and severity), a third regression was conducted. This regression considered as independent variables, workplace ethical behaviour and personal ethical behaviour, and as dependent variables, the frequency and severity of academic misconduct. Both models, ethical behaviour in the workplace and personal, turned out to be significant. In the case of the workplace ethical behaviour, it was found that the model explains 9.1% of the variance of the indicator, while in the case of personal ethical behaviour, only 7.4% of the variance was explained (Table  4 ). Based on these results, it can be concluded that the lack of academic integrity generally affects people’s ethical behaviour.

It is interesting to note that, in the case of ethical behaviour in the workplace, the only variable that was significant and positive was the severity of widespread dishonesty. That is, those respondents who considered any type of dishonesty as a serious offense had a greater tendency to be ethical in their workplace. This situation may be supported by the fact that academic integrity is presented in institutionalized spaces, such as school, university or business, and where the perception of greater severity tends to limit unethical behaviour within these institutions or organizations.

On the other hand, personal ethical behaviour was significantly influenced by the variables related to committing any act of academic dishonesty in general (frequency and severity). The negative sign in frequency indicates that those who reported having committed less academic dishonesty - whichever it may be - have better ethical behaviour on a personal level. In the same way, those who consider that committing academic dishonesty is something serious, also have a better ethical behaviour on a personal level. Another variable that was significant was the frequency in plagiarism or paraphrasing without citing, in the personal ethical behaviour, being those that had a lower frequency the ones that reported a better ethical behaviour.

The results of this third regression complement the findings of the first two regressions and allow to evidence the specific weight of considering academic dishonesty as a serious fault in people’s ethical behaviour.

Based on the results generated in the previous section, some reflections and conclusions can be drawn related to academic integrity, academic misconduct, and ethical behaviour.

The respondents’ ethical behaviour shows a relationship to the practice of academic dishonesty, both in terms of the frequency with which they carry out these acts, as well as the severity they assign to them. The more severe the students consider an act of academic dishonesty, the more ethically they behave outside of the university. Likewise, it is important to establish measures to discourage or reduce the number of acts of academic misconduct, since the habitual practice of unethical actions may promote a normalization of these behaviours, and reduces a student’s interest in practising ethical behaviours after graduating from college. It is important to disclose a basic assumption, that a person faces ethical dilemmas first, in an educational environment and later, in a workplace context. This situation suggests that, since academic integrity is usually experienced earlier than workplace ethical behaviour in a person’s life, the former may influence the latter.

These results encourage the reflection on the importance of student perceptions about academic dishonesty and the opportunities they have to act on these dishonest practices. Interestingly, in terms of perception, students who have developed a conscience about the severity of any kind of cheating in an academic setting, exhibit a greater degree of ethical behaviour. Likewise, when a student frequently practices academic misconduct shows less ethical behaviour within other contexts. These findings add another reason why higher education institutions should establish systematic programmes focused on promoting a culture of academic integrity to convince students of the severity of these unethical actions, to discourage them from committing them and to punish them if the previous endeavours do not work.

The results of this study suggest that it is not enough to teach academic integrity in a theoretical or conceptual way, but that it is learned and acquired through real contexts and practices, where the prevention or discouragement of gaining benefits through misconduct contributes to student learning and development. This learning goes beyond the classroom and the university context and becomes an ethical behavioural pattern in the work and personal environments. Likewise, organizations should have ethical codes and other elements of a business ethics and compliance programme to foster a culture of integrity and continue the formative process started within educational institutions.

It can be stated that a part of a professional’s ethical behaviour is related to their awareness of the risks or severity of getting involved in academic dishonesty, as well as having the opportunity to engage in these acts. For this reason, it is not enough to convince students of the importance of following integrity criteria, it is also necessary to create an environment where cheating or deceptions are very difficult to practice. It is essential that students are convinced to act with integrity during their college years and that they are made aware of the risks or penalties that come with not doing so. This will strengthen a positive behavioural pattern in different contexts of their lives, and encourage them to become ethical professionals, business people, and citizens.

It is essential for higher education institutions to demonstrate a commitment to building a culture of academic integrity, both in terms of their awareness and their practice, since through them the ethical behaviour of students and future graduates is strengthened and forged. In this respect, the university campus is featured as a favourable environment to train individuals and promote ethical behaviour within and outside the university, meeting its commitment to the community and the world to develop more ethical and engaged citizens who do things well in all aspects of their lives.


There has been little research published regarding the relationship of students perceptions about their behaviour on academic integrity in schoolwork, and on professional performance. This study, like the ones identified previously, points out a relationship that can and should be explored in greater depth. Academic integrity - concept, benefits, strategies - and its counterpart, academic dishonesty - frequency causes, consequences, management - have not received, in México and Latin America, the attention they have earned in other countries and regions.

Considering that corruption is a major problem afflicting Mexican society and that academic dishonesty is related one way or another with corruption, it becomes particularly important to understand the academic dishonesty phenomenon in depth.

In order to achieve this, it is necessary to invest resources to identify the strategies which most effectively promote academic integrity, because doing so, not only prevents fraud and economic losses, but also builds the foundations of a more humane and fair society, resulting in a common interest. Viewed from this perspective, academic integrity is not an issue that should be addressed only within educational institutions, but it should also awaken the interest and the action of the business and production sectors.

Limitations of the research

The instrument used to collect information for this research project was a survey created with the support of others and thus the questions have only been validated in this exercise.

It is a self-reporting tool regarding ethical behaviour, that is, it reflects the self-reported participants’ perceptions of themselves and not about their own behaviours. This situation shows two limitations. The first one is that it does not discuss behaviours per se, but the perception participants have about them. The second limitation is that the results are subjected to the biases of the same person who self-reports. The results depend not only on the “objectivity” of respondent’s perception but also on the sincerity with which each question is answered. Despite the prevailing atmosphere of illegality, it is still desirable to seem somewhat honest to others. Additionally, the application of the survey was done via an electronic format on the personal devices of the participants, which can raise suspicions about the true anonymity of the participants’ responses.

Self-reported surveys leave aside the profound answers related to the causes of correlations found. A qualitative approach to the phenomenon could complement our results and lead to a more in depth analysis of the relationship between corruption and/or unethical behaviour and academic dishonesty in the Mexican context.

Another important limitation of the study, derived from its exploratory perspective, is that the instrument did not consider as a relevant variable the employment situation, years of work experience or hierarchical level of the respondents. This limitation causes the self-report of ethical behaviour in the workplace to be presented in a general way and not with a greater level of depth. However, the results found in this research and the identification of the relationship between academic integrity and ethical work behaviour in an exploratory way, open the door for studies where it is sought to deepen the understanding of this relationship that was identified by this study, as mentioned in the next section.

Implications for future investigations

As mentioned in the previous section, the following works related to the study of the academic integrity and ethical behaviour of individuals could point to the confirmation of the results found in this research. These future studies could be based on the causal relationships found in this research, which were generated based on the review of the literature and the assumptions that arise from it. In this sense, the use of structural equations is necessary as a method of confirmation from a quantitative perspective, as well as the use of a qualitative approach that contribute to a better understanding of this phenomenon. This study is a first step towards the realization of scientific research that demonstrates the impact that efforts to promote academic integrity in universities have on the ethical behaviour of its students and graduates.

It would be useful to replicate the research by gathering information periodically to validate the results and/or conduct a longitudinal study that allows monitoring of the “real-time” habits of the different graduating classes over time. Thereby, self-reporting of what happened at each moment in time would be collected and would enable researchers to explore different associations.

Many questions still remain unanswered in the Mexican context: What is academic integrity? How is it experienced? How is it perceived? How is it assessed? What are the benefits in doing so? What are the most appropriate strategies? What are the levels of academic dishonesty? Who carries it out? Why do they do it? What are the reasons that cause it? What is the mindset of people that behaves ethically? What are the reasons why someone turns out to be more or less ethical? How should it be addressed and managed? What consequences does it trigger? What role do professors and other educational stakeholders play? What is the impact of technology?

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.


