Re-Conceptualising Privacy and Discrimination in an Age of Talent Analytics

35 Pages Posted: 5 Sep 2014

See all articles by Mark Burdon

Mark Burdon

The University of Queensland - T.C. Beirne School of Law

Paul Harpur

University of Queensland - T.C. Beirne School of Law

Date Written: 2014

Abstract

Employee recruitment and retention have always been contentious and complex decisions for employers. Historically, hiring was based on social processes of human interaction – a prospective employee traditionally submitted a job application and a manager would decide whether or not to call the person in for an interview. The traditional process is by no means perfect, as exemplified in Michael Lewis’s Moneyball. The subsequent success of the Oakland A’s is often touted as a justification for the use of ‘big data’ in the workplace, or ‘talent analytics’ as it is commonly called. Talent analytics has opened up new employer opportunities which use predictive techniques to improve the accuracy of recruitment and retention decisions. Moneyball encapsulates the start of a journey that is gathering increasing momentum. We are entering an age of predictive recruiting and retention which is challenging and changing the foundations of employee selection, with many potential positive benefits for both employers and employees. However, we contend that negative implications can arise through potential forms of discriminatory action that are very different to traditionally constructed forms of discrimination based on certain attributes, such as age, disability, race or sex. Discrimination in the talent analytics era can still be founded on these attributes but discriminatory decisions can now also be founded on random attributes generated through endless correlations of predictive patterns and segmentations founded on prescriptive actions. In order to find a balance between the benefits and the potential negative impacts of talent analytics, we put forward a new conceptual framework, an info-structural perspective which affords the viewer a different lens to consider these new problems and thus moves discussion away from the confines of first generation anti-discrimination and information privacy laws. We then suggest that new forms of info-structural due process could ameliorate issues of structural discrimination through the greater integration of information privacy law and anti-discrimination law.

Keywords: Information Privacy, Discrimination, Law and Technology

Suggested Citation

Burdon, Mark and Harpur, Paul David, Re-Conceptualising Privacy and Discrimination in an Age of Talent Analytics (2014). University of New South Wales Law Journal, Vol. 37, No. 2, p. 679, 2014; University of Queensland TC Beirne School of Law Research Paper 14-23 . Available at SSRN: https://ssrn.com/abstract=2491346

Mark Burdon (Contact Author)

The University of Queensland - T.C. Beirne School of Law ( email )

The University of Queensland
St Lucia
4072 Brisbane, Queensland 4072
Australia

HOME PAGE: http://law.uq.edu.au/academic-staff/staff.php?nm=markburdon

Paul David Harpur

University of Queensland - T.C. Beirne School of Law ( email )

Brisbane, Queensland 4072
Australia

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