The minitrack addresses topics related to imposing fairness requirements and conditions in algorithmic decision making. With the introduction of regulations such as GDPR and California algorithms used for autom
Fairness is one of the most prominent values in the Ethics and Artificial Intelligence debate and, specifically, in the discussion on algorithmic decision-making. However, while the need for fairness in ADM is widely acknowledged, the very concept of fairness has not been sufficiently explored so ...
decision-making is a form of exercising power. Thus, the discussion of what constitutes substantive fair decision-making procedures indicates a considerable overlap with theories of relational justice, a perspective new to algorithmic fairness (Wegner et al.,2024). In short...
Algorithmic decision making and the cost of fairness Proceedings of the 23rd ACM SIGKDD international conference on knowledge discovery and data mining, Association for Computing Machinery, New York, NY, USA (2017), pp. 797-806 CrossrefView in ScopusGoogle Scholar Current et al., 2022 Current ...
In Int. Conf. Machine Learning 60–69 (PMLR, 2018). Corbett-Davies, S., Pierson, E., Feller, A., Goel, S. & Huq, A. Algorithmic decision making and the cost of fairness. In Proc. 23rd ACM SIGKDD Int. Conf. Knowledge Discovery and Data Mining 797–806 (2017). Pleiss, G., ...
AI fairness aims to address and mitigate health disparities exacerbated by algorithmic decisions, promoting equitable healthcare delivery. However, the complex nature of clinical settings poses unique challenges, such as uncertainty in using non-clinical variables, addressing biases in clinical variables, ...
Therefore, we need to situate the psychology of how humans perceive fair ness into the realm of algorithmic decision-making. Such an effort requires an integrative approach to better understand how we can examine AI fairness, what its meaning is, its impact, and ultimately its position in ...
and algorithmic decision-making—are increasingly critical. While extant research has focused mainly on P2P contexts, you will focus mainly on platforms and ecosystems with a strong B2B component. Using experimental and qualitative methodologies, this research will uncover strategies for fostering fairness...
Researchers or policymakers pre-define fairness definitions, imposing a one-size-fits-all notion of fairness on algorithmic decision-making. However, differ- ent individuals and communities may have different per- spectives, values, and priorities regarding fairness. Allow- ing users to customize ...
Recent studies have shown that algorithmic decision-making may be inherently prone to unfairness, even when there is no intention for it. This paper presents an overview of the main concepts of identifying, measuring and improving algorithmic fairness when using AI algorithms. The paper begins by ...