Standardized coefficients

Non-standardized coefficients

International Center for Academic Integrity

Kaiser, Meyer and Olkin

Adjusted R squared


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G-D designed the study and collected the data, P-D performed the statistical analysis, H-E contributed with results analysis. All authors discussed the results and contributed to the final manuscript. All authors read and approved the final manuscript.

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ICAI’s Academic Integrity Survey – for students (McCabe 2016 ) plus ethical behaviour.

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Guerrero-Dib, J.G., Portales, L. & Heredia-Escorza, Y. Impact of academic integrity on workplace ethical behaviour. Int J Educ Integr 16 , 2 (2020).

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In 2024, most chief economists surveyed by the Forum believe generative AI will increase productivity and innovation in high-income countries. But for low-income countries, just over a third think this will be the case.

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The impact of AI on jobs was not going to be "an employment apocalypse", but that reskilling, upskilling and lifelong learning would be key to managing the transition to augmentation, he stressed.

4. More pop-up offices

LinkedIn has seen a drop in the number of fully remote job postings, from a peak of 20% in April 2022, to just 8% in December 2023, said co-founder Allen Blue, speaking in a Davos session ' The Role of the Office is Still TBC ' .

But employee interest in taking remote or hybrid jobs remains high, at around 46% of applications.

"The office is going to be in competition with working from home ... that’s a good thing for the office," he said, as management would need to innovate and create a workplace environment that "emphasizes dynamic human interaction".

Young people taking their first job want human connection, so they're more interested in hybrid than remote roles.

Martin Kocher, Austria's Federal Minister of Labour and Economy, said that some Austrian villages are actually paying for pop-up community office spaces, because people don’t want to work from home, and they can make use of other amenities close by.

He predicted the development of more pop-up office spaces away from company headquarters.

Have you read?

  • Davos 2024: 6 innovative ideas on reskilling, upskilling and building a future-ready workforce
  • From hierarchy to partnership: rethinking the employee/employer relationship in 2024

5. Skills will become even more important

With 23% of jobs expected to change in the next five years, according to the Future of Jobs Report, millions of people will need to move between declining and growing jobs.

Coursera CEO, Jeff Maggioncalda and Denis Machuel, CEO of Adecco Group AG, joined the Davos session ' The Race to Reskill ' to discuss the transferability of skills, and the potential of AI to help with personalized learning and productivity, which also levels the playing field for job opportunities globally.

But the key is in learning how to use AI and digital technologies, as Founder and CEO, Hadi Partovi, pointed out in the session ' Education Meets AI '.

When people think about job losses due to AI, he said, the risk isn't people losing their jobs to AI: "It's losing their job to somebody else who knows how to use AI. That is going to be a much greater displacement.

"It's not that the worker gets replaced by just a robot or a machine in most cases, especially for desk jobs, it's that some better or more educated worker can do that job because they can be twice as productive or three times as productive.

“The imperative is to teach how AI tools work to every citizen, and especially to our young people."

6. More women enter the workforce

In 2020, the World Bank found that potential gains from closing economic gender gaps could unlock a “gender dividend” of $172 trillion for the global economy.

But the Forum’s Global Gender Gap Report 2023 found that the Economic Participation and Opportunity gap has only closed by just over 60%.

Several sessions at Davos looked at how inclusion could benefit the economy , particularly by helping mothers return to the workforce, which could close skills gaps.

“There are 606 million women of working age in the world who are not working because of their unpaid care responsibilities, compared to 40 million men," Reshma Saujani, Founder and CEO of Moms First, explained in a session on the ‘ Workforce Behind the Workforce ’.

“At Moms First, we're working with over 130 companies in every sector, who are saying, ‘I don't have enough workers’. We are working with them to redesign their childcare packages and increase their subsidies.

“Childcare pays for itself. When you offer childcare to employees, you get higher worker productivity and lower rates of attrition, and greater rates of retention. We have to look at care as an economic issue that world leaders must actually do something about.”

Ethical AI governance: mapping a research ecosystem

  • Original Research
  • Open access
  • Published: 14 February 2024

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  • Simon Knight   ORCID: 1 , 2 ,
  • Antonette Shibani 1 &
  • Nicole Vincent 1  

How do we assess the positive and negative impacts of research about- or research that employs artificial intelligence (AI), and how adequate are existing research governance frameworks for these ends? That concern has seen significant recent attention, with various calls for change, and a plethora of emerging guideline documents across sectors. However, it is not clear what kinds of issues are expressed in research ethics with or on AI at present, nor how resources are drawn on in this process to support the navigation of ethical issues. Research Ethics Committees (RECs) have a well-established history in ethics governance, but there have been concerns about their capacity to adequately govern AI research. However, no study to date has examined the ways that AI-related projects engage with the ethics ecosystem, or its adequacy for this context. This paper analysed a single institution’s ethics applications for research related to AI, applying a socio-material lens to their analysis. Our novel methodology provides an approach to understanding ethics ecosystems across institutions. Our results suggest that existing REC models can effectively support consideration of ethical issues in AI research, we thus propose that any new materials should be embedded in this existing well-established ecosystem.

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1 Introduction

How do we assess the positive and negative impacts of research about- or research that employs artificial intelligence (AI) Footnote 1 ? This is a pressing question, with ambiguities around the role of researchers, governance bodies, and those who will use or/and be impacted by technologies, across both academic and industry contexts. While significant work has been undertaken to describe ethical challenges of AI, and develop guidance and principles to guide practice, there remains concern regarding the governance of AI research, the gap between principles and practice, and the participation of stakeholders in deciding how AI may be used about, with, for, and on them.

This paper engages with this challenge through the analysis of existing research governance material, by investigating the resources that researchers and research ethics committees (RECs) draw upon in articulating and navigating ethical issues arising out of AI-related research. Resources, such as formalised ethical principles and articulated processes, inscribe knowledge. As such, they act as reflections of knowledge and practices, while also shaping that practice through their conceptual and normative (or regulatory) impact on actors. Beyond this, knowing what resources researchers and RECs actually draw upon can provide important insights into existing knowledge and practices, as well as shape future practice. Such knowledge can also help ascertain whether the hype of AI ethics deserves the attention it’s getting, by illuminating whether—and, if so, how—the numerous published AI Ethics principles are actually used, which in turn will help to appraise the utility of such publications. In doing this we aim to contribute to understanding the ethical issues that AI-related research gives rise to and how learning about these might be (or could be) taking place. Through our socio-material analysis of materials relating to AI from a single institution’s ethics committee process, we address this concern, exploring how these materials provide a lens onto and reflection of the ethical concerns of AI research.

2 Literature review

2.1 ethical principles and practices.

To foster ethical action in the developing areas around use of AI and data, a wide range of guidance and sets of principles have been developed. A recent review identified 84 sets of AI ethics guidelines globally with 11 themes among them [ 45 ], while another review of 36 principles documents identified that consensus could be seen across eight common themes [ 32 ]. A third review of only research studies regarding ethical principles identified 27 such studies with 22 principles [ 49 ]. Finally, a fourth review of public, private, and non-governmental organization (NGO) documents providing AI guidance identified 112 such documents [ 75 ]. Significantly, this last review identified significant differences in the focus of documents produced by different stakeholders, and their production, with NGOs and public organisations covering more topics, and being more likely to have engaged participatory approaches in their development. Nevertheless, across these reviews, identified principles overlap significantly with the classic Belmont principles.

Moreover, there have been various calls to move from a focus on developing AI ethics principles, to instantiating them in practice and organisational structures to support practical ethics [ 50 , 60 , 72 , 89 , 91 ]. These calls emphasise the significance of micro-ethics or ‘ethics-in-action’, and a shift from procedural to situational ethics [ 33 , 38 , 43 , 51 , 64 ]. This shift, particularly as expressed by [ 38 ] reflects both that when we apply procedural ethics we are engaged in practices, and that this process of translation is not mechanical and requires interpretation. This is a concern of recent AI work, reflecting that ethics is fundamentally imbued with action, and ongoing interactions in design processes, in ways hard to capture in procedural ethics. In addition, recent calls have highlighted the importance of analysis of ethical issues of technologies in terms of both immediate or direct impacts (hard impacts), and long-term or indirect impacts (soft impacts), that may affect people’s lives [ 80 ].

