Ok, fine but... Understanding bias isn't what engineers are trained to do. It's not just running a few correlations.pic.twitter.com/Me8b2yWk39
Complex systems, wicked problems. Society, technology, science and more. @UNC professor. @NYTimes columnist. My newsletter is @insight: http://www.theinsight.org
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Ok, fine but... Understanding bias isn't what engineers are trained to do. It's not just running a few correlations.pic.twitter.com/Me8b2yWk39
Silicon Valley doing "ontogeny recapitulates phylogeny" in social sciences. From behaviorism to positivism. Awaiting discovery of Foucault.
Causal inference in human social systems is hard. Your "data" is limited and biased. Need depth of understanding. Being smart isn't enough.
If you want to deal with bias in digital platforms, you gotta bring in people who think a lot about stratification, inequality, culture...
Engineers, you know how you are befuddled by very smart people who can't figure out email? Sometimes, that's you, with human social systems.
(Yes, Smart people can be confused by computers. I know one of world's top physicists: can barely email. Domain expertise. Really).
The culture clash is real; methodological gap between engineers & trad social scientists is real but silos won't let you solve the problems.
There is a lot of social science expertise in "unintended" consequences of "easy-seeming" fixes from available data. A lot of it is subtle.
You can't just hire a few social scientists to Silicon Valley (often mostly economists anyway). Would need real teams; different thinking.
Also, AirBnB's race problem was apparent from day one among social scientists BECAUSE IT WAS TERRIBLY EASY TO PREDICT. Why did they not see?
We see this often: a terribly easy to see complication to business model is ignored for years, then a team of engineers tasked after outcry.
Truth is, there *are* a lot of things companies CAN do easily to help solve this, and then there are a lot of hard problems in this space.
You'd need—at a minimum—a huge dose of humility; willingness to hire & *empower* social scientists of stratification, culture & inequality.
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