Under Construction: How Organisational Stakeholders Socially Produce Algorithmic Fairness

Algorithmic decision-making (ADM) systems are increasingly used in Human Resource (HR) processes, such as recruitment or performance assessments. They help to increase efficiency, for example by reducing the time to screen CVs. However, in practice ADM systems are associated risks around unfair assessment towards stakeholders like employees and job applicants. Research has focused on defining algorithmic fairness (AF) from different perspectives. Yet, such research often overlooks the stakeholders responsible for the oversight and implementation of algorithmic HR tools, and how their varying perspectives and interactions with algorithmic technology socially construct AF. We conducted 7 initial interviews with different HR professionals, HR consultants and artificial intelligence (AI) consultants to explore the question - what factors are considered in the construction of AF by stakeholders overseeing and implementing ADM systems in the organisational HR context. For this research-in-progress paper, we identified four aspects considered by practitioners that influence their construction of AF in practice.