How Much Effort Is Enough? - Fairness in Algorithmic Recourse Through the Lens of Substantive Equality of Opportunity

Explore algorithmic fairness and recourse through a 17-minute conference talk examining substantive equality of opportunity in machine learning systems. Delve into the critical question of determining appropriate effort levels required for individuals to achieve fair outcomes when algorithmic decisions affect their lives. Learn from researchers Andrew Bell, Joao Fonseca, Carlo Abrate, Francesco Bonchi, and Julia Stoyanovich as they present their findings on balancing fairness considerations with practical implementation challenges in algorithmic recourse mechanisms. Understand how substantive equality of opportunity frameworks can guide the development of more equitable algorithmic systems that account for varying individual circumstances and capabilities when providing pathways for positive outcome changes.