Breaking the vicious cycle of algorithmic management: A virtue ethics approach to people analytics

Abstract The increasing use of People Analytics to manage people in organizations ushers in an era of algorithmic management. People analytics are said to allow decision-makers to make evidence-based, bias-free, and objective decisions, and expand workers' opportunities for personal and professional growth. Drawing on a virtue ethics approach, we argue that the use of people analytics in organizations can create a vicious cycle of ethical challenges - algorithmic opacity, datafication, and nudging - which limit people's ability to cultivate their virtue and flourish. We propose that organizations can mitigate these challenges and help workers develop their virtue by reframing people analytics as a fallible companion technology, introducing new organizational roles and practices, and adopting alternative technology design principles. We discuss the implications of this approach for organizations and for the design of people analytics, and propose directions for future research.

[1]  Wanda J. Orlikowski,et al.  Technological frames: making sense of information technology in organizations , 1994, TOIS.

[2]  Stella Pachidi,et al.  Organizational intelligence in the digital age: Analytics and the cycle of choice , 2018 .

[3]  C. Sunstein Nudging and Choice Architecture: Ethical Considerations , 2015 .

[4]  When Nudges are Forever: Inertia in the Swedish Premium Pension Plan , 2018 .

[5]  Gregory R. Beabout Management as a Domain-Relative Practice that Requires and Develops Practical Wisdom , 2012, Business Ethics Quarterly.

[6]  Tal Z. Zarsky,et al.  The Trouble with Algorithmic Decisions , 2016 .

[7]  Martin Peterson,et al.  Is there an ethics of algorithms? , 2011, Ethics and Information Technology.

[8]  P. Sackett,et al.  A meta-analysis of gender stereotypes and bias in experimental simulations of employment decision making. , 2015, The Journal of applied psychology.

[9]  Jean Paul Isson,et al.  People analytics in the era of big data , 2016 .

[10]  Luciano Floridi,et al.  The Fourth Revolution: How the infosphere is reshaping human reality , 2014 .

[11]  T. Davenport,et al.  Make better decisions. , 2009, Harvard business review.

[12]  D. Minbaeva,et al.  Building credible human capital analytics for organizational competitive advantage , 2018 .

[13]  Ioanna D. Constantiou,et al.  New games, new rules: big data and the changing context of strategy , 2015, J. Inf. Technol..

[14]  Ben Green,et al.  Algorithmic realism: expanding the boundaries of algorithmic thought , 2020, FAT*.

[15]  Andreas Wendemuth,et al.  Companion technology : a paradigm shift in human-technology interaction , 2017 .

[16]  Frederick L. Oswald,et al.  Statistical Methods for Big Data: A Scenic Tour , 2015 .

[17]  Frank A. Pasquale The Black Box Society: The Secret Algorithms That Control Money and Information , 2015 .

[18]  Shoshana Zuboff,et al.  Big other: surveillance capitalism and the prospects of an information civilization , 2015, J. Inf. Technol..

[19]  Graeme G. Shanks,et al.  Ethical Implications of Big Data Analytics , 2016, ECIS.

[20]  Samuel J. Gershman,et al.  Computational rationality: A converging paradigm for intelligence in brains, minds, and machines , 2015, Science.

[21]  Aristotle,et al.  THE NICOMACHEAN ETHICS , 1990 .

[22]  Stefan Baack Datafication and empowerment: How the open data movement re-articulates notions of democracy, participation, and journalism , 2015 .

[23]  Jorrit van der Togt,et al.  Toward evidence-based HR , 2017 .

[24]  Virginia Dignum,et al.  Responsible Artificial Intelligence: Designing Ai for Human Values , 2017 .

[25]  Mike Ananny,et al.  Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability , 2018, New Media Soc..

[26]  Michael I. Barrett,et al.  Envisioning E-HRM and strategic HR: Taking seriously identity, innovative practice, and service , 2013, J. Strateg. Inf. Syst..

[27]  M. Barrett Challenges of EDI adoption for electronic trading in the London Insurance Market , 1999 .

[28]  Tal Z. Zarsky,et al.  The Algorithm Game , 2018 .

[29]  Engin Bozdag,et al.  Bias in algorithmic filtering and personalization , 2013, Ethics and Information Technology.

[30]  B. Jefferson Predictable Policing: Predictive Crime Mapping and Geographies of Policing and Race , 2018 .

[31]  M. Haas,et al.  Information, Attention, and Decision Making , 2015 .

[32]  David Beer,et al.  The social power of algorithms , 2017, The Social Power of Algorithms.

[33]  Oren Etzioni,et al.  Designing AI systems that obey our laws and values , 2016, Commun. ACM.

[34]  Tina Blegind Jensen,et al.  Collective mindfulness in post-implementation IS adaptation processes , 2016, Inf. Organ..

[35]  Lucas D. Introna,et al.  Privacy in the Information Age: Stakeholders, Interests and Values , 1999, Journal of business ethics : JBE.

[36]  C. M. Bakewell Aristotle On Ethics , 2005 .

