Microsoft and Amazon offer tools to detect bias and toxicity in AI models, but the real problem is leadership that understands what those metrics mean and acts on them. Most implementers treat these tools as black boxes instead of thinking deeply about responsibility.
Today, luckily, there are companies like Microsoft, like Amazon that have implemented frameworks, packages, tool sets for monitoring toxicity, for monitoring injustice, for monitoring bias. Um, but the funny thing is, is those tools are not new. I think what's new, hopefully, is a new type of leadership that knows to look at that data and take action on it. Um, like in machine learning, we've been looking at bias in machine learning for a long time, But will our leadership or will the teams that leverage these apply, you know, black boxes, will they know to look at the data that's being provided by these models and say, oh, toxicity, what does that number even mean to us? That I think is the burden today is how do we get our, you know, how do we get the implementers and users of this technology to think more deeply about what it means to be responsible?
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