Algorithmic Fairness Across Alignment Procedures and Agentic Systems

Zeyu Tang, Prakhar Ganesh, Awa Dieng, Miriam Rateike, Jamelle Watson-Daniels, Golnoosh Farnadi, Jessica Schrouff, Sanmi Koyejo

Keywords: Algorithmic Fairness, AI Alignment, Agentic AI, Large Language Model, Foundation Model, Societal Impact, AI Ethics

TL;DR: As AI evolves into autonomous, decision-making agents, traditional fairness frameworks fall short, and our AFAA workshop aims to address these emerging fairness challenges in this pivotal moment.

Abstract: AI has transitioned from predictive models to interactive, autonomous agents capable of reasoning, planning, and executing complex goals. As the systems increasingly influence social, economic, and scientific decisions, they determine whose interests are represented and whose opportunities are constrained. Ensuring fairness, therefore, is no longer an ethical preference but a practical imperative. As the fairness challenges are fundamentally transformed by advanced AI systems, traditional algorithmic fairness frameworks developed primarily for prediction and/or prediction-based decision-making no longer suffice. This workshop, _Algorithmic Fairness Across Alignment Procedures and Agentic Systems_ (AFAA), emerges at this pivotal moment as a timely forum for rethinking fairness in AI alignment processes and agentic system development. By examining fairness across alignment procedures and agentic systems, this workshop creates a crucial platform for bridging the gap between rapid technical advances in model capabilities and the equally important advances needed in frameworks of algorithmic fairness to govern these powerful systems.

Submission Number: 72