Research project

Investigator: Christine Carter

Abstract:
The nature of work and status of workers has fundamentally changed over the past years in response to the rapid proliferation and introduction of Artificial Intelligence (AI) and Machine Learning (ML) technologies in the modern workplace. Many of the most notable changes can be seen in the automation of decision-making processes from humans to machines in matters concerning the organization and management of the workforce, specifically in the context of recruitment and retention decisions, as well as in general performance and target-related reviews of the workforce.

Against this increased technological presence in the workplace, concerns have arisen as to the adequacy and suitability of labor protection laws against the potential harms arising from the industrial use of AI and ML in automated decision-making processes; particularly in relation to possible issues of algorithmic bias or discrimination; the maintenance of accountability and transparency in the decision-making process; and in the assurance of fairness and equity in the substantive outcome of the decisions reached by automated processes.

This research paper will investigate these concerns regarding the automation of the decision-making processes in the workplace and analyze how the law responds to these concerns and regulates the use of AI and ML. The research paper will focus on anti-discrimination and equality laws, data protection and privacy laws, as well as on the piecemeal legislative implementation of targeted AI regulations, as sources of law that are relevant to the protection of the workforce and regulation of the workplace. The aim of the research paper is to understand the legal significance of these technological advancements for the organization and management of human labor by determining whether the workforce is provided with adequate and appropriate legal protections and redress where AI and ML have been utilized in automated decision making processes.

This research paper will approach this investigation through a comparative analysis of the relevant laws in the United States and Europe to investigate how these jurisdictions have each responded to the emergence of AI and ML, and assess the extent to which their respective regulatory approaches may address the aforementioned concerns raised in the context of automated decision-making processes in the workplace.  The paper will also refer to relevant academic literature and empirical studies where appropriate to identify the good, the bad and the reform-worthy elements of the applicable laws in each jurisdiction to illuminate their respective regulatory potential and success in protecting the workforce and regulating the workplace.