2.2 The role of research ethics committees

Beyond the myriad of AI ethics principles, the role of governance structures in oversight of novel applications of AI has received attention, beyond the governance pages of companies and universities, in popular media coverage (e.g. [ 13 , 42 , 52 , 53 ]. These structures—in the form of Research Ethics Committees (RECs) and Institutional Review Boards (IRBs) — play a crucial role in university research internationally, with mounting pressure to create similar bodies in companies, and a recognition of the challenges such bodies face. In this paper, we will use RECs as a general term that includes medical MRECs, human HRECs, and IRBs, except where explicitly stated otherwise.

RECs are typically comprised of multi-disciplinary research experts, alongside non-research members—in some systems, including lay people—who oversee and review research that involves human participants. Footnote 2 Researchers who wish to undertake such work typically submit an application that explains what the research will involve, and how it will address key ethical principles including the Belmont principles of respect for persons (or autonomy), beneficence, and justice [ 66 ]. The role of RECs is to assure these principles are instantiated in research that is approved, and to provide feedback to researchers [ 44 ]. RECs do this by assessing materials submitted by researchers. However, due to the formalised process of this work, tensions have emerged regarding the bureaucratisation of research and control by RECs with perceptions that RECs are particularly suited to work in a bio-medical model [ 5 ], although some of these concerns may relate to local—changeable—practices rather than underlying theoretical issues [ 40 ].

2.2.1 International context of RECs

Significantly, the requirements and remit of RECs vary internationally. While research ethics systems share much common history, a number of publications have investigated similarities and variations across international ethics standards and committees [ 37 , 44 , 88 ] and common emerging themes—including that of data and AI [ 88 ].

However, there are also more or less nuanced differences in expression and execution of REC processes internationally. A particularly salient example, given that US experiences are often universalised, is found in the United States IRB guidance, which explicitly directs members as follows:

§ 46.111 Criteria for IRB approval of research : (2) Risks to subjects are reasonable in relation to anticipated benefits, if any, to subjects, and the importance of the knowledge that may reasonably be expected to result. In evaluating risks and benefits, the IRB should consider only those risks and benefits that may result from the research (as distinguished from risks and benefits of therapies subjects would receive even if not participating in the research). The IRB should not consider possible long-range effects of applying knowledge gained in the research (e.g. the possible effects of the research on public policy) as among those research risks that fall within the purview of its responsibility. [ 82 ].

In considering this quote as exemplifying the direction given in the wider document, and in comparison to international documents, we can note that IRBs receive unclear advice regarding their role in assessing merit and integrity (a key principle in the Australian model [ 70 ]), and that they must navigate the directions to (1) balance risks and benefits, with those to (2) “not consider” long-range effects [ 9 ]. Moreover, common across RECs is that they provide ‘point-in-time’ governance, but monitor and evaluate largely via periodic self-report of applicants or a complaints-based system for participants [ 20 ]. This lack of long-view consideration may create an ethical debt, through which technologies are developed without adequate consideration of long-term impacts [ 68 ].

This specific statement has thus been highlighted as a key feature in considering the adequacy of the US IRB model for AI research [ 25 ]. Importantly, we should be cautious in universalising models of ethics given cultural and contextual variation in values and practices, and in capacity and procedures for ethics governance such that universal expectations of REC review may exclude researchers from countries where no such review is available [ 55 , 90 ]. Further, complications stem from disciplinary differences, e.g. [ 18 ], and conflicts between REC guidelines and ethical norms of communities with whom research is conducted [ 21 ]. Crucially, differences in disciplinary, cultural, and other contextual features must be recognised. In places, this recognition and negotiation is a crucial part of ethical practice, because we should expect values to be contextual. In other contexts, there may be variation presently that rests on a lack of clear standards or articulation of possible norms to which we might work; expressing this is important.

2.2.2 AI and data as challenges to research ethics committees

Even outside the context of AI, concerns have been raised about what we know regarding researchers’ level of understanding of research ethics [ 10 ], and correspondingly, regarding expectations around interaction between committee members and disciplinary experts and their respective expertise [ 26 ]. However, as Hickey et al., [ 40 ] highlight, although there are various criticisms of ethics review boards, disentangling issues of practice in particular institutional committees, from more fundamental concerns with their underpinning principles, is challenging. They suggest that the criticisms of RECs can be addressed through fostering positive learning-oriented ethical review processes, adopting practices of open communication, outreach to research communities, and engagement with disciplinary expertise [ 40 ]. These suggestions are echoed by Brown et al.’s [ 17 ] specific analysis of education researchers’ views in the UK, finding that although there were concerns regarding understanding of the specific methods and issues in educational research, many respondents had positive interactions with their RECs [ 17 ]. Nevertheless, a lingering concern is that RECs act as ‘moral bureaucracies’ via a managerial audit approach to ethics, that is likely to incentivise ‘safe’ practice, and reduce productive rich dialogue regarding ethics, particularly in the context of technology [ 61 ].

Indeed, this sentiment is echoed in a discussion of the strengths and limitations of RECs’ specifically focused on AI and data research [ 29 , 30 , 31 ]. Here, two key concerns regard the nature of research conducted entirely outside university contexts (in which REC systems are mandatory and established) or in collaboration with such industry partners; and where the research involves secondary uses of publicly available datasets [ 35 ]. Footnote 3 Given these concerns, and particularly the potential for unanticipated and unintended consequences, there have been calls to adjust REC’s understanding of research and data [ 28 ]; privacy protection in the context of re-identification (e.g. [ 15 ]; and moves in some UK RECs to give greater attention to data and AI [ 39 ]. An alternative approach has also been piloted in which researchers wishing to access participating funders’ grants undertake a separate review by an ‘Ethics and Society Review (ESR) board’ [ 11 ]. This ESR is constituted of interdisciplinary researchers who review author statements regarding possible impacts and risk mitigation, and provide feedback, with positive initial evaluation of the program. Relatedly, specific guidance has been produced to support industry organisations in establishing ethics bodies [ 74 ].

While such concerns have been highlighted across a number of studies and media articles, in a seminal study that involved interviewing REC members, some of the interviewed participants rejected the need for yet further guidelines, instead calling for “implementable procedures to assess big data projects effectively” [ 31 ], 136). As the authors highlight, differences in requests for specific guidance may lead to differing outcomes from different committees, with potential for negative impact on “researchers’ trust in the oversight system, data sharing practices, and research collaborations” [ 31 ], 138). Crucially, a lack of expertise and experience in assessing big data and AI-related projects was also explicitly recognised by the interviewed REC members [ 31 ], findings supported by further European and US research [ 81 , 86 ]. Footnote 4

2.3 Learning for AI research ethics

Despite apparent gaps in REC systems, as the Future of Privacy Forum report ‘Designing an Artificial Intelligence Research Review Committee’ [ 46 ] sets out, in developing models to adequately address AI research, we can learn from the significant work undertaken in human and animal research, and biosafety committees. In similar work proposing developments in RECs, a 2021 collaboration between the UK’s Ada Lovelace Institute, University of Exeter, and Alan Turing Institute, investigated ‘Supporting AI research ethics committees: Exploring solutions to the unique ethical risks that are emerging in association with data science and AI research’ [ 1 ], and the associated ‘Looking before we leap’ project [ 84 ]. Their report [ 2 ] highlighted six challenges for research ethics committees:

lack of resources and training

mismatch in principles designed for researcher-subject relationships applied to researcher-data subject relationships

lack of established norms regarding principles for use specifically in AI and data research

cross-institutional (and sector) research which can lead to research being assessed by multiple committees

challenges of assessing unexpected impacts

transparency with respect to corporate research ethics groups or involvement of corporate entities in research activities

These challenges, and the context described in the preceding sections, led these researchers to recommend some key foci for RECs in considering AI research (which we revisit in Conclusions), synthesised to indicate their strong parallels in Table  1 .

