Ethics & Coffee with Liran Razinsky: How Well Can Algorithms Know Us?
Liran Razinsky, senior lecturer at Bar Ilan University in Israel, will explore the widely circulated idea that big data AI algorithms will soon be able to know people “better than they know themselves.”
He will address this idea from two perspectives. First, he argues for the particular subjective qualities of experience and self-understanding issuing from the constitutive role of our reflexive relation to ourselves. These are not “known” by the algorithms. He will then address our fundamental opacity to ourselves and the biased, partial, and limited nature of human self-understanding. Our failure to know ourselves is however essential to our subjectivity and therefore, to know a subject in a perfect way that bypasses these limitations is actually not to know them. Taken together, both directions show that while algorithmic knowledge of humans can be vast, and can outperform their own knowledge, it remains foreign to their subjectivity and cannot be said to be better than self-understanding.
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Michael Hoffmann
michael.hoffmann@pubpolicy.gatech.edu