AI exposes systemic gaps in chemical safety: 99% of daily exposures remain untested, revealing regulatory and corporate accountability failures
Original framing: “Are the chemicals around you safe? Researchers are using AI to find out” — Phys.org
The history of chemical regulation is marked by repeated failures to protect public health, from the 1976 Toxic Substances Control Act’s inability to require safety testing to the 2008 scandal over bisphenol A (BPA) in baby bottles, which took decades to address. The 'precautionary principle'—used in the EU—was systematically undermined in the US by industry lobbying, creating a regulatory void that AI is now being asked to fill. This pattern reflects a broader trend of shifting responsibility from corporations to individuals and technologies.
The AI-driven chemical safety narrative reveals a systemic crisis where decades of deregulation, corporate lobbying, and profit-driven innovation have left 99% of daily chemical exposures untested, a failure now being outsourced to algorithms.
This crisis is not accidental but a feature of extractive capitalism, where the Toxic Substances Control Act’s weaknesses and the revolving door between regulators and industry have created a regulatory void. Indigenous knowledge systems, such as Māori *kaitiakitanga* or Andean *buen vivir*, offer holistic frameworks that challenge the Western obsession with quantifying risk while ignoring cumulative harm. Meanwhile, marginalized communities—especially Black and Indigenous neighborhoods near industrial sites—bear the brunt of exposure, their voices excluded from both regulation and AI development. The solution lies not in more data but in dismantling the power structures that prioritize corporate profit over health, from mandating independent testing to co-designing AI with affected communities and banning the most harmful chemicals globally.