I recently wrote a blog entry on the Progressive Gauge site. That is where the work associated with my technical writing practice is located. This entry is a review and meditation on Jill Lepore's "If Then" which looks at the '60s research group known as Simulmatics. The intro follows along with a link to the story on Progressive Gauge.
I'd hope to bring in a wider discussion that included things that touched me over time: the Army Math Research Center, Rand Corp ill-fated work in New York City government, and maybe even the Symphony Road Arson research done by David Scondras (who passed just last week, as I worked on this story). But had to keep it focused. - J.V.
Advances in Artificial Intelligence have always been muted, moving forward in spasms. When these advances take the form of “AI,” they are cloaked in a mystic veil – that changes as they make it to production.
When AI models actually work, they take on the form of castoffs. Once-new technologies like machine vision, circuit optimization, or voice recognition throw away their AI badge and are sprouted unannounced in fertile ground.
AI that doesn’t sprout continues a long trudge through academic research labs, questing for the holy grail that usually amounts to “predicting the future.” Then they sprout anew. The much-discussed algorithms of Amazon, Google, Facebook and Cambridge Analytica have a pre-history and are cases in point. Their makers don’t mind if some of the veil of mystic shroud remains.
This is what it looks like today – Amazon predicts what book you’ll buy, Google predicts which ad to serve you, and Facebook predicts which meme of the moment will hold your attention.
The purpose of Cambridge Analytica’s algorithm was to predict which profiles could be pinged to move an election. To the extent this may have influenced an election, it might be the most powerful algorithm of all. In any case, all these wonks’ algorithms had precursors in Collaborative Filtering and Software Agents – AI efforts of yore. Today’s they prowl the Web inside Recommendation and Personalization engines.
Such precursors are forgotten in the rushing currents of news. Behind the algorithms is a history populated by people with the requisite defects that humans show, which a recent book by Harvard historian Jill Lepore uncovers in engaging detail.
In “If Then: How the Simulmatics Corporation Invented the Future” [W.W. Norton, 2020], Lepore explores a 1960s corporation that sought to apply what is now called data science to politics and other domains, doing the algorithms by hand but then using the mainframe computers of the day, to predict social outcomes. TO READ MORE, CLICK ON LINK THAT FOLLOWS.
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