Well said. Nevertheless, I feel that we are focusing too much on the algorithms and not enough on the big behavioral data that fuel the predictions. There are so many issues to unpack there. You raise the question of “what kind of person is Joe?” but the behavioral focus of machine learning personalization restricts any kind of “person-level concept” of Joe to a bundle of *recorded* behaviors within the narrow confines of the apps and devices he uses. We must therefore consider which kind of data and what sort of data-representation we wish to give to these algorithms. Ideally there will be some input into this data-representation by the person himself (an intention behind the GDPR, for example). Anywho, if you’re interested, I have a couple pieces about the relation between persons, personal data and personalization (metaphysics of personal data) here https://medium.com/swlh/the-metaphysics-of-personal-data-a-sketch-of-competing-views-c9f482f7f31

Travis Greene. PhD Student in Business Analytics at the Institute of Service Science, National Tsing Hua University https://greenet09.github.io/datasophy/

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