‘World lacks rigorous scientific methods to test AI safety’

The teams get dismantled.

- Binayak Dasgupta

(GETTY IMAGE)

The testing tools are scientifically inadequate. The commitments don't survive changes, corporate or political. And no jurisdiction has found a governance model that works to make AI safe and responsible.That is the assessment of Rumman Chowdhury, who led AI safety policies at (erstwhile) Twitter, at the US government, and in civil society, speaking to HT on the sidelines of the India AI Impact Summit. She is the CEO and co-founder of the nonprofit Humane Intelligence, which works for community-driven AT auditing and evaluation.

“One of the big things that happens at all these summits is new voluntary commitments,” she said. “It's lovely PR and great optics, but what does it tangibly, fundamentally mean? These organisations cannot live at the mercy of companies or political organisations. In order to be codified or solidified, it needs to actually be something required by law.”

Chowdhury has reason to be direct. She directed the ML Ethics, Transparency, and Accountability (META) team at X (formerly Twitter), which published a study on algorithmic amplification of political content. The team was dissolved after Elon Musk’s acquisition. She subsequently led the US Department of Defense's Responsible AI division, was designated the US Science envoy for AI, and stepped down as the Trump administration reorganised the office and revoked Biden-era safeguards. Two responsible AI teams, two collapses — one corporate, one political.

For Chowdhury, CEO and co-founder of AI safety nonprofit Humane Intelligence, the Twitter algorithm analysis — the only one by a Big Tech company yet involving independent, outside researchers — exposed a problem relevant in AI safety regulation today. The analysis had found Twitter was surfacing more right-wing content organically.