{"id":6843,"date":"2024-07-04T06:27:23","date_gmt":"2024-07-04T04:27:23","guid":{"rendered":"https:\/\/www.uni.lu\/c2dh-en\/articles\/creativy-and-ai-recording\/"},"modified":"2026-01-27T14:35:37","modified_gmt":"2026-01-27T13:35:37","slug":"creativy-and-ai-recording","status":"publish","type":"articles","link":"https:\/\/www.uni.lu\/c2dh-en\/articles\/creativy-and-ai-recording\/","title":{"rendered":"Creativy and AI – recording"},"content":{"rendered":"\n
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Recording of the conference with Alban Leveau-Vallier on Creativy and AI (12 June 2024).<\/strong><\/p>\n\n\n\n

Alban Leveau-Vallier is a postdoctoral researcher at University Paris 8 and lecturer at Sciences Po Paris. He recently published IA, l\u2019intuition et la cr\u00e9ation \u00e0 l\u2019\u00e9preuve des algorithmes<\/a><\/em> (Champ Vallon).<\/p>\n\n\n\n

In his proposal for the Dartmouth summer research project (1955-1956), Nathaniel Rochester wondered whether injecting some randomness into a machine could make it creative. But how to control this randomness to prevent machines crashing and ensure the generated content\u2019s relevance ? Seventy years later, the so-called \u00ab generative AI \u00bb seems to have solved the problem, or at least circumvented some obstacles. Despite the difficulty of estimating what goes on inside deep neural networks, we will briefly describe what \u00ab creativity \u00bb is about in generative AIs (interpolation in a latent space) and the current controversy over how to evaluate it using dedicated benchmarks. Then, drawing from literature and philosophy (Borges, Caillois, Bachelard), we will challenge the claim that it can be compared to human creativity. Finally, we will examine how these machines don\u2019t have to be creative like humans to trigger an epochal change that we need to characterize.<\/p>\n\n\n

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