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By Elisabeth Hildt Image courtesy of  Pixabay . Research is not an isolated activity. It takes place in a social context, sometimes influenced by value assumptions and sometimes accompanied by social and ethical implications. A recent example of this complex interplay is an article, “ Deep neural networks can detect sexual orientation from faces ” by Yilun Wang and Michal Kosinski, accepted in 2017 for publication in the J ournal of Personality and Social Psychology. In this study on face recognition, the researchers used deep neural networks to classify the sexual orientations of persons depicted in facial images uploaded on a dating website. While the discriminatory power of the system was limited, the algorithm was reported to have achieved higher accuracy in the setting than human subjects. The study can be seen in the context of the “prenatal hormone theory of sexual orientation,” which claims that gay men and women tend to have gender-atypical facial morphology. The abstract ...

By Andy Clark Andy Clark is Professor of Logic and Metaphysics in the School of Philosophy, Psychology and Language Sciences, at Edinburgh University in Scotland. He is the author of several books including Surfing Uncertainty: Prediction, Action, and the Embodied Mind (Oxford University Press, 2016). Andy is currently PI on a 4-year ERC-funded project Expecting Ourselves: Prediction, Action, and the Construction of Conscious Experience . In this post, I’d like to explore an emerging neurocomputational story that has implications for how we should think about ourselves and about the relations between normal and atypical forms of human experience. Predictive Processing: From Peeps to Phrases The approach is often known as ‘predictive processing’ and, as the name suggests, it depicts brains as multi-area, multi-level engines of prediction. Such devices (for some introductions, see Hohwy (2013), Clark (2013) (2016)) are constantly trying to self-generate the sensory stream – to re-creat...

By Katie L. Strong, PhD  In a quiet room in a London office building, artificial intelligence history was made last October as reigning European Champion Fan Hui played Go , a strategy-based game he had played countless times before. This particular match was different from the others though – not only was Fan Hui losing, but he was losing against a machine. The machine was a novel artificial intelligence system named AlphaGo developed by Google DeepMind . DeepMind, which was acquired by Google in 2014 for an alleged $617 million (their largest European acquisition to date), is a company focused on developing machines that are capable of learning new tasks for themselves. DeepMind is more interested in artificial “general” intelligence, or AI machines that are adaptive to the task at hand and can accomplish new goals with little or no preprogramming. DeepMind programs essentially have a kind of short-term working memory that allows them to manipulate and adapt information to ma...