ECGC 2019 Sessions

APRIL 16TH – 18TH, 2019

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The Black Mirror implications of using Data Exhaust and Machine Learning to Model People

April 17 at 10:15 am - 11:15 am

Room: 306B

By Richard Boyd

In this talk, I will discuss how the data exhaust hapless humans leave behind as they traipse and trollop around the Internet can be harnessed with machine learning to model them in great detail, for both positive and negative purposes. There is evidence that these synthetic models can be better predictors of future behavior than focus groups and surveys. Netflix and Amazon and Google all know that if you want to understand people, you don’t ask them questions, you monitor what they do with their time, money and attention.

The implications of this revelation range from explaining why no exit polls and surveys predicted Donald Trump or Brexit; to why we now demand kale in restaurants when no one was eating it six years ago, and how we are going to manage personal, commercial and political relationships in the future. Can we resurrect the dead? Should we? What conversations would we have with these synthetic people? What are the implications for characters in gaming?

Pre-reading Doc Searls’ book “The Intention Economy” will be very helpful before this talk. It also wouldn’t hurt to watch a few Black Mirror episodes or read some Ray Kurzweil rants.


April 17
10:15 am - 11:15 am
Event Category:


Analytics, Other
Richard Boyd

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