5 papers
The Accuracy Trap: Structural Scarcity Amplifies Relative Inequality in Algorithmic Allocation
Erina Seh-Young Moon, Matthew Tamura, Shion Guha
Algorithmic systems increasingly rank individuals for access to scarce public resources, from child welfare interventions to cancer treatment referrals. The prevailing fairness fra…
The Paradox of Prioritization in Public Sector Algorithms
Erina Seh-Young Moon, Shion Guha
Public sector agencies perform the critical task of implementing the redistributive role of the State by acting as the leading provider of critical public services that many rely o…
The Promises and Perils of using LLMs for Effective Public Services
Erina Seh-Young Moon, Matthew Tamura, Angelina Zhai +5
Governments are the primary providers of essential public services and are responsible for delivering them effectively. In high-stakes decision-making domains such as child welfare…
Emerging Practices in Participatory AI Design in Public Sector Innovation
Devansh Saxena, Zoe Kahn, Erina Seh-Young Moon +9
Local and federal agencies are rapidly adopting AI systems to augment or automate critical decisions, efficiently use resources, and improve public service delivery. AI systems are…
The Datafication of Care in Public Homelessness Services
Erina Seh-Young Moon, Devansh Saxena, Dipto Das +1
Homelessness systems in North America adopt coordinated data-driven approaches to efficiently match support services to clients based on their assessed needs and available resource…