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Humans by our very nature categorize things – otherwise how can we really differentiate? How can we learn about new ideas and experiences if not finding a way to store them in our mental models. And in data, we’ve been treating diagnostic and descriptive analytics as an entirely different category to the predictive analytics of AI and ML. The way we partition the world in data is around how data will be used and then prepare the data as such, to be very fit for purpose. What if instead we partition around the data domain and don’t really care about who or how things are used – we want to serve all consumers – what changes? Can we create data that is simply usable by many? Does that actually reduce complexity overall by not owning data production designed to specific purposes? Do we really need to treat AI/ML as if their consumption is all that different or special?
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All music used this episode was found on PixaBay and was created by (including slight edits by Scott Hirleman): Lesfm, MondayHopes, SergeQuadrado, ItsWatR, Lexin_Music, and/or nevesf