At the Panoramai AI Summit, Michel Jaccard, Founder & Partner at id est avocats, delivered a provocative analysis of intellectual property and legal frameworks in the AI age. Drawing on his extensive experience in M&A deals and intellectual property rights while accompanying startup ecosystems, he challenged conventional approaches to AI regulation and innovation protection.

The Innovation-Theft Paradox

Jaccard presented a controversial thesis on the nature of innovation: « From the moment we want to innovate, we have to steal. So the history of science, of the evolution of science, of the arts, of architecture, of music, it's a story of successive flights, of imitation, of successive flights, of the use of what was known ». He positioned this not as criticism but as historical reality, arguing that breakthrough innovations inherently build upon existing work.

The Google Books Precedent

He cited Google Books as a paradigmatic case: « Google Books is the school case of the massive violation of intellectual property. It was Google who at some point decided that in libraries, they would scan, page after page, the entire contents of the libraries ». Despite initial outrage and litigation, Google ultimately transformed industry dynamics and compensated affected parties, establishing a pattern for AI development.

Regulatory Skepticism

Jaccard advocated against waiting for legislative solutions: « Don't wait for the courts to agree. It will take a long time. Don't wait for politicians to represent your interests. It is an intimate and personal decision to know how we want to position ourselves in relation to these tools ». He pointed to GDPR's limitations despite its regulatory ambitions: « We realize that despite the magnificent quotas that have been set up... each person, even those who criticize social media, are all on LinkedIn, published three posts a day ».

AI Litigation Forecast

He predicted current legal challenges will follow established patterns: « There are a lot of lawsuits going on against content creators, etc. You have to hold on for five years and then the balance of power is reversed ». This suggests that well-funded AI companies will ultimately prevail through persistence and market transformation rather than legal victory.

Copyright's Evolution

Jaccard outlined how AI challenges traditional IP frameworks: « Copyright exists, and the protection of copyright exists on what comes from a human creation. So there is already a part of this creation, of this creative idea, which is not captured by the law ». He noted that AI competition focuses more on trade secrets and talent acquisition than patent protection.

Economic Model Transformation

Addressing concerns about universal income and taxation, Jaccard proposed streaming-style solutions: « We will make a tax a bit like streaming, so we will have a system... those who have photocopiers must pay at the end of the year 10 cents or I don't know what the royalty is, per photocopy ». This collective management approach could compensate creators while enabling AI development.

Individual Agency Over Regulation

His core message emphasized personal responsibility: « It's our behavior in relation to this technology... From the moment one player stops playing the game, it's going to be the deck of cards that falls ». He stressed that technological adoption depends on individual choices rather than regulatory frameworks.

Five-Year Social Focus

Jaccard's outlook prioritized social implications over technical challenges: « In five years, there will be a lot of lawyers who will be much richer. Or not. So it's no longer a technological problem, it won't be at all in five years. It will be considerably a social problem, so of social cohesion ». He emphasized education and critical thinking: « There must be a possibility to be a European citizen or of this world happy in five years without having to be dependent on all this technology that surrounds us ».

Key Achievement: Michel demonstrated how legal frameworks must adapt to AI's disruptive nature, advocating for pragmatic approaches that acknowledge innovation's inherently transformative character while preparing for social rather than technological challenges in AI's mature phase.