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Hey Heidy and Anima - we agree this is a huge issue, and it's one we're very engaged on. We're identifying + communicating known biases in our models to customers, setting up academic partnerships to dive deeper, + developing tools to reduce problematic outputs. (1/2)
Thanks for getting back @Miles_Brundage That's good that you are working to reduce biases. But how are you monitoring how your customers are using these models? @awscloud had same excuse for launching racist face recognition. There is no accountability and that disturbs me.
Great question! So far we're working with a small # of customers, so we're familiar with each use case. Going forward, we're thinking about more scalable approaches to monitoring use, though it's definitely a challenge (Terms of Use + use case restrictions will also play a role).
Really disturbing that your basic answer is: "we'll let our customers figure it out". What about fundamentally changing the way models are constructed, and not creating bigoted models? What happened to ethical AI, "benefiting humanity", and having a "positive human impact"?
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