33 citations · 52 across the 9 of their papers we have counts for
9 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…
Beyond Predictive Algorithms in Child Welfare
Erina Seh-Young Moon, Devansh Saxena, Tegan Maharaj +1
Caseworkers in the child welfare (CW) sector use predictive decision-making algorithms built on risk assessment (RA) data to guide and support CW decisions. Researchers have highli…
A Human-Centered Review of Algorithms in Homelessness Research
Erina Seh-Young Moon, Shion Guha
Homelessness is a humanitarian challenge affecting an estimated 1.6 billion people worldwide. In the face of rising homeless populations in developed nations and a strain on social…
Rethinking "Risk" in Algorithmic Systems Through A Computational Narrative Analysis of Casenotes in Child-Welfare
Devansh Saxena, Erina Seh-Young Moon, Aryan Chaurasia +2
Risk assessment algorithms are being adopted by public sector agencies to make high-stakes decisions about human lives. Algorithms model "risk" based on individual client character…
Unpacking Invisible Work Practices, Constraints, and Latent Power Relationships in Child Welfare through Casenote Analysis
Devansh Saxena, Erina Seh-Young Moon, Dahlia Shehata +1
Caseworkers are trained to write detailed narratives about families in Child-Welfare (CW) which informs collaborative high-stakes decision-making. Unlike other administrative data,…