The annual Germeval natural language processing event solicits German-language "shared tasks"; one of this year's proposed tasks from the University of Hamburg is Prediction of Intellectual Ability and Personality Traits from Text, which proposes to mine test subjects' essays as a predictor of IQ. The University of Washington computational linguist Emily M Bender does a good job explaining how this is all kinds of wrong, from supporting the racially biased junk science of IQ testing to the ethical implications of mining subjects' text to predict "intelligence." Bender also points out that one of the people before the shared task, David Scheffer, owns a "neuromarketing" consultancy that offers "automated personality analysis" and "automated personnel selection." A reply in the thread invokes Frank Pasquale's "Second Wave of Algorithmic Accountability," and Pasquale weighs in: "so much depends on where the corpora come from, what was people's intent when they wrote/spoke, what contestable cultural assumptions are built into assessments of complexity from text." The proposers of the shared task have posted a reply that is broadly dismissive of the ethical critique of their work, implicitly refusing to contemplate the possibility that it is unethical to undertake the kind of analysis they're doing for the purposes they're interested in, and instead are pleading with their critics for "dialog" about how it could be made ethical.
German Researchers With Ties To For-profit "neuromarketing" Company Want To Use Ai To Guess Peoples' "intelligence" From Their W
Cory Doctorow, Boing Boing
Thu, 12/05/2019 - 5:43pm
Topics: second wave of algorithmic accountability, second wave germeval german-language hamburg prediction intellectual ability personality traits text the university washington emily m bender david scheffer operant motive test omt motive index mix image cryteria german iq the bender pasquale operant omt omt mix mix mix intelligence school high psychologists motives people questions subjects freely reply write development subsequent
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