"same [AI] techniques will be able to … transform whole industries. But this won’t happen—or shouldn’t happen—unless we find ways of making techniques like deep learning more understandable to their creators and accountable to their users."https://www.technologyreview.com/s/604087/the-dark-secret-at-the-heart-of-ai/?utm_source=facebook&utm_medium=tr_social&utm_content=2017-12-31&utm_campaign=site_visitor.unpaid.engagement&fbclid=IwAR26Ii8D7xgNZdxyg4pS2qI5-Ad-I9WQdVYIQ06nIpSVPeAHN31uVg1IQpU …
This is a practical problem, in that enterprise customers insist on visibility into how the algorithm works. I built such a tool for our client at Palantir; it was just a random forest, but we had to show the humans what factors contributed to the algorithm's decision.
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Many industries are TOTALLY unused to rubrics that are probabilistic and multifactorial. Not an 'AI' issue but a statistics issue. Many people are uncomfortable with uncertainty. They won't accept a rubric that spits out a probability without a lot of skeumorphism.
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Some customers so insist, others do not. Its a nice feature to have, but things like "more understandable" and "factors contributed" are matters of degree.
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