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.
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.
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.
A recent study challenges the common belief that income support programs like SNAP reduce employment, finding that for individuals with a work history, receiving SNAP benefits can actually increase long-term employment.
This paper introduces a method for auditing benefits eligibility screening tools in four steps: 1) generate test households, 2) automatically populate screening questions with household information and retrieve determinations, 3) translate eligibility guidelines into computer code to generate ground truth determinations, and 4) identify conflicting determinations to detect errors.
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.
This research summary presents findings from a randomized controlled trial demonstrating how mRelief’s simplified SNAP application significantly increases application rates among eligible individuals.
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 brief analyzes the current state of federal and state government communication around benefits eligibility rules and policy and how these documents are being tracked and adapted into code by external organizations. This work includes comparisons between coded examples of policy and potential options for standardizing code based on established and emerging data standards, tools, and frameworks.
This study examines public attitudes toward balancing equity and efficiency in algorithmic resource allocation, using online advertising for SNAP enrollment as a case study.