2.3.1 The need for learning in RECs

These sets of concerns and recommendations are intertwined, each contributing- and being contributed to by others in the list. A lynchpin of these recommendations is learning. This focus involves understanding how RECs, researchers, and stakeholders learn about AI, its impacts, and the systems into which it is deployed and the ethical concerns of those systems. Research is required to understand the processes of this learning, how learning about AI, ethical development and thinking, and systems thinking come together. RECs should have continuous training for staff regarding ethical review processes and their importance, with ongoing development. This applies in university contexts, but notably: “Many corporate RECs we spoke with also place an emphasis on continued skills and training, including providing basic ‘ethical training’ for staff of all levels.” ([ 2 ], 37).

In a powerful move highlighting the significance of learning through editorial policy, the Journal of Empirical Research on Human Ethics includes in its manuscript template an Educational Implications section, intended to discuss the ‘key concepts’ from the article to support teaching to different stakeholders, including research and REC communities, as well as students, and external stakeholders such as participants and the general public [ 47 ]. In Ferretti et al.,’s analysis—published in that journal—this ‘Educational Implications’ section notes the significance of: “knowledge exchange and a more productive engagement among the various factors involved in big data research. These include and are not limited to RECs, researchers, research institutions, private enterprises, citizen science groups, and the public” ([ 31 ], 139), highlighting that this responsibility involves developing skills around both the technology (AI), and ethical processes and values. As they also highlight, the range of actors for whom there are implications for learning extends to “informing society about issues related to big data and the use of AI in research. Starting with this democratic engagement, the general public can clarify their expectations regarding research with big data and thus inform the decisions of other actors involved.” ([ 31 ], 140).

2.3.2 Beyond principles

The importance of learning regarding the application of ethical concepts to AI research has been highlighted. However, as noted in the introduction to this article, while a significant body of work has engaged in developing guidelines and principles for ethical AI with an aim to disseminate and educate a variety of audiences, the operationalisation of these principles into organisational structures, practices, and professional reflection, has received less attention [ 50 , 60 , 72 , 89 , 91 ]. As Resseguier et al., put it: “this identified gap in AI ethics finds its root in the very nature of the currently dominant approach to AI ethics, i.e. a view on ethics that considers it as a softer version of the law. [They] point to the need to complement this approach […and…] call for a shift of attention in AI ethics: away from high-level abstract principles to concrete practice, context and social, political, environmental materialities.” ([ 72 ], 3).

Awareness of these principles and guidelines is important, and has positive impact on intention to consider ethical issues, by providing orienting devices for stakeholders to think with. Specifically, [ 22 ] surveyed > 1,000 managers in the US, randomising presentation of different four groupings of AI regulations and asking about ethics in AI and their intent to adopt AI. They found “ that information about AI regulation increases manager perception of the importance of safety, privacy, bias/discrimination, and transparency issues related to AI. However, there is a tradeoff; regulation information reduces manager intent to adopt AI technologies. ” ([ 22 ], 1). Similar reflections were provided by Miller and Coldicutt [ 59 ] who polled UK ‘tech workers’ ( n  = 1010) finding that 81% of those who worked on AI tools ( n  = 155/192), “would like more opportunities to assess the potential impacts” (p.10). Thus, principles can be useful tools insofar as they offer orienting devices to think with. However, learning to engage in ethical practice goes beyond principles in addressing at least four key concerns:

How do we learn to operationalise principles in context : Principles provide useful anchors, but we must learn how to work with them with particular contexts and people, noting that ethical boundaries may change over time and location. As Resseguier et al. put it: “ethics must entail a sharp attention to specific situations and relations, accounting for the different levels of the personal, the interpersonal, the organisational, up to broader social, political, and environmental configurations” ([ 72 ], 10).

How do we learn to navigate tensions between principles: Classic dilemmas include freedom vs equality, or free speech vs privacy, and there is significant literature on this topic.

How do we learn for a substantive ongoing ethics over procedural ethics: There are questions around (1) how we probe why a tool is being implemented, and (2) whether reinforcement of existing systems closes off opportunity for work that develops futures worth wanting? Focussing on ‘doing things ethically’ can lead to abstracted models of action that fail to interrogate underlying aims in, for example, developing particular tools, including how they intersect with existing power relations [ 6 , 72 ]. As work on Data Feminism highlights [ 24 ], current approaches to AI ethics are inadequate to addressing structural entrenched inequality and the material reality of AI development. As [ 48 ] note, a focus on ethics in the technical design of systems misses significant concerns (including in their proposal for an ethical ‘Algorithmic System for Turning the Elderly into High-Nutrient Slurry’).

How do we assess the indirect, long-range, or soft, impacts of our work: Principles used in research ethics have typically focused on risks to participants, and relatively direct and immediate impacts more broadly (sometimes excluding risks, focussing only on possible benefits). These direct impacts may be relatively predictable, perhaps through a hypothesised pattern of causation and modelling of their likelihood of occurrence. However, many technology systems have broader and long-term impacts. These occur in the ways they may reorganise social relations, and re-shape normative assumptions regarding human value and values.

2.3.3 Resources for learning AI ethics for research

Where, then, should we look for resources to support this learning? In their work surveying 54 and interviewing six AI practitioners, Morley et al., highlight that “the AI ethics community is not yet meeting the needs of AI practitioners” ([ 62 ], 6), with more practitioners saying further resources would be useful than those who say that what exists is already adequate, across a range of types (from principles, to design guidelines, and ‘best practice examples’) [ 62 ]. Where lessons are being drawn from other parts of the community, the historical parallels—for example, the sharing of security flaws in software as a defensive practice—may not carry over into AI [ 76 ]. Various resources exist, including worked cases [ 3 , 67 ], and one helpful example of how one might complete a REC form [ 23 ], and emerging reviews of materials such as those in the ‘Responsible AI Pattern Catalogue’ [ 54 ]. Understanding how these resources are being, or could be, mobilised including via the crucial role of RECs is thus important.

Indeed, this is a challenge across fields: understanding how researchers develop and express research ethics, [ 10 ]. Based on their review of papers discussing ethical issues in research, Beauchemin et al., [ 10 ] highlight a dominance of descriptive ethics, with relatively little use of established definitions or reflection, leading them to call for a greater focus in research outputs on articulating the ethical concepts used [ 10 ]. This is particularly salient given RECs may draw directly on literature (or expect applicants to include relevant disciplinary literature) regarding ethical issues. However, if discussion of ethical issues is unusual in academia’s primary mode of communications—research outputs—where should researchers and RECs look in seeking to increase “sensitivity to ethical issues [and consider] how empirical data may be relevant to various ethical principles and problems.” ([ 27 ], 16).

In their specific analysis of AI in mental health initiatives, Gooding and Kariotis highlight that ethical and legal issues tend not to appear in the peer-reviewed literature, even if they may have been considered in the REC process [ 36 ]. Perhaps as importantly, they also flag that most publications in the space report on pilot work, thus obscuring the potential long-range impacts of the research [ 36 ]. Even more concerningly, one analysis of over 227 publications on health technology (from an initial pool of over 14,000 returned) indicated that approximately half made no reference to ethical principles at all [ 79 ]. In a review of software engineering journals, Badampudi et al., [ 8 ] report that roughly half discuss one of consent, confidentiality, or anonymity, but only 6 of 95 reviewed discuss all three [ 8 ].

Here we see how the roles of advisory bodies, formal RECs, publication processes, and the guidelines and principles come together in an ethics ecosystem [ 73 ]. In this ecosystem “individuals (researchers), organisations (research institutions and the various committees within) and external bodies (publishing houses, funding bodies, professional associations and the governance policies they produce)” ([ 73 ], 317) participate in developing understanding and evaluating of ethical behaviour, through their roles in the research process. Footnote 5 Moreover, we see how different components of a system come together to act on ethical thinking, and provide resources for that thinking. Adopting this view, Chi et al., [ 19 ], analysed AI ethics documentation regarding diversity and inclusion, within three large AI infrastructure companies. This expansion of “the range of documents past high-level corporate principles sheds light on how firms translate principles into action and provides greater clarity about the problems and solutions they hope to address through AI ethics work.” [ 19 ]. Through this analysis, they highlight that diversity and inclusion initiatives within these companies is configured to an “engineering logic”, thus while they claim AI ethics expertise, they act as “ethics allocators” pushing decisions regarding impacts of tools downstream to customers [ 19 ].

