AutoML can be a tool for good, but there are pitfalls along the way. Rahul Sharma and David Selby tell us about how AutoML systems can be used to give us false impressions about explainability metrics of ML systems - maliciously, but also on accident. While this episode isn't talking about a new exciting AutoML method, it can tell us a lot about what can go wrong in applying AutoML and what we should think about when we build tools for ML novices to use.
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