6 papers
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…
Measurement as Bricolage: Examining How Data Scientists Construct Target Variables for Predictive Modeling Tasks
Luke Guerdan, Devansh Saxena, Stevie Chancellor +2
Data scientists often formulate predictive modeling tasks involving fuzzy, hard-to-define concepts, such as the "authenticity" of student writing or the "healthcare need" of a pati…
Making the Right Thing: Bridging HCI and Responsible AI in Early-Stage AI Concept Selection
Ji-Youn Jung, Devansh Saxena, Minjung Park +4
AI projects often fail due to financial, technical, ethical, or user acceptance challenges -- failures frequently rooted in early-stage decisions. While HCI and Responsible AI (RAI…
AI Mismatches: Identifying Potential Algorithmic Harms Before AI Development
Devansh Saxena, Ji-Youn Jung, Jodi Forlizzi +2
AI systems are often introduced with high expectations, yet many fail to deliver, resulting in unintended harm and missed opportunities for benefit. We frequently observe significa…
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…