Importantly for this paper, they highlight a key claim: That on the one hand, the various sorts of documents or material resources organisations produce and draw on are reflections of (or, ‘containers for’) value statements, while (on the other hand) they also shaping this discourse (reflection on) through the resources they provide and the particular kinds of narrative they encourage and recognize as genuinely ethical. In this way “they are a kind of agent, educating clients, the public, and the broader field, articulating and defending values, developing scripts for ethical action that allocate work and responsibility to internal and external actors, and constructing the knowledge and expertise AI ethics work requires.” ([ 19 ], 2).

3.1 The materiality of research ethics

Despite the significant body of work drawing attention to the ethical impacts of AI, alongside corresponding guidelines and principles, relatively little is known regarding the resources drawn on and produced through the workings of actors within the research ethics ecosystem (including researchers, those impacted by the research including participants, and ethics committee members and secretariat).

These diverse components of ethics ecosystems, including the ethics process itself, are forms of knowledge which, as Freeman and Sturdy [ 34 ], Footnote 6 Footnote 7 put it, are inscribed, embodied, and enacted. Inscribed in different kinds of artefacts that encode knowledge, including ethical principles and templates, that are made available for use across contexts. Embodied within individuals who bring this knowledge to bear in their actions, often in implicit ways. And enacted , in the sense that new knowledge emerges from interactions, and is available for use in, particular contexts. An example offered by Freeman and Sturdy is helpful: “ When a committee convenes, embodied and inscribed knowledge is brought into the room in the form of what each of its individual members knows [embodied], whether through education or experience, and in what has been recorded in the minutes of previous meetings and in the documents prescribing the committee’s remit and procedural rules. But the committee’s knowledge is not limited to what is brought into the meeting. In the course of discussion, the committee may generate new knowledge: new ideas and insights, new aims, and new rules for how to fulfil them [enacted] ” ([ 34 ], 12). How the learning transfers beyond the members of the committee is an important question to ask.

Because many resources that inscribe knowledge in an ethics process are used explicitly as objects by multiple agents—researchers, REC members, stakeholders, compliance organisations, to name a few—these resources act as boundary objects [ 4 , 16 , 78 ]. In this way, resources such as formal policies, standardised forms, principles, and learning resources, are materials that inscribe knowledge in order to span across context and actors. Simultaneously, they are interpreted and reinterpreted in context, thus their meaning is not only held in the resource itself, but in the way its knowledge is mobilised and negotiated (or, enacted). Resources such as REC application forms and the materials to which they refer thus provide textual lenses reflecting both stances in their own right, and instruments that shape discourse [ 63 ].

3.2 Mapping research ethics

In Australia, the primary research ethics document—with legal standing in national research governance systems—is the National Statement on Ethical Conduct in Human Research [ 65 ] (henceforth “National Statement” or just “Statement”). While research ethics naturally extends beyond this document, and the document is grounded in histories of practice, culture, and artefacts, here we will treat it as the first order ethical document. From this document, we can see second order materials arising through the ethics process, at varying steps removed from the National Statement:

Institutions develop ethics forms, intended to support researchers in instantiating responses to the Statement’s key principles.

Researchers then complete these forms, with reference to the Statement, and other soft (e.g. disciplinary guidance documents) and hard (e.g. privacy legislation) policy.

Completed forms are evaluated by RECs, and their evaluations are articulated (using National Statement concepts) with the intent that researchers will respond to them.

Researchers then conduct research, within the scope of their REC approval, and ongoing commitment to ethical practice (which may be further informed by disciplinary and cultural norms).

Journal editors and reviewers, funders, and RECs, will then review submissions at different levels of granularity regarding the completed work, for internal or external reporting/dissemination. These should include reference to the REC process (at minimum reporting that one was completed), and any issues arising.

Therefore, to map the material ethics ecosystem we conducted a review of:

Resources available institutionally, to be drawn on by the REC process.

Where these resources are taken up in research practice, through a systematic search of our internal REC application database, and external publication databases.

And within these materials, an analysis of the REC application detail, supplemented by semi-structured interviews of the respective researchers, and further review of published outputs.

While previous research [ 19 ] has mapped documents from multiple organisations to analyse expressions of values and ethics, we instead focus on a single organisation. In that prior work documents were coded as representing different functions regarding ethics: (1) pedagogic tools; (2) product documentation; (3) legal/policy; (4) general communications. As our focus is on understanding networks of resources linked to specific projects internally, and how this analysis can help us understand the socio-material context of the work reflected, we develop an approach informed by Chi et al. [ 19 ]. Specifically, our analysis maps out the following materials:

Pedagogical tools—specifically guidelines, courses, and scholarly outputs such as reviews of ethics strategies, of participant preferences, etc.

Process resources—these include materials such as ethics proformas in document or web-form format, for example focussing on data protection, and REC application details

Legal and policy instruments—these include statements of principles, the Australian National Statement on Research Ethics [ 65 ], and legal instruments such as relevant privacy legislation

General communications—these include any available communications from the institution referring to relevant issues, made available through general (rather than ethics targeting) channels

Discursive resources including REC consultation, and stakeholder consultation (or other forms of input, such as codesign)

Reflection on practice, including any expression regarding previous experience (e.g. provided in REC applications), or experiences of relevance within the project (e.g. in publications, or public reflections).

As described above, analysis of these material resources frames these resources as providing an expression of, or lens onto, the conceptual space that shapes and is shaped by ethical discourse.

3.3 Interviews

Interviews were conducted based on invitations to researchers from a higher educational institution who had been identified as submitting relevant applications in our search process (described below).

A semi-structured interview schedule was developed, to understand perspectives of the researcher stakeholders regarding their use (or otherwise) of ethical frameworks in their research on data and Artificial Intelligence (AI). Participants were invited to speak about their organisational contexts—which, for some, crossed university and industry settings—and any practical challenges in use of AI and advanced technologies and approaches to address these ethically. Interview questions (Table  2 ) were developed to probe the dimensions described above, regarding:

Developing approaches to ethical concepts and principles

Learning to navigate tensions and challenges

Procedural and substantive ethics: Process (and adequacy) of REC in mediation

Challenges in AI research and soft impacts

The questions were designed to leave open the discussion of principles used and any ways these were identified and navigated by participants, and to allow for discussion of the range of pedagogic, discursive, reflective, legal, and other resources used alongside the formal REC process and any others followed.

Interviews were scheduled for 30–60 min duration, conducted via online video conferencing. They were conducted following a consent process in which we requested access to key REC materials related to projects of relevance (described below), these thus act as an anchor for the interviews, acting as a preliminary stimulus and material artefact. We also provided reference to other principles in advance via the introduction to the interview, including the National Statement, Australia’s Artificial Intelligence Ethics Framework [ 7 ], and the Human Rights and Technology Issues Paper: UTS Submission [ 85 ]. As a semi-structured protocol, not all questions were asked of all participants, although all themes were introduced in all interviews. The initial questions often naturally led to further discussion of ethical issues and the role of the REC, and the interview protocol served as a guide to steer these conversations (even where the questions were not explicitly used).

The interviews were conducted by a single researcher, who also implemented the first analysis of the interview and REC material data. The interviews were professionally transcribed, and these transcriptions were selectively coded alongside other research texts (submitted REC applications and files) drawing on approaches to discourse and document analysis [ 14 , 71 ].

In reporting, the transcription convention used is that […] indicates words were removed (where these are not relevant to the key issue), and [unclear] indicates words that were inaudible or unclear. A non-verbatim transcription is used, with non-linguistic features (gesture, and fillers such as um, er, etc.) not transcribed.

