CLAIR Conference

What happens when AI stops helping scientists analyse knowledge and starts helping create it? A recent result from mathematics may offer an early glimpse of that future. An AI model reportedly contributed to solving a problem that had challenged researchers for nearly 80 years, identifying a novel mathematical approach that experts had not previously considered. This may be one of the clearest demonstrations yet of AI moving beyond information processing and into scientific discovery. At #CLAIR, this is precisely why Scientific Models is one of our first focus areas. The long-term opportunity is not simply to build AI systems that analyse scientific data more efficiently. It is to develop models that can help researchers generate hypotheses, uncover hidden relationships, and accelerate the creation of new knowledge. Mathematics provides a highly structured environment where discoveries can be rigorously verified. In R&D environments like Health and life sciences are far more complex, involving heterogeneous data, uncertain causal relationships, and demanding requirements for transparency, trust, and governance. This makes robust data infrastructures, interoperability, and high-quality research data more important than ever. If AI can contribute to solving a problem that has challenged researchers for nearly 80 years, the question is no longer whether scientific AI is possible. The question is how we build the ecosystems that allow researchers, AI, and data to work together in creating the next generation of scientific and industrial breakthroughs. #CLAIR #ScientificModels #AIforScience #ResearchInnovation #Interoperability #Leadership #FutureOfResearch

I’m delighted to share that I will be speaking at CLAIR – International Conference on Leadership & AI in Research, taking place in Copenhagen on 16–18 September 2026. I will join Charlotta Kronblad and Petra Wilson for a cross-industry panel on “Leading Research into an AI-Defined Future”, exploring how artificial intelligence is reshaping scientific methods, decision-making, organizational leadership, and innovation in research-intensive environments. CLAIR offers a unique forum for academia and industry to come together and discuss not only what AI can do, but what it means for the future of research, accountability, trust, and leadership. I look forward to the discussion and to exchanging perspectives with researchers, leaders, policymakers, and innovators in Copenhagen. More information and agenda: https://lnkd.in/evW5UsHd #AI #Research #Competitiveness #Innovation #CLAIR2026. EFPIA - European Federation of Pharmaceutical Industries and Associations

Looking forward to lots of meaningful discussions in Copenhagen.

“If you’re not tokenmaxxing, it’s hard to compete.” That line from a recent article in Svenska Dagbladet stayed with me. We have moved from measuring working hours and productivity to measuring AI consumption: number of agents, number of tokens, number of automated decisions. In Silicon Valley, titles such as “Token Legend” and “Cache Wizard” are reportedly being handed out. Employees are evaluated based on how much AI they use. It is fascinating. But also worth pausing to reflect on. Because when “tokenmaxxing” becomes a culture, we risk optimizing for what is easy to measure — rather than what actually creates human value: judgment, empathy, creativity, responsibility, and trust. AI can dramatically increase productivity. There is no doubt about that. But if the future of work becomes a competition over who can consume the most tokens the fastest, we may be missing the most important question: What will humans contribute when machines become better at almost everything measurable? This is precisely why CLAIR matters. Not only as a conference about AI technology — but as a forum for discussions about leadership, healthcare, ethics, society, and the human role in an AI-driven world. Because the future will not be determined only by how powerful AI becomes. But by which human values we choose to amplify with it.

About the CLAIR Conference #Innovative. #Interactive. #High-#End. A conference is ultimately defined by the conversations it enables. 🎤 Meet four of the experts shaping this year’s dialogue at #CLAIR: Brian Spisak PhD, Aaron Mann, Nakshathra Suresh and Thomas Senderovitz. Together, they bring perspectives spanning leadership science, data collaboration, responsible AI and innovation policy — reflecting the interdisciplinary exchange CLAIR is designed to foster.   Through their talks, they will challenge assumptions, contribute new perspectives on #AI in research-intensive environments, and help bridge #scientific #rigor with #practical #transformation. It is this combination of deep expertise and cross-sector relevance that makes their contributions central to the CLAIR experience. In our "About the Conference" series, we continue introducing the people shaping CLAIR Conference — from #committees and #ambassadors to the #speakers driving this year’s dialogue. #Conference #Leadership #AI #Research #ScientificLeadership #ResponsibleAI #Community

“Perhaps the problem is not that AI is becoming more human. Perhaps the problem is that humans are increasingly describing themselves as machines.” Reading Johan Anderberg’s article in Svenska Dagbladet — “This Could Be the Beginning of Our Downfall” — that line stayed with me. Every technological era shapes how we understand ourselves: the heart as a pump, the nervous system as electricity, and now the human being as a computer. If intelligence is reduced to information processing, optimization, and decision-making, it is no surprise that AI will outperform us in those areas. Daniel Kahneman transformed our understanding of human behavior, but the article raises an uncomfortable question: have we reduced human value to productivity and cognitive performance? This is why conferences like CLAIR matter. AI is not only about algorithms and automation. It is also about what we choose to value as uniquely human. Perhaps we are competing in the wrong race. See you in Copenhagen in September! https://lnkd.in/edG67Waf