Developing Fairness Rules for Talent Intelligence Management System

Talent management is an important business strategy, but inherently expensive due to the unique, subjective, and developing nature of each talent. Applying artificial intelligence (AI) to analyze large-scale data, talent intelligence management system (TIMS) is intended to address the talent management problems of organizations. While TIMS has greatly improved the efficiency of talent management, especially in the processes of talent selection and matching, high-potential talent discovery and talent turnover prediction, it also brings new challenges. Ethical issues, such as how to maintain fairness when designing and using TIMS, are typical examples. Through the Delphi study in a leading global AI company, this paper proposes eight fairness rules to avoid fairness risks when designing TIMS.

[1]  Staffan Nilsson,et al.  Employability and talent management: challenges for HRD practices , 2012 .

[2]  S. Rynes,et al.  Applicant Attraction Strategies: An Organizational Perspective , 1990 .

[3]  M. Ronald Buckley,et al.  The role of trustworthiness in recruitment and selection: A review and guide for future research , 2013 .

[4]  Huayu Li,et al.  Prospecting the Career Development of Talents: A Survival Analysis Perspective , 2017, KDD.

[5]  Suzanne D. Pawlowski,et al.  The Delphi method as a research tool: an example, design considerations and applications , 2004, Inf. Manag..

[6]  James W. Smither,et al.  APPLICANT REACTIONS TO SELECTION PROCEDURES , 2006 .

[7]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[8]  Blair H. Sheppard,et al.  Toward general principles of managerial fairness , 1987 .

[9]  Hannah R. Rothstein,et al.  The influence of selection test type on applicant reactions to employment testing , 1993 .

[10]  Guda van Noort,et al.  Building brands with interactivity: The role of prior brand usage in the relation between perceived website interactivity and brand responses , 2013 .

[11]  Ronald L. Cohen,et al.  Distributive justice: Theory and research , 1987 .

[12]  J. Thibaut,et al.  Procedural Justice: A Psychological Analysis , 1976 .

[13]  Hui Xiong,et al.  Large-Scale Talent Flow Forecast with Dynamic Latent Factor Model? , 2019, WWW.

[14]  Hui Xiong,et al.  Person-Job Fit , 2018, ACM Trans. Manag. Inf. Syst..

[15]  Debi S. Saini,et al.  Talent management in China and India: A comparison of management perceptions and human resource practices , 2014 .

[16]  Hui Xiong,et al.  Talent Circle Detection in Job Transition Networks , 2016, KDD.

[17]  R. H. Moorman,et al.  JUSTICE AS A MEDIATOR OF THE RELATIONSHIP BETWEEN METHODS OF MONITORING AND ORGANIZATIONAL CITIZENSHIP BEHAVIOR , 1993 .

[18]  M. A. Campion,et al.  APPLICANT REACTIONS TO SELECTION: DEVELOPMENT OF THE SELECTION PROCEDURAL JUSTICE SCALE (SPJS) , 2001 .

[19]  Jerald Greenberg,et al.  Determinants of Perceived Fairness of Performance Evaluations , 1986 .

[20]  J. Stewart Black,et al.  Marketing AI recruitment: The next phase in job application and selection , 2019, Comput. Hum. Behav..

[21]  Jason Bennett Thatcher,et al.  Looking Toward the Future of IT-Business Strategic Alignment through the Past: A Meta-Analysis , 2014, MIS Q..

[22]  Reuben Binns,et al.  What Can Political Philosophy Teach Us about Algorithmic Fairness? , 2018, IEEE Security & Privacy.

[23]  J. Colquitt.  On the dimensionality of organizational justice: a construct validation of a measure. , 2001, The Journal of applied psychology.

[24]  Sumeet Gupta,et al.  Classifying, Measuring, and Predicting Users’ Overall Active Behavior on Social Networking Sites , 2014, J. Manag. Inf. Syst..

[25]  Donald M. Truxillo,et al.  Multiple Dimensions of Procedural Justice: Longitudinal Effects on Selection System Fairness and Test‐Taking Self‐Efficacy , 2001 .

[26]  R. Bies.  Interactional justice : communication criteria of fairness , 1986 .

[27]  G. Leventhal.  What Should Be Done with Equity Theory? New Approaches to the Study of Fairness in Social Relationships. , 1976 .

[28]  Tom R. Tyler,et al.  Beyond Formal Procedures: The Interpersonal Context of Procedural Justice , 2015 .

[29]  Paul R. Sackett,et al.  Fairness in selection: Current developments and perspectives , 1993 .

[30]  David G. Allen,et al.  Meta-Analytic Review of Employee Turnover as a Predictor of Firm Performance , 2013 .

[31]  Rosman Md. Yusoff,et al.  Impact of innovation culture on human resources management practices , 2013 .

[32]  S. Gilliland.  The Perceived Fairness of Selection Systems: An Organizational Justice Perspective , 1993 .