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NLP ZURICH Linkedin: / nlp-zurich YouTube: / @nlpzurich4889 Twitter: / nlp_zurich TALK SUMMARY For an industry that prides itself on moving fast, the tech community has been remarkably slow to adapt to the differences of designing with AI. Machine learning is an intrinsically fuzzy science, yet when it inevitably returns unpredictable results, we tend to react like it’s a puzzle to be solved; believing that with enough algorithmic brilliance, we can eventually fit all the pieces into place and render something approaching objective truth. But objectivity and truth are often far afield from the true promise of AI, as we’ll soon discuss. In this talk, I’m going to introduce three conversations that I think every product team should have prior to breaking ground on AI development. The point of these conversations isn’t to plan for every little detail or solve all your problems in advance. The point is to engage with one another, to promote intellectual curiosity, to make space for common sense, and to commit to acting with purpose. The point is to be able to say what you’ll do and do what you say. 1. Capability: What is uniquely AI and what is uniquely human? 2. Accuracy: What does “working as-intended” mean for a probabilistic system? 3. Learnability: How will people build — and rebuild — trust in something that’s inherently fallible? THE SPEAKER Josh leads Design for Ethics & Society at Microsoft, where his team works at the intersection of product development, user experience, AI, law, and philosophy. Prior to Microsoft, he was UX lead for People+AI Research at Google and founded Amazon’s unified design system for online shopping experiences. Twitter: https://twitter.com/jdlovejoy?s=20