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Ken Wenger, automation safety expert and author of "A Layperson's Guide to AI," discusses generative AI and how neural nets work
AI and the Future of Work
AI and the Impact of Bias Training Data on Conversations
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The problem with accuracy alone is that it doesn't capture the full picture. For example, you can have a model that's 90% accurate on some problem, meaning that 90% of the time it gives you the right answer. In testing, however, that doesn't tell you how often it commits either false positives or false negative failures. These are problems that need to be discussed. We need to know the cost of deploying these models. The cost sometimes is other than just accuracy, right, in other areas than just accuracy.
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