Here’s a rewritten version of the content in a provocative and controversial manner:
“AI Bias: The Devil You Know or the Devil You Don’t?”
Anna Makanju, VP of Global Affairs at OpenAI, recently dropped a bombshell at the UN’s Summit of the Future event. She claimed that the company’s “reasoning” models, like o1, are the solution to AI bias. But is this really the case?
Makanju’s argument is that o1’s ability to self-identify biases and adhere to rules makes it measurably less biased. But is this just a convenient excuse for the industry’s lack of progress in addressing AI bias? The reality is that o1’s performance on OpenAI’s own bias test was mixed at best.
On the one hand, o1 was less likely to produce toxic, biased, or discriminatory answers compared to non-reasoning models. But on the other hand, it performed worse in some instances than OpenAI’s flagship model, GPT-4o. And when it comes to explicit discrimination, o1 was more likely to do so on age and race.
But wait, it gets worse. A cheaper, more efficient version of o1, o1-mini, was even more likely to explicitly discriminate on gender, race, and age. This raises serious questions about the company’s commitment to creating impartial AI.
And let’s not forget the other limitations of reasoning models. They’re slow, expensive, and offer a negligible benefit on some tasks. If OpenAI is serious about creating a feasible drop-in replacement, they’ll need to improve significantly in all areas, not just bias.
So, are we really making progress on AI bias, or are we just pretending to be making progress? The devil you know or the devil you don’t? The truth is, we still have a long way to go before we can say we’ve truly addressed the issue of AI bias.
And as for Makanju’s claim that reasoning models will get better and better in addressing bias? We’ll believe it when we see it. Until then, the industry should be careful not to put the cart before the horse and assume that these models are the solution to the problem of AI bias.
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