Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-27T10:15:25.939Z Has data issue: false hasContentIssue false

Improving conditions or conditional improvements? A modern code, and mode, of I-O ethics

Published online by Cambridge University Press:  09 May 2023

Rachel S. Rauvola*
Affiliation:
Department of Psychology, DePaul University, Chicago, IL, USA
Mounica Reddy
Affiliation:
Department of Psychology, DePaul University, Chicago, IL, USA
*
*Corresponding author. Email: rrauvola@depaul.edu
Rights & Permissions [Opens in a new window]

Abstract

Type
Commentaries
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of the Society for Industrial and Organizational Psychology

The preamble of the American Psychological Association’s (APA) Ethical Principles and Code of Conduct (“the code”) begins with a statement of shared values and aims: “Psychologists are committed to increasing scientific and professional knowledge of behavior and people’s understanding of themselves and others and to the use of such knowledge to improve the condition of individuals, organizations, and society.” To ensure this core vision can be promoted and upheld—in the face of challenges new and old, and particularly within nonclinical domains—we agree with Watts and colleagues (Reference Watts, Lefkowitz, Gonzalez and Nandi2023) that proactively reimagining the code and its applications to industrial-organizational (I-O) psychology is needed. Indeed, we can think of many ethical dilemmas I-O psychologists may face in the near future (if they are not already) that the code has potential to address proactively; we present some notable examples of these in our commentary and calls for expansion of the code in turn.

Importantly, these dilemmas occur in areas of the code that are simultaneously central to our ethical prerogatives as (I-O) psychologists and likely to come into conflict with organizational goals. Given this inherent tension, we conclude with broader thoughts on reframing, reapplying, and reinvigorating our professional commitment to the code to address such aspects of modern work in I-O. Adherence, even to an expanded, supplemented, and more I-O-relevant code, will largely result in reactive and conditional improvements for the populations and communities we serve. Meanwhile, such compliance does nothing to address, and thereby in many ways supports, the fundamental harm and inequity perpetuated by and through work (i.e., as a societal institution) and workplaces. If we wish to truly improve conditions for individuals, organizations, and society alike, I-O must cultivate an altogether new orientation toward the code focused on prevention, promotion, and active resistance.

Three categories of modern dilemmas are immediately apparent in relation to reimagining and committing to a more proactive code in I-O, given their overlap with contemporary issues in technology and data management, health and accessibility, and justice, equity, diversity, and inclusion: ethical use of assessments (e.g., AI in selection); ethical conduct of research and data analysis; and ethical imperatives for fairness, inclusiveness, wellness, and equity in organizations, particularly in light of recent world events (e.g., the COVID-19 pandemic, social justice movements, inflation and economic challenges). Multiple “areas of deficiency” in the code noted by Watts and colleagues directly align with the categories of modern dilemmas that we explore: in particular, the “assessments in organizations,” “research practices,” “professional interactions,” and “proactive ethical behavior” gaps noted in the focal article are areas in which the code currently lacks sufficient guidance to address the modern dilemmas we cover herein. We build from the focal article’s discussion of these gaps and their associated themes (e.g., fairness of testing procedures and outcomes; research falsification, manipulation, and framing; multiple relationships and conflicts of interest; and proactivity) in our commentary, calling for ethical code and mode adjustments in turn.

First, organizations are increasingly incorporating machine learning algorithms, big data, and various technologies such as game-based assessments and social media into selection processes. These technological enhancements are currently outpacing regulatory and ethical guidelines (Tippins et al., Reference Tippins, Oswald and McPhail2021). The critical issue around using these technologies for selection involves transparency. Interpretation of machine learning algorithms driven by large numbers of variables are plagued by a “black box,” where it is difficult to understand exactly how complex algorithms arrive at their predictions. Training and testing datasets should utilize high-quality data, but there is little guidance on the representativeness and collection of such data. Algorithms are then bound by the quality (and bias) incorporated into the data upon which they are trained and tested. Thus, with the regulatory landscape in flux, it becomes even more important to utilize an ethical code to develop assessments. I-O psychologists may find themselves as ethical advisors between data scientists developing machine learning models and managers who want to meet specific hiring targets, neither of whom may be bound to an explicit ethical code. I-O psychologists have a unique responsibility to ensure that the selection process is fair, reliable, and valid, and this should be expanded to include the development of algorithms, the use of predictors, and the quality of data. Category 10 (Assessments) encompasses standards that address confidentiality, use, and interpretation of assessments, but it should be expanded to incorporate ethical development of assessments and selection processes that includes high quality training and testing data, transparency around algorithm use, transparency around predictor use, and rigorous documentation and rationale throughout the development process.

