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Computers Understand Humans By Watching And Modeling Them
Computers finally seem poised to take Yogi Berra's advice, namely that "you can observe a lot just by watching".
Despite significant breakthroughs in artificial intelligence, it has been notoriously hard for computers to understand why a user behaves the way she does...
"The benefit of our approach is that much smaller amount of data is needed than for 'black box' methods. Previous methods for performing this type of tuning have either required extensive manual labor, or a large amount of very accurate observation data, which has limited the applicability of these models until now", Doctoral student Antti Kangasrääsiö from Aalto University explains.
The method is based on Approximate Bayesian Computation (ABC), which is a machine learning method that has been developed to infer very complex models from observations, with uses in climate sciences and epidemiology among others. It paves the way for automatic inference of complex models of human behavior from naturalistic observations. This could be useful in human-robot interaction, or in assessing individual capabilities automatically, for example detecting symptoms of cognitive decline.
Great, just what I need; my computer judging me. I suppose turnabout is fair play though; I've been judging the speed and intelligence of my computers for at least fifty years.
Of course, science fiction writers knew that computers need to watch and learn; see this entry on the usuform robot bartender from Anthony Boucher's amusing Q.U.R. (1943).
Via aalto.
Researchers from Aalto University, University of Birmingham and University of Oslo present results paving the way for computers to learn psychologically plausible models of individuals simply by observing them...
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