From the course: Machine Learning and AI Foundations: Producing Explainable AI (XAI) and Interpretable Machine Learning Solutions
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The argument against XAI - KNIME Tutorial
From the course: Machine Learning and AI Foundations: Producing Explainable AI (XAI) and Interpretable Machine Learning Solutions
The argument against XAI
- [Instructor] The first time I encountered the ideas of Cynthia Rudin, I was attending her keynote at the 2019 Knowledge Discovery in Databases conference in Anchorage, Alaska. The premise of her keynote was perhaps we're using complicated models when we don't need them. You can find her keynote on the internet, and I highly recommend it. She's become very vocal, and she's taken a strong contrarian position on explainable AI, but she's very well regarded. She recently won a million-dollar award for pioneering work in socially responsible AI. I'd like to briefly summarize the key points of her position. If you're curious to learn more, she's prolific, so it's easy to find articles and presentations where she discusses these points in more detail. She and her graduate students have also made a number of technical contributions to the field, some of which we'll see later in the course. First, she argues that accuracy is…
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