Second, and relatedly, I-O psychologists who conduct research in organizations may not have regulatory oversight (e.g., institutional review board governance, peer review processes, expectations for pre-registration and open science practices) to guide their studies; if present and applicable, regulatory oversight may still be mismatched with organizational research, often ill fitted to certain types, disciplines, and contexts, or only focused on particular elements or stages of the research process while neglecting others (e.g., Bell & Wray-Bliss, Reference Bell, Wray-Bliss, Buchanan and Bryman2009; Buchanan & Bryman, Reference Buchanan, Bryman, Buchanan and Bryman2009; Greenwood, Reference Greenwood2016). This can result in questionable research practices (QRPs) that serve organizational goals but are not ethically sound; unfortunately, QRPs plague academia as well due to various issues in review procedures, publication pressures, training deficiencies, and other forces (Banks et al., Reference Banks, Rogelberg, Woznyj, Landis and Rupp2016). Psychologists, whether in applied or academic roles (a dichotomy we agree with Watts et al. is falsely constructed) may be asked or otherwise motivated to present research in a way that highlights certain results while omitting others. Similarly, they may conduct research on a sample that is not representative of their true population of interest and then be expected to generalize to that population (see discussions in Hinkin & Holtom, Reference Hinkin, Holtom, Buchanan and Bryman2009; Tay et al., Reference Tay, Woo, Hickman, Booth and D’Mello2022). Standard 1.03 (Conflicts Between Ethics and Organizational Demands) provides little guidance on how to resolve these conflicts and ethically ambiguous practices in organizations. In research, Standard 8.10 (Reporting Research Results) addresses fabrication of data and correction of errors specifically, whereas Standard 5.01 (Avoidance of False or Deceptive Statements) addresses falsification and deception in research findings. Both of these latter standards are not robust enough to address the ethically blurry practices prevalently occurring in organizations, as well as the proactive steps all I-O psychologists must take to collect and evaluate data ethically. As the authors suggest, the code should be expanded to acknowledge QRPs and encourage data and methodological transparency. We go further to suggest that open, transparent science practices, and the general conduct of responsible and translational research—including such principles as considering questions of societal relevance and importance, presenting research in accessible fora and manners, judiciously allocating resources toward new data collections and using existing datasets and archival sources whenever possible, and designing study methods and analyses with rigor and representation in mind—are imperative, proactive steps for our code and field to systematize.

Finally, I-O psychologists may also find themselves in ethical dilemmas as workers return to the office post pandemic. The pandemic has posed new challenges for psychologists to practice fairness and inclusion and uphold the Principle of Justice and Standard 3.01 (Unfair Discrimination). For example, when providing flexible work arrangements for individuals, how can I-O psychologists make these arrangements fair and equitable for all when part of the workforce may be hybrid, some fully remote, and others in the office full time? How do I-O psychologists equitably accommodate immunocompromised individuals when there is a return-to-office mandate? How can practitioners ensure that performance reviews or career opportunities are not influenced by a worker’s fully remote work arrangement compared to those of a worker who comes to the office every day? The code could be expanded to take a proactive rather than reactive approach toward justice: Rather than solely exercising reasonable judgement towards justice (Principle D: Justice) or refraining from engaging in unfair discrimination (Standard 3.01), the code should incorporate psychologists actively striving for equity, fairness, and inclusion across training programs, organizations, and groups.

Apart from their specific topical focus, each of these code recommendations directly pertain to the “Proactive Ethical Behavior” gap noted by Watts and colleagues: those areas in which the code could support the anticipation or de-escalation of situations with potential for ethical issues, thereby mitigating their effects or avoid their occurrence entirely. However, even with a more proactively oriented code in hand, I-O psychologists must ultimately adopt and enact these ethics. How can we foster proactive uptake of a modern code?

