Connectionism, symbolic AI, and machine learning in AI

Where do the predictive techniques of machine learning come from? How do they represent and organise the social? Join us for a public talk with’s Dominique Cardon (@Karmacoma), Wed 24th April 5pm: https://t.co/oBplRQvRgZ

— Digital Humanities (@kingsdh) April 19, 2019

If you follow the link you'll see this abstract:

Neurons spike back. The invention of inductive machine and the Artificial intelligence controversy - Dominique Cardon (Sciences Po Médialab)

Since 2010, machine learning based predictive techniques, and more specifically deep learning neural networks, have achieved spectacular performances in the fields of image recognition or automatic translation, under the umbrella term of “Artificial Intelligence”. But their relation to this field of research is not straightforward. In the tumultuous history of AI, learning techniques using so-called "connectionist" neural networks have long been mocked and ostracized by the "symbolic" movement. This talk retraces the history of artificial intelligence through the lens of the tension between symbolic and connectionist approaches. From a social history of science and technology perspective, it seeks to highlight how researchers, relying on the availability of massive data and the multiplication of computing power have undertaken to reformulate the symbolic AI project by reviving the spirit of adaptive and inductive machines dating back from the era of cybernetics.

The hypothesis behind this communication is that the new computational techniques used in machine learning provide a new way of representing society, no longer based on categories but on individual traces of behaviour. The new algorithms of machine learning replace the regularity of constant causes with the "probability of causes". It is therefore another way of representing society and the uncertainties of action that is emerging. To defend this argument, this communication will propose two parallel investigations. The first, from a science and technology history perspective, traces the emergence of the connexionist paradigm within artificial intelligence techniques. The second, based on the sociology of statistical categorization, focuses on how the calculation techniques used by major web services produce predictive recommendations.

This talk will be partly based on the article (in French): Cardon (Dominique), Cointet (Jean-Philippe), Mazières (Antoine), «La revanche des neurones. L’invention des machines inductives et la controverse de l’intelligence artificielle», Réseaux, n°211, 2018, pp. 173-220.