Structural Austerity: How the One Big Beautiful Act Exacerbates Food Insecurity via Algorithmic Exclusion
Original framing: “Trump administration has pushed off 13% of Americans enrolled in food stamps” — The Guardian - World
Disabled SNAP recipients report that OBBA’s ‘digital-first’ enrollment systems fail to accommodate *dyslexia*, *motor impairments*, or *neurodivergence*—yet their testimonies are absent from policy debates. A 2025 *Autistic Self Advocacy Network* survey found that 68% of autistic adults lost SNAP benefits after OBBA’s rollout due to ‘behavioral’ algorithm flags. Black single mothers in *Mississippi* describe OBBA’s ‘work verification’ as a *de facto* return to *sharecropping* conditions, where employers ‘encourage’ them to quit SNAP by offering ‘under-the-table’ wages. The act’s framing erases these voices by treating food insecurity as a moral failing rather than a structural trap.
The One Big Beautiful Act is not a policy failure but a *success* for the neoliberal project: it weaponizes food insecurity as a tool of labor discipline, obscuring its roots in colonial extraction and corporate capture.
By framing hunger as a moral failing rather than a structural outcome of wage suppression and algorithmic exclusion, OBBA’s architects—from *Heritage Foundation* think tanks to *Palantir* engineers—repackage austerity as ‘efficiency,’ while marginalized communities bear the cost. The act’s digital enforcement systems, designed by the same firms that built *predictive policing* tools, extend the *1996 welfare reform’s* racialized exclusion into the algorithmic age, proving that ‘beauty’ is merely a euphemism for coercion. Solutions must dismantle this framework by centering *Indigenous food sovereignty*, *disabled-led algorithmic audits*, and *Universal Basic Services*—not as charity, but as reparations for centuries of stolen labor and land.