[37]  H. Tsoukas The tyranny of light , 1997 .

[38]  Murray L. Wax,et al.  After Virtue: A Study in Moral Theory. , 1981 .

[39]  Michael Stohl,et al.  Managing Opacity: Information Visibility and the Paradox of Transparency in the Digital Age , 2016 .

[40]  R. Atkinson,et al.  A Short History of Ethics. , 1967 .

[41]  Cathy O'Neil,et al.  Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy , 2016, Vikalpa: The Journal for Decision Makers.

[42]  Hamed Haddadi,et al.  Human-Data Interaction , 2016 .

[43]  Sun-ha Hong,et al.  Data’s Intimacy: Machinic Sensibility and the Quantified Self , 2016 .

[44]  K. Weick,et al.  Organizing for high reliability: Processes of collective mindfulness. , 1999 .

[45]  Evgeny Morozov,et al.  Book review: To save everything click here: the folly of technological solutionism , 2013 .

[46]  Fei-Yue Wang A Big-Data Perspective on AI: Newton, Merton, and Analytics Intelligence , 2012, IEEE Intell. Syst..

[47]  Kevin Macnish Unblinking eyes: the ethics of automating surveillance , 2012, Ethics and Information Technology.

[48]  Gerardine DeSanctis,et al.  Capturing the Complexity in Advanced Technology Use: Adaptive Structuration Theory , 1994 .

[49]  Bart W. Schermer,et al.  The limits of privacy in automated profiling and data mining , 2011, Comput. Law Secur. Rev..

[50]  Jenna Burrell,et al.  How the machine ‘thinks’: Understanding opacity in machine learning algorithms , 2016 .

[51]  Mike Ananny,et al.  Toward an Ethics of Algorithms , 2016 .

[52]  W. A. Schiemann,et al.  Putting human capital analytics to work: Predicting and driving business success , 2018 .

[53]  G. Kasper,et al.  The Challenges of Algorithm-Based HR Decision-Making for Personal Integrity , 2019, Journal of Business Ethics.

[54]  D. Sisti,et al.  The Ethics of Behavioral Health Information Technology: Frequent Flyer Icons and Implicit Bias. , 2016, JAMA.

[55]  Gerd Gigerenzer,et al.  Fast and frugal heuristics: The tools of bounded rationality , 2004 .

[56]  R. Hursthouse On Virtue Ethics , 1999 .

[57]  R. Thaler,et al.  Nudge: Improving Decisions About Health, Wealth, and Happiness , 2008 .

[58]  Benjamin N. Waber,et al.  People Analytics: How Social Sensing Technology Will Transform Business and What It Tells Us about the Future of Work , 2013 .

[59]  Omer Tene,et al.  Taming the Golem: Challenges of Ethical Algorithmic Decision Making , 2017 .

[60]  Mark A. Huselid The science and practice of workforce analytics: Introduction to the HRM special issue , 2018 .

[61]  H. Simon,et al.  Administrative Behavior: A Study of Decision-Making Processes in Administrative Organization. , 1959 .

[62]  Wayne F. Cascio,et al.  Investing in People: Financial Impact of Human Resource Initiatives , 2008 .

[63]  Erik Brynjolfsson,et al.  Big data: the management revolution. , 2012, Harvard business review.

[64]  John W. Boudreau,et al.  An evidence-based review of HR Analytics , 2017 .

[65]  David Beer,et al.  Envisioning the power of data analytics , 2018 .

[66]  Shannon Vallor Technology and the Virtues: A Philosophical Guide to a Future Worth Wanting , 2016 .

[67]  Miriam A. Cherry,et al.  The Law and Policy of People Analytics , 2016 .

[68]  Brian S. Butler,et al.  Reliability, Mindfulness, and Information Systems , 2006, MIS Q..

[69]  A. Zwitter Big Data ethics , 2014, Big Data Soc..

[70]  Tina Blegind Jensen,et al.  People Analytics in the Age of Big Data: An Agenda for IS Research , 2017, ICIS.

[71]  Stella Pachidi,et al.  Working and organizing in the age of the learning algorithm , 2018, Inf. Organ..

[72]  Jens-Erik Mai,et al.  Big data privacy: The datafication of personal information , 2016, Inf. Soc..

[73]  H. Tsoukas Strategy and virtue: Developing strategy-as-practice through virtue ethics , 2018 .

[74]  Bernard Marr Data-Driven HR: How to Use Analytics and Metrics to Drive Performance , 2018 .

[75]  Claudia Pagliari,et al.  People analytics - A scoping review of conceptual boundaries and value propositions , 2018, Int. J. Inf. Manag..

[76]  Mariarosaria Taddeo,et al.  The ethics of algorithms: Mapping the debate , 2016, Big Data Soc..

[77]  Richard Hall,et al.  Lost in translation? An actor-network approach to HRIS implementation , 2013, J. Strateg. Inf. Syst..

[78]  Yogesh pal,et al.  Human Resource Predictive Analytics (HRPA) For HR Management In Organizations , 2016 .