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Do algorithms dream of consciousness?

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22 May 2019




21:00 (more or less) 

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Brussels Beer Project

Rue Antoine Dansaert 188, 1000 Bruxelles






While most people put an ethereal mind or spirit at the origin of consciousness, neuroscientists are gathering increasing amounts of evidence for consciousness as a property of the brain. If that is the case, are we just biological machines? Will we soon be able to crack the brain code and develop self-conscious AIs? How about AIs with ethical values and principles? While cognitive scientists like Axel Cleeremans seek to discover what separates us from machines, computer scientists like Toon Calders are looking for ways to fix discriminatory effects that predictive algorithms may have.

Machine-learning discrimination: bias in, bias out

Toon Calders

Data mining researcher & Professor

University of Antwerp

Artificial intelligence is more and more responsible for decisions that have a huge impact on our lives. But predictions made using data mining and algorithms can affect population subgroups differently. Academic researchers and journalists have shown that decisions taken by predictive algorithms sometimes lead to biased outcomes, reproducing inequalities already present in society. Is it possible to make a fairness-aware data mining process? Are algorithms biased because people are too? Or is it how machine learning works at the most fundamental level?

Photo credit: Berkman Klein Center

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Consciousness: is this what separates us from machines?

Axel Cleeremans

Director, ERC Grantee

Neuroscience Institute, Université Libre de Bruxelles

While computers can calculate or recognise faces, they are not aware of themselves (yet?). Consciousness is in the essence of human beings; its nature, however, appears to lack a reliable explanation. Prof. Axel Cleeremans is developing a new theory, the Radical Plasticity Thesis, maintaining that consciousness is a long-lasting property of our brain rather than just a static feature. In order to test it, he is taking a multidisciplinary approach including psychological studies and advanced brain imaging.

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