The work was internally funded through a faculty seed grant. REC material may fall under the intellectual property of the institution or be considered internal material for the purposes of evaluation and quality improvement. However, because of the research intent of the work, and the inclusion of semi-structured interviews, a REC application was submitted (ETH216658) and data sharing agreement put in place, building on an earlier application (ETH205567) regarding use of ethical frameworks based on responses to a public consultation on AI ethics. This updated application provided approval for:

a search to be conducted on the REC database for keywords across titles and summaries, with results provided to the authors;

the authors screening these as described above;

the authors contacting lead researchers on relevant projects, to seek their consent to access their full REC materials, and invite them to interview (these were treated as separate consents);

the authors liaising with the REC secretariat to provide consents (where given) for sharing the REC material for the stated purposes; and

using the REC materials to inform the interview discussions, where those occurred.

Separately, we also sought references to REC approval in published works (as above). The reporting here is not intended to identify specific authors or their work, and we have sought in our aggregation and excerpts of interviews and other material to maintain confidence and reduce risk of re-identification.

The reporting here is also not an evaluative reflection of any work noted, at an institutional or individual level. Our analysis is limited to the data available to us, selected through a particular search strategy at a single institution. We have no reason to suppose that this data is particularly unusual, but nor do we make claims about generalisability either at our institution or more broadly. Rather, our interest is in how the process of conducting such analysis may inform understanding of ethics processes, and how our specific study may provide broader insights.

4 Data—instantiations of ai ethics resources in use

4.1 mapping ethics resources.

In our first step, we sought to map the institutional ethics ecosystem, using the model described above, and drawing on the visual representation in Chi et al., (see, [ 19 ], 4). That foundational work analysed multiple technology companies and their expression of ethics and values with respect to diversity and inclusion. A helpful step in their representation was to (1) colour code documents according to department or product space within the organisations, and (2) draw connections to explicitly highlight how documents referred to each other. Neither is appropriate in our case. That is because (1) the documents we are drawing on are all within the research governance space, with the exception of “general communications”, and (2) the documents are highly interconnected in their present form (again, with the exception of general communications). Figure  1 below indicates the set of resources returned through searches of both internal and external sites. In addition to these resources many other materials may be drawn on by individuals, groups to which we do not have access, and from external sources. Our intent here is not to suggest this resource set is exhaustive either of the set of resources within the institutional ecosystem, or—clearly—of the set of relevant resources in the wider ethics ecosystem.

figure 1

Mapping the institutional ethics ecosystem

4.2 Search strategy and output

A term-based search was conducted on all REC applications, using the centralised system through which all such applications are submitted. This system allows for searching over the text-field submissions, which comprise most of the application, barring attachments which typically consist of items such as: consent forms; participant information sheets; budgets; organisational approval letters; data collection materials of various sorts, such as survey instruments and interview protocols; elaborated answers to text fields, such as rationales for particular approaches, study design diagrams, etc. At the point of the initial search, the RECs received 6–700 applications per year across the full REC panels and faculty level delegation.

The initial search was conducted in October 2021, for applications dating from 2015 (when the system was launched). A follow-up search was conducted in September 2022. Applications on which any of the co-authors were an investigator, or involved in the research in a non-investigator role (e.g. advisor, participant, student-of), were excluded. In some cases, no researcher was still at the institution, and these applications were excluded. Some researchers had multiple studies identified, in one case two submissions were discussed in interview; in others, the researchers either declined or did not reply to an earlier invitation, and thus any later applications were also excluded. Results of this search and screening are summarised in Fig.  2 .

figure 2

Search strategy for AI Studies via REC

4.3 Research outputs

To complement our search of REC applications, we conducted a bibliographic search of the Web of Science (WoS) core collection (Fig.  3 ), which provides comparable coverage to Scopus as an indexed article collection [ 12 , 77 ]. This approach was intended to (1) act as a check on further applications that may have been missed in the internal-system search; and (2) provide further insight regarding the expression of ethics by researchers, through analysis of reflections of ethics in their published works. Footnote 8

figure 3

Search strategy for AI Studies via publications

We also conducted a search for obtained REC numbers (e.g. searching for “REC-15000”) in Google Scholar, to supplement the materials in the REC process, though this did not identify any further material.

Finally, we also conducted preliminary searches of the institutional repositories (an Open Access self-hosted repository, and via the Dimensions database, with which we have an institutional arrangement), using a full-text search for the same terms. These searches were not systematically reviewed due to significant overlap with the WoS search which yielded data saturation.

5 Results and analysis of ethics materials and interviews

The materials retrieved were analysed and drawn upon to identify and invite interviewees. From the n = 11 applications shared, the set of resources drawn on explicitly within the application, or via the interview data, were mapped using the framework in 1. As indicated in Fig.  4 there is significant overlap between the resources available in the ethics ecosystem (Fig.  1 ), and those drawn on ( Fig.  4 ) in practice, notably:

The National Statement featured as a central principles document

The REC process itself was explicitly noted as drawn on in ethical consideration

The Australian Privacy Principles (APPs) and generic ‘university policy’ provided some policy context

Discursive resource via colleagues (peers, supervisors or other senior colleagues), and other stakeholders were mentioned as a key resource

figure 4

Mapping Aspects of the institutional ethics ecosystem drawn on in practice. *The interviews of course provide a clear indication of reflection on practice. Here we are specifically interested in examples of resources that are designed to promote reflection, or/and instances where materials (including the interview data) refer explicitly to a prior occurrence of reflection, such as learning from previous experience on a similar project

However, as our interview data indicates, the depth of use of these resources is unclear in places. The pedagogical tools and general communications referred to were targeted at the specifics of the projects, and thus differed significantly from those available via the institutional ecosystem. However, although some resources in this internal ecosystem were relevant to AI, with the AI ethics principles being clearly highly relevant, the former were not drawn upon at all, and the latter were only mentioned once.

Table 3 sets out key responses from the pool of interviewees, mapped against the four key concerns in learning to engage in ethical practice (see p.8). The five researchers interviewed are identified (R1-5), and the topics of their research projects were:

Transcript 1: Understanding (through self-report methods) organisational practices for data projects, using both qualitative and quantitative methodologies (such as path analysis).

Transcript 2: Interviewing developers of an AI system to understand how their design practice avoided bias.

Transcript 3: Developing and deploying a system at a field site, including secondary analysis of data captured on site (with removal of any data that could de-identify people on site, prior to receipt by the researchers).

Transcript 4: Effective delivery of data science initiatives in a specific sector.

Transcript 5: How organisations manage and use their AI technologies.

Interviewees 3 and 4 were building AI tools via their research (others may have been in other capacities). This may suggest that in the process of REC submission, while information regarding methods is elicited, this elicitation does not capture the range of relevant approaches adopted.

Developing approaches to ethical concepts and principles : The participants were invited to consider nationally relevant ethics principles, alongside which they noted national privacy principles, and the European General Data Protection Regulation (GDPR) in passing. Participants referred to self-reflection in contrasting ways, with regard to a trigger for seeking out an ethics framework (R3), and the idea that “My ethical framework is myself, and that’s good enough, I think.” (R1).

Learning to navigate tensions and challenges: Participants referred to challenges in operationalisation of principles not only into practice but into other material forms, for example saying “so this is what the documents say, and how are we going to transfer it into our ethics applications” (R3). This went alongside a sense that outside of the university context, ethics is not a consideration in research and development, with one researcher (R3) who contacted external researchers reporting that “they don’t have ethics or they don’t really care about the ethics around this.” (R3).

In discussing the published outputs of their research, R3 notes that a core concern of their methodology was to ensure that the site of their research could not be re-identified from images contained in these outputs. For instance, R3 described their response to a person who, at a conference presentation, asked about their collection process and ethics: “ I told them, if you want more details, this is the ethics number. […] So, you can contact us. Because [they were] very interested. [They] wanted to do something similar. And [they were] interested about the ethics and the data collection process around it .” (R3). Another (R2) notes their research was informed by a well-known case of “AI failure”, with part of the work investigating how designers seek to avoid these kinds of biases: “ my idea was, are there processes that we can put in place to prevent that from happening ” (2–1). In both cases, we see how knowledge is inscribed in resources made externally available for shared learning.

