Modern civilisation is a miraculous feat, one made possible by science. Every time I take a flight, I marvel at the technology that has allowed us to soar above the clouds as a matter of routine. We have mapped the genome, built supercomputers and the internet, landed probes on comets, smashed atoms at near light speed in particle accelerators and put a man on the moon. How have we managed to do any of this? When one stops to contemplate what has been accomplished by our 3lb brains, it’s quite remarkable.
The scientific method might be the single most powerful idea humans have ever had, and progress since the Enlightenment has been simply astonishing. But we are now at a critical juncture where many of the systems we need to master are fiendishly complex, from climate change to macroeconomic issues to Alzheimer’s disease. Whether we can solve these challenges — and how fast we can get there — will affect the future wellbeing of billions of people and the environment we all live in.
The problem is that these challenges are so complex that even the world’s top scientists, clinicians and engineers can struggle to master all the intricacies necessary to make the breakthroughs required. It has been said that Leonardo da Vinci was perhaps the last person to have lived who understood the entire breadth of knowledge of their age. Since then we’ve had to specialise, and today it takes a lifetime to completely master even a single field such as astrophysics or quantum mechanics.
The systems we now seek to understand are underpinned by a vast amount of data, usually highly dynamic, non-linear and with emergent properties that make it incredibly hard to find the structure and connections to reveal the insights hidden therein. Kepler and Newton could write equations to describe the motion of planets and objects on Earth, but few of today’s problems can be reduced down to a simple set of elegant and compact formulae.
This is one of the greatest scientific challenges of our times. The founding fathers of the modern computer age — Alan Turing, John von Neumann, Claude Shannon — all understood the central importance of information theory, and today we have come to realise that almost everything can either be thought of or expressed in this paradigm. This is most evident in bioinformatics, where the genome is effectively a gigantic information coding schema. I believe that, one day, information will come to be viewed as being as fundamental as energy and matter.
At its core, intelligence can be viewed as a process that converts unstructured information into useful and actionable knowledge. The scientific promise of artificial intelligence (AI), to which I have devoted my life’s work, is that we may be able to synthesise, automate and optimise that process, using technology as a tool to help us acquire rapid new knowledge in fields that would remain intractable for humans unaided.
Today, working on AI has become…