Machine learning is innately conservative and wants you to either act like everyone else, or never change

Next month, I'm giving a keynote talk at The Future of the Future: The Ethics and Implications of AI, an event at UC Irvine that features Bruce Sterling, Rose Eveleth, David Kaye, and many others!

Preparatory to that event, I wrote an op-ed for the LA Review of Books on AI and its intrinsic conservativism, building on Molly Sauter's excellent 2017 piece for Real Life.

Sauters insight in that essay: machine learning is fundamentally conservative, and it hates change. If you start a text message to your partner with Hey darling, the next time you start typing a message to them, Hey will beget an autosuggestion of darling as the next word, even if this time you are announcing a break-up. If you type a word or phrase youve never typed before, autosuggest will prompt you with the statistically most common next phrase from all users (I made a small internet storm in July 2018 when I documented autocompletes suggestion in my message to the family babysitter, which paired Can you sit with on my face and).

This conservativeness permeates every system of algorithmic inference: search for a refrigerator or a pair of shoes and they will follow you around the web as machine learning systems re-target you while you move from place to place, even after youve bought the fridge or the shoes. Spend some time researching white nationalism or flat earth conspiracies and all your YouTube recommendations will try to reinforce your interest. Follow a person on Twitter and you will be inundated with similar people to follow.