AI tools for public benefits
Researching alongside our stakeholders
We conducted research with stakeholders at every level of the benefits application process. This included professionals who help people apply for benefits, often called navigators, program beneficiaries, and strategic advisors from organizations in the public benefits space. We spoke to our participants in 60-minute, remote sessions and sourced them through a combination of personal connections, online advertisements, and referrals from community-based organizations. We will continue to engage with beneficiaries and strategic advisors throughout the project.
Process
We spoke to 14 navigators and subject matter experts who possess deep, cross-programmatic expertise in helping others apply for benefits. Collectively, they connect with beneficiaries over the phone, in WIC clinics, hospitals, and other community-based settings. They represented the following organizations:
Maryland Hunger Solutions (SNAP Outreach)
Public Health Solutions NYC
Legal Assistance of Western New York
Food Research and Action Center (FRAC)
Benefits Data Trust (BDT)
WIC state and local agencies
Our Strategic Advisory Council, which includes leaders in early childhood systems change, human services policy, and civic technology, meets monthly to provide ongoing feedback on our research findings and prototype development, emphasizing state and local contexts for applying AI-powered tools. Our strategic advisors represent the following organizations:
American Public Human Services Association (APHSA)
Center for Public Sector AI
Having and Child and Early Childhood Life Experience Team
Center on Budget and Policy Priorities (CBPP)
Family Voices
Help Me Grow National Center
Center for Health Care Strategies (CHCS)
In addition to our strategic advisors and navigators, we formed a Family Advisory Board. It consists of 12 parents and caregivers who have experience applying for and managing benefits. The Family Advisory Board members represent different races, ethnicities, languages, immigration status, ages, caretaking roles, abilities, locations, programs, and access to technology. They also had experience applying for and managing benefits in the following programs:
Early Head Start
WIC
Medicaid
Medicare
SNAP
Cash assistance/Temporary Assistance for Needy Families (TANF)
Family and Medical Leave (FMLA)
Unemployment insurance
Disability benefits
Home Energy Assistance Program (HEAP)
Supplemental Security Income (SSI)
Housing assistance
Job readiness program
When interviewing our strategic advisors, navigators, and beneficiaries, we focused on asking about participants’ lived experiences applying for or helping others apply for benefits, which revealed several pain points in the benefits application process. By identifying pain points, we were able to brainstorm applications of AI-powered tools that might make the benefits application process easier. We also worked with navigators and strategic advisors to gain an understanding of the end-to-end process of applying for benefits, from initial outreach to the administration of benefits. This helped us pinpoint use cases for AI at specific stages of the process, such as during the initial screening of an applicant or during a phone call between an applicant and a navigator. Lastly, we spoke to participants about their feelings on AI in public benefits and ideas for how AI might be leveraged for different use cases. Their concerns and ideas are informing how we design our experiments.
