But these kinds of problems are accumulating: pandemics, climate change, resistance to antibiotics, food security, cybersecurity challenges, shared economic prosperity, etc. It’s urgent that we change our traditional approach to science.

For centuries, we have conceived science in a linear fashion: a problem gives rise to a hypothesis, followed by a model and a test. If the result is a failure, the process starts all over again, and testing can take years. With this method we have come a long way, developing better plastics, more efficient solar panels, and lighter and stronger materials for aircraft, for example.

Science has no limits for creative scientists

The world is changing rapidly, and to meet today’s global challenges as quickly and effectively as they arise, we need a new way of doing science.

Science is an inherently creative process, as scientists are constantly stretching their imagination to explore new drugs and chemical product designs. But the human brain has its limits. After all, there are more possible designs for a molecule than there are atoms in the universe.

The good news is that we have the ingredients to push science, and the limits of our brains: cutting-edge computer technology and talent. The real challenge is to apply them strategically, in both the public and private sectors.

What superpowers of innovation does Artificial Intelligence give us?

The world is witnessing a revolution in computing. Artificial Intelligence (AI) is enhancing traditional computing and could soon power emerging quantum computing , with machines that could enable us to solve some of the world’s biggest problems. They could be accessed from anywhere on the planet through a Hybrid Cloud.

A growing number of companies and laboratories are using AI, whose deep neural networks are capable of extracting scientific knowledge at scale from all the scientific papers published on a given topic.

Let’s say a scientist needs to create a new catalyst to improve artificial fertilisers. Rather than blindly trying to determine the chemical structure of the catalyst, the AI would first examine a multitude of patents, academic papers and other publications to see what has already been done on this topic.

The AI would then automatically generate hypotheses based on the data found, to expand the search for new molecular designs.

Based on the most promising hypothesis, high-performance and quantum computers would simulate a new molecule.

Once the digital work was done, the simulation would be confirmed or refuted in increasingly autonomous laboratory tests. Finally, the AI would evaluate the result, identify anomalies and extract new knowledge. New questions would arise, and the process would continue.

Mix in a pipette: AI + Hybrid Cloud + quantum computing + new discovery communities = an accelerated scientific method.

To change the paradigm of scientific discovery, we need AI, the Hybrid Cloud and, eventually, quantum computing to converge. We also need a second ingredient: new types of scientific collaboration or “communities of discovery” to be added to the mix.

What would we gain?

An accelerated scientific method, capable of catalysing major transformations in science, and with unprecedented speed and automation. We could design new materials faster than ever before, which would have an impact on every aspect of our lives, from healthcare, to manufacturing, agriculture, and other fields.

Credit: IBM Research

For the first time, closing the circle of scientific discovery seems a very real and imminent possibility. When this happens, we will have achieved a dream: scientific progress will be a self-driven, never-ending process.

New scientific communities no longer have limits

But it’s not only technology that will drive this new level of discovery; so will people. The world is teeming with millions of talented and creative scientists spread across academia and industry, who shouldn’t be tackling the many global crises they face independently. In fact, no single company or university laboratory can overcome a pandemic on its own.

National and international public-private partnerships share knowledge, data and the latest technology, accelerating the discovery process.

They must also be diverse. In science, problems can be large and complex, or small and more specific. For example, the CERN (European Organisation for Nuclear Research) requires a thoroughly coordinated community of scientists from 42 countries to carry out around two million experiments per day at some 170 laboratories, and that’s just for the science coming from the particle accelerator: the Large Hadron Collider.

However, science is becoming more open and researchers in the public and private sectors are, increasingly, sharing papers, experiments, data, results and resources.

A successful example of this new smaller discovery community is the COVID-19 High Performance Computing Consortium.

This collaborative effort between 87 partners from academia, industry and national laboratories has given researchers around the world fighting the current pandemic access to supercomputers.

Unity makes science

Industry partners are often rivals, but not now, with the goal of creating a coronavirus vaccine. All members of the Consortium are united by a common goal: to accelerate the search for a new treatment or vaccine against COVID-19. This collaboration allows for greater speed and accuracy, freer exchanges of ideas and data, and full access to cutting-edge technology. In short, innovation is enhanced, and the pandemic will, hopefully, be halted faster than would otherwise have been possible.

The limit is not in the design of materials.

With the continued evolution of data-driven AI, advanced Hybrid Cloud computing, progress in quantum computing, and growing discovery communities, the updated and self-driven continuous scientific method should have a major impact on multiple aspects of our lives. And, given all the present and future global crises that we face, the need for it has never been greater.