As a field with expertise in proactivity, it seems only fitting that we consider what we know about proactive behavior emergence and occurrence, and attempt to leverage these principles to avoid ethical dilemmas (and promote ethical actions) in the first place. As we know from the proactivity literature (e.g., Griffin et al., Reference Griffin, Neal and Parker2007; Parker et al., Reference Parker, Bindl and Strauss2010), proactive motivation has been tied to “can do” (i.e., expectancy and efficacy beliefs), “reason to” (i.e., the valence, utility, or value of certain behaviors or outcomes), and “energized to” motivational pathways (i.e., affective drivers of goal envisioning and effort). Moreover, proactive behavior is more likely and important within uncertain contexts, particularly those lacking external direction or regulation (e.g., supervision, governance, formalized or codified roles). As Watts and colleagues discuss, there are gaps in the enforceability of the code for unlicensed psychologists, and enforcement becomes even more challenging within fully applied contexts that lack external oversight.

Absent more robust enforcement mechanisms, then, the code has the potential to provide guidance and vision for proactive forms of ethical behavior, particularly if it is accompanied by discipline-wide efforts to boost efficacy (e.g., standards for extensive graduate training and continuing education in ethics), reduce the perceived costs of proactive ethical behavior (e.g., championing success stories and case studies in the field through professional channels, providing formal and informal social support for those who intervene), and inspire internalized commitment to social justice and change (e.g., through social norm setting, accountability, and professional identity development). We contend this is the path forward for modern I-O ethics: Code adjustments alone cannot prompt new modes of action and responsibility. Instead, profound and radical efforts to renew and reinstitutionalize the ethos of I-O psychology as a discipline with humanist, social justice responsibilities that transcend stakeholder groups will be required to truly move toward ethical proactivity (Lefkowitz, Reference Lefkowitz2008; see also Hage & Kenny, Reference Hage and Kenny2009). Such efforts will ultimately help address some of the perennial issues with code applicability, scope, and updating outlined by Watts and colleagues as well. Although regular revisions and assessments of ethics codes are certainly needed, codes are just “important starting place[s]” (Watts et al., p. 31), necessarily limited documents that cannot wholly, solely, or statically address every potential ethical dilemma facing a field, let alone make the field and its constituents ethical.

The dilemmas we highlight are inherently tied to uncertainty, justice, and proactivity. Indeed, they largely pertain to fundamental conflicts between organizational goals on the one hand (e.g., efficiency, cost effectiveness, productivity) and individual goals on the other hand (e.g., worker health and wellness; equitable, inclusive, and identity-affirming experiences)—exactly the sorts of conflicts with the potential for prevention or intervention through prediction and early identification. Conflicts between individual and organizational goals also occur against a backdrop of competing societal systems, some which resist change and reinforce existing structures and norms (i.e., seeking to maintain the status quo) and others which aim to destabilize and replace current systems. These are not only just the sorts of pressures and forces that we as I-O psychologists are trained to expect and plan for when facilitating organizational change. They are also the oppressive systems that I-O has begun to take a concrete stance on (e.g., recommendations to become anti-racist, Bergman, Reference Bergman2019; confront ableism, Wax, Reference Wax2014; adopt intersectional feminism, Rabelo & Cortina, Reference Rabelo, Cortina, Roberts, Curtin, Duncan and Cortina2016) in light of world events and heightened awareness of the role work and employment play in perpetuating inequity and inequality (e.g., Andrea et al., Reference Andrea, Eisenberg-Guyot, Oddo, Peckham, Jacoby and Hajat2022; van Dijk et al., Reference van Dijk, Kooij, Karanika-Murray, De Vos and Meyer2020). Clearly, we have cause to reimagine our ethical code as well as the resources and values needed to adopt a modernized ethical mode in I-O. With these, we can we proactively use knowledge to improve conditions for all and do so with confidence and clarity of purpose in the face of individual, organizational, or societal opposition.