Tensions between data quality and ethical considerations were a recurring theme, as were reflections on whether standardised processes could help navigate such tensions. For instance, R3, who required images of a physical space, but not the people in it, noted that “one of the main questions that was raised was do we have the consent of those [people] to be appearing in the video. […] if I had set up the cameras by myself, then I would have [inadvertently] captured the [people] ”. To navigate this challenge, secondary data (alternative images) were provided and filtered to ensure people were not visible, but this meant that the images obtained were not captured from a position the researcher would have chosen. Two researchers (R3 and R4) noted the challenge that high-quality imaging increasingly makes it harder to de-identify subjects by filming from a distance, because by-standers may still be recognisable even if they were not the intended target of analysis. R4 commented: “ Then you say, hang on, I got 25 projects trying to do the same. What can we standardise? What’s the guiding principles? What are the governance frameworks? ”. However, as R1 observed, a challenge for such standardisation, and broader concerns about consent, is that particular research methods used may require bespoke (i.e. not standardised) approaches: “ An interesting experience I made recently is that people don’t understand my analysis, not even academics, and that might make it a bit complicated in terms of, maybe, ethics as well .” (R1).

Procedural and substantive ethics: Process (and adequacy) of REC in mediation : Participants reflected on tensions between procedural and wider ethical considerations, including features of the REC process and requirements around such things as data privacy. R5 observed: “it’s stipulated by the university what you need to do and how you need to keep your data […] So, it’s not really an ethical decision. It’s more like there’s rules to follow. So, I don’t need to make any ethical decision.” Later also noting that “ there’s a difference between following the law and an ethical decision” (R5).

Nevertheless, participants recognised that established REC processes supported ethical reflection by encouraging them to “think about things a bit differently” (R1) and “stop and think a moment” (R2), and even suggested: “I think it would be wise if more organisations would have an AI ethics committee to stop and think before they build the AI because there are so many problems around this area. And many organisations don’t stop and think. They just do, and as a result we have a lot of biased AI and a lot of problems. So, I think the concept of having an AI ethics committee can be very, very valuable and we should actually move that from the university to the more corporate world as well.” (R2).

The importance of fine-grained contextual factors, and not merely relying on generic procedural ethics, was also noted. For example, that consent practices must be adapted to specific contexts, moving beyond basic procedural requirements. R3 notes: “We have to establish that dialogue with them. They’re not into reading consent forms, user agreements. So, we have to do the face to face dialogue and to explain to them. And some of them didn’t even realise what machine learning, AI, deep learning means. For them, it’s like they think we’re doing something robotics when we talk about AI. So, it’s very understanding. Different people have different perceptions. […] So, it goes beyond documented consent forms and user agreements. You have to have these dialogues, verbal communication. I think that’s very, very important in AI research. ”.

Perhaps unsurprisingly, a technical framing of ethical concerns was another theme among our participants’ responses—for instance, seeking to employ technical approaches to explainability or bias to proceduralise ethics—and using terms like “explainable”, “ethical”, and “responsible” interchangeably.

Challenges in AI research and soft impacts : Although the REC ethics process was generally seen as rigorous, and our participants viewed their own research as posing relatively low risks, concurrently they also observed that AI more generally might raise more- and different kinds of issues that the REC process is “not reflective of, how should I say, the ethical implications for artificial intelligence for the whole of society. ” (R1).

Two examples of the relatively-uncontroversial nature of many current uses of AI were that human-in-the-loop systems are often used to mediate AI’s decisions, and that the purpose for which AI is used is often relatively tame. As R5 put it: “not to be dramatic or controversial. So, I guess that’s an ethics thing that they are tapering their AI. They’re not making the extreme ” (R5). At the same time, though, they also recognised broader ethical concerns regarding responsibility to the conduct of science and the public’s trust in science: “ I guess that people feel aggrieved or unfairly dealt with. So, I guess if that feeling swelled, there would be less people who’d want to take part in my research if there was that feeling that it was unsafe, unsecure. And then I wouldn’t be able to conduct my research. Or if it grew wider, then no one would conduct any research sort of thing if there’s such mistrust there. '” (R5).

Participants also commented on issues in AI research around soft impacts and commercialisation, including that the ethical use of data and ethical use of AI raise different issues (R4), and their sense that there is a gap in ethical research and development outside of universities: “ outside, people are doing whatever they want ” (R1), and “ AI is not necessarily localised and AI is borderless, and organisations would need to apply to all these different regulations when building the AI, which doesn’t really help in the process. ” (R3).

6 Discussion

Demands are emerging to put into place governance structures for AI research across sectors, inspired by existing research ethics governance models. In light of the findings of this research, we point to key issues and reflections in Table 4 . As the table indicates, findings are largely consistent with prior work. The researchers were generally positive about the REC process as a means to support their reflection and provide oversight, however noting concerns regarding oversight of cross-sector work and long-range impacts. The implication, then, is that in considering the ethics ecosystem (Fig.  5 ), and how it draws on resources (Fig.  4 ), attention should be paid to how ethics governance and reflection can be inscribed so as to cross-institutional and temporal boundaries, in order to foster ethical reflection and action across all research (and in this context, all research involving AI) (Table 4 ).

figure 5

Elaborated research ethics ecosystem

Grounded in the findings reflected in Table 4 , we propose a broader updated ethics ecosystem (Fig.  5 ) that builds on the governance recommendations reviewed (Table  1 ), Samuel et al.’s [ 73 ] ethics ecosystem model, and the features of it described in Sect. 3.2, highlighting the kinds of resources, and their role in learning, borne out in this research.

7 Conclusion

Rising awareness of AI has prompted increasing demands for its ethical governance and a plethora of ethical AI guidelines. RECs have a well-established history in ethics governance, but there have been concerns about their capacity to adequately govern AI research. However, no study to date has examined the ways that AI-related projects engage with the ethics ecosystem, or its adequacy for this context. This project is based on a single institution, of projects identified via the particular search strategy, and notably only of those that undertook a REC application. These contingencies present limitations, although we have no particular reason to believe that the results are particular to our institution (where AI is a strategic focus). Moreover, the model developed for analysing these applications presents a novel approach to understanding and assessing an ethics ecosystem, a contribution with broad application across both university and industry RECs.

Our results suggest that, despite calls for new structures, existing REC models can effectively support consideration of ethical issues in AI research. REC principles and processes were drawn on and referred to by our participants, and — in the Australian REC context at least—are embedded in a lineage of work on research ethics that is continuing to develop. Thus, where new materials are required, we propose that they should be embedded in this existing well-established ecosystem, rather than creating novel governance mechanisms tailored specifically to AI.

Gaps were identified in the resources drawn on, and by participants in the interviews. Participants expressed uncertainty about some practices, and noted that long-range impacts and issues such as secondary use of data may not be effectively addressed in existing guidance. However, it is not clear these issues are addressed in AI ethics guidelines, and indeed only one participant referred to use of AI ethics principles specifically, with multiple participants raising concerns that outside the research ethics context —a context from which these new guidelines have largely emerged — practices were more varied, and less rigorous.

One upshot of our study’s findings is that the development of new AI principles may not be an optimal strategy for addressing ethical issues related to AI. Indeed, it is far from clear that the proliferation of AI-targeted principles has helped in practice. The results indicate that shared artefacts of practice, such as ethics applications and published articles referencing ethics, provide one lens (socio-material) into the practical usage of principles in context. These resources may be used to support learning by individual and organisational stakeholders. In tandem, organisations seeking to engage with ethics and AI should look to the well-established structures of RECs to build on this lineage. RECs themselves may develop further and support uptake in new contexts by evaluating how their communities—REC members, researchers, the public, etc.—learn regarding ethical issues, and where within institutional governance structures the kinds of issues specific to emerging technologies are addressed, and updated in an ongoing way.

