Food Stamps For Thought: Scholarship in Human Services Delivery
mRelief v1, Our First Prototype:
Startup time goes fast. It feels like only yesterday we had our first prototype and now we are on the eve of September 1st, our 1-year-anniversary since we launched live on the web. As a co-founder of mRelief.com, a nonprofit dedicated to fixing the broken American welfare system that leaves the most vulnerable people without access to available public assistance, we are spending more time these days reading about the industry of social service delivery.
While it is important to follow the Product Hunts and Blue Sky Innovations, we are intrigued by solutions proposed in human services delivery as told by scholars who are contending with concepts such as privacy and poverty and the limitations and advantages of automated technology. It first must be said that the leading organization providing platforms for influencers in this space is the New America Foundation. At the intersection of their Asset Building Program and Breadwinners and Caregivers Program they have hosted memorable events bringing thought leaders in multiple disciplines to share solutions on the dynamics of technology, surveillance, privacy and automation as they relate to the public assistance system. Let’s look at 2 key solutions to these problems.
Collect Less Data
In a Slate article co-penned by New America Foundation Senior Fellow Seeta Peña Gangadharan she proposed this solution to preserve the privacy of poor people:
One straightforward solution to this problem would be to collect less data. To target programs effectively, state agencies need information on applicants’ financial circumstances — but maybe not quite as much as we’re collecting. Asset tests, for example, have historically required applicants to turn over reams of paperwork documenting their finances — everything from bank statements to funeral agreements and life insurance policies — despite the fact that most applicants have next to nothing.
This is something we have thought about a lot at mRelief. It is the reason why we created slim screening tools — on average 7.5 questions — that give beneficiaries a sense of whether they qualify for public assistance programs by the most objective criteria before pursuing the entire application. In addition, we hold firmly to the belief that people should be able to get a sense of whether they qualify without having to give lots and lots of data — which is why we only ask for the bare minimum personal identifying information and do not enable providers to ask non-eligibility related questions for public assistance screening.
Stop Means-Testing Programs
In her thought provoking and informative piece, Caseworkers vs. Computers, New America Fellow Virginia Eubanks discusses the perils of automation and what might be one solution to the limitations of automated eligibility determination:
The push to automate intake processes requires computers to do tasks for which they are manifestly unsuited — evaluating the “deservingness” of human beings. In our current political climate, the public assistance system is fixated with gauging applicants’ moral fitness for government aid. Intake processes go far beyond identifying eligibility for programs and then crunching the numbers to determine benefit levels. It’s the conditionality of welfare in the United States — not lack of technical know-how — that makes eligibility automation such a debacle. If we want to successfully modernize our public assistance programs in the United States, the solution is simple: Stop means-testing welfare programs.
It is important to note that there is a difference between automated eligibility determination that is the final answer on someone’s eligibility for a program and preliminary automated eligibility determination that leads to further analysis. mRelief’s core offering focuses exclusively on the latter. mRelief does utilize automated processes in our SMS-based and online screeners. But these preliminary screening tools are designed to complement — not replace — caseworkers. In the Chicago context, our screening tools have been integrated into the eligibility determination processes that case workers on the ground use. That way, a beneficiary can have the best of both worlds: the speed in which a computer can calculate eligibility for multiple programs and a caseworker to build on this analysis to provide holistic care.
Integrating automated eligibility determinations saves 75 percent on average during eligibility determination time allowing case workers — and the vulnerable folks they serve — to move beyond calculations and towards answering tough questions and empathizing in the way that only a human being can provide. In addition, our tools are ramping up to include a host of non means-based programs so that we can increase awareness on the plethora of come-as-you-are programs in the safety net — which still have some requirements — often provided by nonprofits.
Take Home?
Perhaps the key resonating theme of scholars in this space goes back to a saying often stated by board member and Social Work Doctoral student Janae Bonsu, “the people closest to the problem are closest to the solution.”
