This brief offers a new, anti-racist vision for transforming the Child Care and Development Fund (CCDF) into a program that actively pushes back against structural racism and advances racial equity and economic prosperity for all families.
Sarah Bargal provides an overview of AI, machine learning, and deep learning, illustrating their potential for both positive and negative applications, including authentication, adversarial attacks, deepfakes, generative models, personalization, and ethical concerns.
This brief describes TDI’s efforts to transform federal TANF and employment data into an integrated resource for program management and evidence building.
This report explores technologies that have the potential to significantly affect employment and job quality in the public sector, the factors that drive choices about which technologies are adopted and how they are implemented, how technology will change the experience of public sector work, and what kinds of interventions can protect against potential downsides of technology use in the public sector. The report categories technologies into five overlapping categories including manual task automation, process automation, automated decision-making systems, integrated data systems, and electronic monitoring.
This academic paper examines how federal privacy laws restrict data collection needed for assessing racial disparities, creating a tradeoff between protecting individual privacy and enabling algorithmic fairness in government programs.
ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT)
This policy brief explores how federal privacy laws like the Privacy Act of 1974 limit demographic data collection, undermining government efforts to conduct equity assessments and address algorithmic bias.
Algorithmic impact assessments (AIAs) are an emergent form of accountability for organizations that build and deploy automated decision-support systems. This academic paper explores how to co-construct impacts that closely reflects harms, and emphasizes the need for input of various types of expertise and affected communities.
ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT)
This report recommends updating the methodology used by the Census Bureau to calculate the Supplemental Poverty Measure (SPM) to reflect household basic needs and replace the current Official Poverty Measure as the primary statistical measure of poverty. The report assesses the strengths and weaknesses of the SPM and provides recommendations for updating its methodology and expanding its use in recognition of the needs of most American families such as medical care, childcare, and housing costs.
National Academies of Sciences, Engineering, and Medicine
Drawing on the Beeck Center’s research on government, nonprofit, academic, and private sector organizations that are working to improve access to safety net benefits, this report highlights best practices for creating accessible benefits content.
