Through our research understanding the government digital service field and what workers in this field need, we want to help strengthen those existing roles and establish more pathways for promotion and career support, as well as help other teams recognize the value of these skills and create new roles.
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)
In this piece, the Digital Benefits Network shares several sources—from journalistic pieces, to reports and academic articles—we’ve found useful and interesting in our reading on automation and artificial intelligence.
In this updated primer, the DBN introduces the concept of digital identity, and provides brief snapshots of digital identity-related developments internationally and in the U.S.
The report examines how current remote identity proofing methods can create barriers to Medicaid enrollment and suggests improvements to ensure equitable access for all applicants.
Annual Computers, Software, and Applications Conference (COMPSAC)
What exactly are the differences between generative AI, large language models, and foundation models? This post aims to clarify what each of these three terms mean, how they overlap, and how they differ.
Center for Security and Emerging Technology (CSET)
This mainstage session from FormFest 2024 included conversations about form design, accessibility, user experience, and data collection to show how good forms can build trust and confidence in government.
The Digital Benefits Network at the Beeck Center for Social Impact + Innovation at Georgetown University and Public Policy Lab co-hosted a webinar presenting breaking research on beneficiary experiences with digital identity processes in public benefits.
