In the article, researchers examines how administrative burdens in waitlist management for subsidized childcare in Massachusetts have led to significant reductions in the number of families awaiting assistance, potentially obscuring the true extent of unmet need.
Errors in administrative processes are costly and burdensome for clients but are understudied. Using U.S. Unemployment Insurance data, this study finds that while automation improves accuracy in simpler programs, it can increase errors in more complex ones.
This article examines the concept of "viral cash" and suggests that the future growth of basic income programs will depend on advocacy networks rather than traditional policy diffusion across jurisdictions.
This resource provides examples and practical guides that explain how to use existing regulations and data sharing agreements to transfer client information or eligibility status between benefit programs.
This article explores how legal documents can be treated like software programs, using methods like software testing and mutation analysis to enhance AI-driven statutory analysis, aiding legal decision-making and error detection.
Through a field scan, this paper identifies emerging best practices as well as methods and tools that are becoming commonplace, and enumerates common barriers to leveraging algorithmic audits as effective accountability mechanisms.
ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT)
The article examines the effects of Arkansas’s Medicaid work requirements, finding substantial coverage losses and no significant increase in employment, compounded by widespread confusion among beneficiaries about the policy.
The article discusses the phenomenon of model multiplicity in machine learning, arguing that developers should be legally obligated to search for less discriminatory algorithms (LDAs) to reduce disparities in algorithmic decision-making.
This article analyses ‘digital distortions’ in Rules as Code, which refer to disconnects between regulation and code that arise from interpretive choices in the encoding process.
