2.3k citations · 2.4k across the 8 of their papers we have counts for
3 papers · 1 filter
Allocation Multiplicity: Evaluating the Promises of the Rashomon Set
Shomik Jain, Margaret Wang, Kathleen Creel +1
The Rashomon set of equally-good models promises less discriminatory algorithms, reduced outcome homogenization, and fairer decisions through model ensembles or reconciliation. How…
Scarce Resource Allocations That Rely On Machine Learning Should Be Randomized
Shomik Jain, Kathleen Creel, Ashia Wilson
Contrary to traditional deterministic notions of algorithmic fairness, this paper argues that fairly allocating scarce resources using machine learning often requires randomness. W…
Algorithmic Pluralism: A Structural Approach To Equal Opportunity
Shomik Jain, Vinith Suriyakumar, Kathleen Creel +1
We present a structural approach toward achieving equal opportunity in systems of algorithmic decision-making called algorithmic pluralism. Algorithmic pluralism describes a state…