References

Andrea, S. B., Eisenberg-Guyot, J., Oddo, V. M., Peckham, T., Jacoby, D., & Hajat, A. (2022). Beyond hours worked and dollars earned: multidimensional EQ, retirement trajectories and health in later life. Work, Aging and Retirement, 8, 5173. doi: 10.1093/workar/waab012 CrossRefGoogle ScholarPubMed
Banks, G. C., Rogelberg, S. G., Woznyj, H. M., Landis, R. S., & Rupp, D. E. (2016). Evidence on questionable research practices: the good, the bad, and the ugly. Journal of Business and Psychology, 31, 323338. doi: 10.1007/s10869-016-9456-7 CrossRefGoogle Scholar
Bell, E., & Wray-Bliss, E. (2009). Research ethics: Regulations and responsibilities. In Buchanan, D. & Bryman, A. (Eds.), The SAGE handbook of organizational research methods (pp. 7892). SAGE.Google Scholar
Bergman, M. E. (2019). Civility, anti-racism, and inclusion. Industrial and Organizational Psychology: Perspectives on Science and Practice, 12, 412418. doi: 10.1017/iop.2019.80 CrossRefGoogle Scholar
Buchanan, D. A., & Bryman, A. (2009). The organizational research context: Properties and implications. In Buchanan, D. & Bryman, A. (Eds.), The SAGE handbook of organizational research methods (pp. 118). SAGE.Google Scholar
Greenwood, M. (2016). Approving or improving research ethics in management journals. Journal of Business Ethics, 137, 507520. doi: 10.1007/s10551-015-2564-x CrossRefGoogle Scholar
Griffin, M. A., Neal, A., & Parker, S. K. (2007). A new model of work role performance: positive behavior in uncertain and interdependent contexts. Academy of Management Journal, 50, 327347. doi: 10.5465/amj.2007.24634438 CrossRefGoogle Scholar
Hage, S. M., & Kenny, M. E. (2009). Promoting a social justice approach to prevention: future directions for training, practice, and research. Journal of Primary Prevention, 30, 7587. doi: 10.1007/s10935-008-0165-5 CrossRefGoogle ScholarPubMed
Hinkin, T. R., & Holtom, B. C. (2009). Response rates and sample representativeness: Identifying contextual response drivers. In Buchanan, D. & Bryman, A. (Eds.), The SAGE handbook of organizational research methods (pp. 451464). SAGE.Google Scholar
Lefkowitz, J. (2008). To prosper, organizational psychology should…expand the values of organizational psychology to match the quality of its ethics. Journal of Organizational Behavior, 29, 439453. doi: 10.1002/job.527 CrossRefGoogle Scholar
Parker, S. K., Bindl, U. K., & Strauss, K. (2010). Making things happen: a model of proactive motivation. Journal of Management, 36, 827856. doi: 10.1177/0149206310363732 CrossRefGoogle Scholar
Rabelo, V. C., & Cortina, L. M. (2016). Intersectionality: Infusing IO psychology with feminist thought. In Roberts, T.-A., Curtin, N., Duncan, L. E., & Cortina, L. M. (Eds.), Feminist perspectives on building a better psychological science of gender (pp. 179197). Springer. https://doi.org/10.1007/978-3-319-32141-7_11 CrossRefGoogle Scholar
Tay, L., Woo, S. E., Hickman, L., Booth, B. M., & D’Mello, S. (2022). A conceptual framework for investigating and mitigating machine-learning measurement bias (MLMB) in psychological assessment. Advances in Methods and Practices in Psychological Science, 5. doi: 10.1177/25152459211061337 CrossRefGoogle Scholar
Tippins, N. T., Oswald, F. L., & McPhail, S. M. (2021). Scientific, legal, and ethical concerns about AI-based personnel selection tools: a call to action. Personnel Assessment and Decisions, 7, 1. doi: 10.25035/pad.2021.02.001 CrossRefGoogle Scholar
van Dijk, H., Kooij, D., Karanika-Murray, M., De Vos, A., & Meyer, B. (2020). Meritocracy a myth? A multilevel perspective of how social inequality accumulates through work. Organizational Psychology Review, 10, 240269. doi: 10.1177/2041386620930063 CrossRefGoogle Scholar
Watts, L. L., Lefkowitz, J., Gonzalez, M. F., & Nandi, S. (2023). How relevant is the APA ethics code to industrial-organizational psychology? Applicability, deficiencies, and recommendations. Industrial and Organizational Psychology: Perspectives on Science and Practice, 16(3).Google Scholar
Wax, A. (2014). Putting the “ability” back into “disability.” Industrial and Organizational Psychology: Perspectives on Science and Practice, 7, 253255. doi: 10.1111/iops.12143 CrossRefGoogle Scholar