A report that defines what effective “human oversight” of AI looks like in public benefits delivery and offers practical guidance for ensuring accountability, equity, and trust in algorithmic systems.
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.
As a part of Benefit Data Trust (BDT)’s Medicaid Churn Learning Collaborative, BDT has created a memo describing policy options and state examples for Medicaid administrators to reduce churn for non-MAGI Medicaid enrollees when the federal public health emergency ends.
