Today, AI-activated progress provides generational progress in biology, transforms science and makes our ways safer.
But this is only the beginning.
If we fully benefit from this opportunity, we can initiate a new era with discovery – strengthen scientists across disciplines to solve challenges when first thought of insoluble at a speed when it was first considered impossible.
Therefore, as global decision makers and technology leaders go to the artificial intelligence – action meeting in Paris next week, our message to decision makers is clear: While AI has the potential to revolutionize science and deliver a significant benefit to people and communities, continued progress is not guaranteed – it will only be possible through immediate and sustained action from the private and public sectors.
The opportunity to promote science in the AI ​​era
AI has already begun to enable landmarks progress in science – with much more to come. It changes how we conduct scientific research, dramatically accelerate the scientific process (sometimes condensing hundreds or even thousands of years of traditional experimentation and research for a few months or days) and allows researchers to look at many things in new ways at the same time. AI also makes it possible for many more people to participate in research.
E.g. Alphafold alone has become access to 2.5 million researchers in 190 different countries. We have also made many of our landmarks, AI-driven advances in Connectomics, Pangenome, Weather, Materials Science and Climate Models that are widely available to researchers. All this creates a great moment of opportunities – offering concrete benefits to people on real world problems and driving economic growth.
But to realize this enormous potential for AI in science requires more than just technological breakthroughs; It requires overall effort to build the basis for continued progress.
Therefore, countries that want to lead here are to work together to establish infrastructure, investments and legal frameworks that support researchers, engineers and a culture of continuous innovation.
To give politicians immediate, action -oriented steps, today we release our political framework to build the future of science with AI.
The three in science in the AI ​​era:
- Infrastructure – Increase access to AI infrastructure. Most researchers do not need to train their own large AI model, but they need access to resources to fine-tune large models, run simulations to generate high quality data or train smaller AI models on their specialized data. And without an established infrastructure for AI-driven scientific research and development, they need to devote energy to coordinating calculation resources, data and model access and becoming skilled with AI tools that all detract from their core research activities. Therefore, it is imperative for governments to build up the infrastructure needed to manufacture AI-activated research tools and resources More available to More researchers in Several places. They can achieve this by creating National AI for Science Resource Centers, similar to the concept of US National AI Research Resource (NAIRR) that makes high-quality data, AI models calculate capacity, software and educational resources available for AI -research.
- Investing – Invest in the Science of AI. Pioneering scientific discoveries often require long -term commitment and sustained investments. Over the years, government financing has played a crucial role in supporting ambitious basic research efforts, encouraging collaboration between academia, industry and the public sector and attracting additional private (foreign or domestic) investments. Governments should create a list of priority areas to direct their funding and incentive research collaboration through public challenges aimed at solving the most pressing problems. New public-private partnerships and funding models can play an important role in promoting a thriving ecosystem and building a strong pool of scientific and technical talent.
- Innovation implementation of pro-science and pro-innovation legal framework. With Global AI competition that is accelerating, we need to support innovation while establishing a framework for high-risk applications. Regulatory uncertainty slows down innovation and creates barriers to researchers and private investors. To tackle this issue, governments should establish regulatory regimes for pro-innovation that supports responsible and reasonable use of data, flexible copyright frames and harmonized privacy legislation. Trade policies should support cross-border data flows, which improves the diversity of data needed for AI discoveries.
There are many more challenges out there for AI to solve and many ways for countries to work together to promote larger AI-led breakthroughs.
With the right political and investment frameworks, governments can help accelerate scientific progress by clearing the path for researchers to continue to deliver the kinds of breakthroughs that will provide a brighter future for people everywhere.