Artificial intelligence enables scientific results to be achieved up to 10,000 times faster
Leadership in AI requires massive infrastructure and long-term investment
AI has become a decisive force in the modern era, playing a central role across cultural, economic, and scientific fields
Warnings over social risks and challenges, with calls to focus on AI technologies that enhance human effort rather than replace it
The Artificial Intelligence Sciences Forum, held as part of the World Scientists Summit, which launched today alongside the World Governments Summit, discussed the impact of artificial intelligence on shaping the economy, the future of jobs, policymaking, and its ability to accelerate science and research.
The World Scientists Summit is considered the largest global gathering of its kind, bringing together over three days more than 100 scientists and participants, including Nobel Prize laureates and recipients of other prestigious international scientific awards, as well as leaders of research institutions.
This takes place alongside the World Governments Summit 2026, scheduled from February 3 to 5, with February 3 designated as a joint day bringing together scientists with heads of state, governments, ministers, and leaders of international organizations and institutions participating in the World Governments Summit.
Participants at the forum emphasized that the future of artificial intelligence is neither inevitable nor purely driven by technical details, but rather a shared societal choice that requires global dialogue, responsibility, and innovation.
They stressed that transformations in jobs and public policies depend fundamentally on human decisions.
Major Social Challenges
For his part, Professor Christopher Pissarides, Nobel Prize laureate in Economic Sciences (2010) and Professor at the London School of Economics, described artificial intelligence as part of the long historical trajectory of economic development.
The Impact on Jobs Is Subject to Human Choices
In his keynote address, Professor Pissarides emphasized that technological change does not eliminate jobs as much as it transforms them, noting that employment outcomes remain subject to human choices rather than technology alone.
Drawing a comparison with China’s economic transformation, which took decades, he cautioned against expectations that AI will deliver miraculous productivity gains in the short term.
He highlighted several challenges that could slow AI adoption, including the need for large-scale investments, energy infrastructure, communication networks, and workforce reskilling.
Professor Pissarides called on policymakers to invest now in infrastructure and energy sectors, urging scientists and workers alike to exercise patience and focus on AI technologies that enhance human effort instead of replacing it.
Accelerating Scientific Effort
Meanwhile, Professor Michael Levitt, Nobel Prize laureate in Chemistry (2013) and Professor of Structural Biology at Stanford University, focused on the impact of AI on scientific discovery, stressing that science is fundamentally driven by experimentation.
He noted that artificial intelligence enables scientists to explore a greater number of ideas and accelerates computational work by approximately 10,000 times, thanks to its ability to significantly reduce the cost and time required for experiments.
Professor Levitt added that differences and barriers related to scientific methodologies are rapidly diminishing, allowing researchers to work across multiple disciplines with unprecedented ease.
Collective Intelligence and Data Governance
In a keynote address on collective intelligence, Professor Michael Jordan, recipient of the Global Award for Leading Scientists (2022) and Professor at the University of California, Berkeley, described modern AI systems as large-scale technological social networks rather than isolated tools.
According to Professor Jordan, AI enables users to interact effectively with accumulated human knowledge. These systems now form the backbone of sectors such as logistics, healthcare, and transportation, raising critical questions around data flows, incentives, and governance.
He warned that while foundation models excel at leveraging prior knowledge, they do not demonstrate the same efficiency when it comes to new scientific discoveries.
Warnings on Control and Misinformation
In the closing keynote, Professor Whitfield Diffie, Turing Award laureate (2015) and consulting researcher at Stanford University’s Center for International Security and Cooperation, addressed concerns related to AI control.
He noted that society will continue to adopt AI technologies, while warning against imposing strict constraints and safeguards that grant AI broad authority within systems lacking transparency.
During a panel discussion moderated by Professor Cohen, scientists explored both the benefits and risks of artificial intelligence.
Dr. Kaishen Dong, Associate Professor at Tsinghua University, highlighted AI’s potential to accelerate education and research, while cautioning against students’ overreliance on the technology.
Meanwhile, Dr. Stuart Haber, President of Stuart Haber Crypto, described the spread of deepfake videos as a major threat to shared truth, calling for international cooperation and the use of cryptographic tools for verification to protect information integrity.