Data availability

Due to the nature of the research, and the legal and ethical restrictions on sharing of internal materials, supporting data is not available.

In this work we will use the term ‘AI’ in a broad sense to refer to techniques that include both symbolic reasoning (e.g. expert systems) and statistical reasoning (I.e. the wide range of techniques often collectively referred to as “machine learning” (ML), as well as hybrid techniques that employ both en ensemble of statistical and symbolic reasoning techniques, targeting tasks that would otherwise require human intelligence, following the early Dartmouth workshop definition of AI [ 57 ].

We limit discussion here to human research ethics here, although similar systems exist in the context of the ethics of research involving animals.

The nature of ‘human subjects’ and personal data is contested in the context of big data research, which often draws on publicly available datasets [ 58 ]. For this reason, alternatives to consent have been explored (e.g. [ 69 ]. Indeed, disagreements and perceptions of varying practices across researchers, and across academic-industry located research, exist across the Belmont principles with respect to use of online data in computer science [ 87 ].

Similar findings were reported in these two further projects. The large EU SIENNA project which surveyed REC members regarding specific technologies including AI and Robotics, with no consistent resources used, some respondents indicating existing guidance sufficed, and others seeking further targeted support [ 81 ]. And a survey of US IRB committees with respondents from 63 distinct institutions, which similarly found both mixed responses to what should be required of researchers, and to questions regarding the IRB capability to assess proposals involving data and AI [ 86 ]

The research ethics ecosystem can of course also be connected to other research institution policies, including data and privacy regulation (and committees relating to these), and the broader structures and regulation for responsible AI beyond research contexts and the relevant material resources and their design characteristics [ 54 ].

A similar framing is provided by [ 83 ] in analysis of research ethics.

As an aside regarding the social nature of research. The lead author attended a workshop run by these authors as part of a large EU project just as they entered postgraduate research (12 years ago); the benefits of academic meetings are often slow, and diffuse, a point which is salient in consideration of immediate and long-range impacts and consideration of knowledge infrastructure.

While this approach was intended to augment our internal search, it may underreport on relevant material given that (1) WoS provides an incomplete archive of all scholarly works; and (2) WoS search is based on article metadata (including title abstract and keywords), and not full text. However, in contrast to more complete indexes such as Google Scholar [ 56 ] WoS provides more advanced search functionality, including full Boolean search and search over metadata fields. This is particularly significant when searching for terms such as “REC” or “Research Ethics Committee” where their discussion may be incidental. A limitation of this approach is that it requires ‘ethics’ to be explicitly mentioned, however in our context this maximises the chances of retrieving publications with a substantive discussion of ethics.

See p.9 discussion which indicates that levels of reporting in publications are low.

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The authors would like to acknowledge the support of the UTS Research Ethics secretariat, in particular Racheal Laugery, for their assistance in this project. Our thanks to the researchers who generously shared their materials and time with us in interviews for their contribution. Mark Israel (Australasian Human Research Ethics Consultancy Services, AHRECS), provided helpful input on a number of issues regarding RECs particularly in international comparison. Our thanks too to Linda Przhedetsky for her research assistance.

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Reproductive rights in America

Research at the heart of a federal case against the abortion pill has been retracted.

Selena Simmons-Duffin

Selena Simmons-Duffin

workplace ethics research paper

The Supreme Court will hear the case against the abortion pill mifepristone on March 26. It's part of a two-drug regimen with misoprostol for abortions in the first 10 weeks of pregnancy. Anna Moneymaker/Getty Images hide caption

The Supreme Court will hear the case against the abortion pill mifepristone on March 26. It's part of a two-drug regimen with misoprostol for abortions in the first 10 weeks of pregnancy.

A scientific paper that raised concerns about the safety of the abortion pill mifepristone was retracted by its publisher this week. The study was cited three times by a federal judge who ruled against mifepristone last spring. That case, which could limit access to mifepristone throughout the country, will soon be heard in the Supreme Court.

The now retracted study used Medicaid claims data to track E.R. visits by patients in the month after having an abortion. The study found a much higher rate of complications than similar studies that have examined abortion safety.

Sage, the publisher of the journal, retracted the study on Monday along with two other papers, explaining in a statement that "expert reviewers found that the studies demonstrate a lack of scientific rigor that invalidates or renders unreliable the authors' conclusions."

It also noted that most of the authors on the paper worked for the Charlotte Lozier Institute, the research arm of anti-abortion lobbying group Susan B. Anthony Pro-Life America, and that one of the original peer reviewers had also worked for the Lozier Institute.

The Sage journal, Health Services Research and Managerial Epidemiology , published all three research articles, which are still available online along with the retraction notice. In an email to NPR, a spokesperson for Sage wrote that the process leading to the retractions "was thorough, fair, and careful."

The lead author on the paper, James Studnicki, fiercely defends his work. "Sage is targeting us because we have been successful for a long period of time," he says on a video posted online this week . He asserts that the retraction has "nothing to do with real science and has everything to do with a political assassination of science."

He says that because the study's findings have been cited in legal cases like the one challenging the abortion pill, "we have become visible – people are quoting us. And for that reason, we are dangerous, and for that reason, they want to cancel our work," Studnicki says in the video.

In an email to NPR, a spokesperson for the Charlotte Lozier Institute said that they "will be taking appropriate legal action."

Role in abortion pill legal case

Anti-abortion rights groups, including a group of doctors, sued the federal Food and Drug Administration in 2022 over the approval of mifepristone, which is part of a two-drug regimen used in most medication abortions. The pill has been on the market for over 20 years, and is used in more than half abortions nationally. The FDA stands by its research that finds adverse events from mifepristone are extremely rare.

Judge Matthew Kacsmaryk, the district court judge who initially ruled on the case, pointed to the now-retracted study to support the idea that the anti-abortion rights physicians suing the FDA had the right to do so. "The associations' members have standing because they allege adverse events from chemical abortion drugs can overwhelm the medical system and place 'enormous pressure and stress' on doctors during emergencies and complications," he wrote in his decision, citing Studnicki. He ruled that mifepristone should be pulled from the market nationwide, although his decision never took effect.

workplace ethics research paper

Matthew Kacsmaryk at his confirmation hearing for the federal bench in 2017. AP hide caption

Matthew Kacsmaryk at his confirmation hearing for the federal bench in 2017.

Kacsmaryk is a Trump appointee who was a vocal abortion opponent before becoming a federal judge.

"I don't think he would view the retraction as delegitimizing the research," says Mary Ziegler , a law professor and expert on the legal history of abortion at U.C. Davis. "There's been so much polarization about what the reality of abortion is on the right that I'm not sure how much a retraction would affect his reasoning."

Ziegler also doubts the retractions will alter much in the Supreme Court case, given its conservative majority. "We've already seen, when it comes to abortion, that the court has a propensity to look at the views of experts that support the results it wants," she says. The decision that overturned Roe v. Wade is an example, she says. "The majority [opinion] relied pretty much exclusively on scholars with some ties to pro-life activism and didn't really cite anybody else even or really even acknowledge that there was a majority scholarly position or even that there was meaningful disagreement on the subject."

In the mifepristone case, "there's a lot of supposition and speculation" in the argument about who has standing to sue, she explains. "There's a probability that people will take mifepristone and then there's a probability that they'll get complications and then there's a probability that they'll get treatment in the E.R. and then there's a probability that they'll encounter physicians with certain objections to mifepristone. So the question is, if this [retraction] knocks out one leg of the stool, does that somehow affect how the court is going to view standing? I imagine not."

It's impossible to know who will win the Supreme Court case, but Ziegler thinks that this retraction probably won't sway the outcome either way. "If the court is skeptical of standing because of all these aforementioned weaknesses, this is just more fuel to that fire," she says. "It's not as if this were an airtight case for standing and this was a potentially game-changing development."

Oral arguments for the case, Alliance for Hippocratic Medicine v. FDA , are scheduled for March 26 at the Supreme Court. A decision is expected by summer. Mifepristone remains available while the legal process continues.

  • Abortion policy
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