OpenAI's VP of global affairs claims o1 is 'virtually perfect' at correcting bias, but the data doesn't quite back that up
OpenAI VP of global affairs Anna Makanju suggests that 'reasoning' models like o1 can solve AI bias. But if that's true, there's much work to be done.
Departures might be dominating the week’s OpenAI-related headlines. But comments on AI bias from Anna Makanju, the company’s VP of global affairs, also grabbed our attention.
Makanju, speaking on a panel at the UN’s Summit of the Future event on Tuesday, suggested that emerging “reasoning” models such as OpenAI’s o1 have the potential to make AI measurably less biased. How? By self-identifying biases in their answers and more closely adhering to rules instructing them not to respond in “harmful” ways, she said.
Models like o1 “actually take longer and are able to evaluate their own response,” Makanju said, “So they’re able to sort of say, ‘Okay, this is how I’m approaching this problem,’ and then, like, look at their own response and say, ‘Oh, this might be a flaw in my reasoning.’”
She added, “It’s doing that virtually perfectly. It’s able to analyze its own bias and return and create a better response, and we’re going to get better and better in that.”
There’s some credence to this. OpenAI’s internal testing found that o1 is less likely on average to produce toxic, biased, or discriminatory answers compared to “non-reasoning” models, including the company’s own.
But “virtually perfectly” might be a bit of an overstatement.