Artificial intelligence (AI) will officially be 70 in 2026! Even so, the general public has only recently begun paying attention. Some are still discovering that they are free to use ChatGPT, Bing Chat or soon Bard in France. Others started asking questions with the call for a moratorium on AI research made in March 2023[1] by upwards of 1,000 experts, including business leaders like Elon Musk and researchers like Yoshua Bengio, one of the leading pioneers in AI.[2] The fact that Geoffrey Hinton, another of the “Godfathers of AI”,[3] joined the ranks of the “concerned” in early May has done little to calm the debate.[4]

We wanted to do our bit to contribute to the understanding of generative AI systems, the strong potential of which and the legal issues they raise are a cause for concern. Where is this phenomenon taking us? What does it mean for organizations baking this type of AI into their production processes? To talk about this with you, Philippe Limantour, Chief Technology Officer at Microsoft France, joined Emmanuelle Mignon and Marc Mossé, lawyers at August Debouzy last May 10th.

"I've been working on AI for 37 years, and I've been waiting for this moment.” For Philippe Limantour, the real AI revolution came a few months ago, with the emergence of generative AI. It took decades of research before major breakthroughs were made.[5]

The Dartmouth conference in 1956 is where it all began: a group of researchers set out to imitate human cognitive functions using the computing capabilities of computers. At the time, it was thought that this would not take long.

But only in the 1990s did we see the first significant applications of AI thanks to machine learning. However, the hyperspecialization of trained AI systems was an obstacle: for each domain, use case, language used, etc., a model had to be trained by a large number of specialists.

The European Union is currently discussing a proposed regulation on AI (AI Act). With a view to facilitating innovation while protecting society, it has opted for a graduated, risk-based regulatory approach: AI applications are classified according to their level of risk, and legal rules vary according to this hierarchy,[1] which will evolve over time.

On the topic of the liability issues in connection with AI models, Marc Mossé told us that a proposed directive is also in the works, addressing issues such as the presumption of causality or access to evidence to facilitate compensation for victims. The categories established in the proposed regulation have been carried over in the wording of the directive.