If you want to see the future of artificial intelligence, you don’t need to head to Silicon Valley’s tech titans – just walk on to a university campus.
Many of the most exciting developments in AI are embedded in and around research-intensive universities. They are a prime source of talent, discovery and innovation. This bodes well for the future of a field that will be shaped by a vast array of startups, academic researchers and students, and not just a handful of corporate giants.
This diverse set of players, where universities play a central role, may allow AI to avoid some of the pitfalls that have afflicted internet technologies. Just weeks before Mark Zuckerberg acknowledged Facebook’s role in the Cambridge Analytica scandal, World Wide Web inventor Tim Berners-Lee bemoaned the “concentration of power [that] creates a new set of gatekeepers, allowing a handful of platforms to control which ideas and opinions are seen and shared” on the web. Universities are helping preserve this diversity in AI.
We’ve already begun to see the potential for AI to dramatically transform society – and how universities work. Machine learning techniques are paving the way for faster diagnosis of disease, improved understanding of human behaviour, and better protection against cyber-attacks. AI systems have also been helping us to make scientific discoveries: formulating hypotheses, designing and running experiments, analysing data, and deciding which experiments to run next.
At the same time, barely a day goes by without warnings about the potential for robots to make human workers redundant – from factory workers and accountants to journalists, professors and Go masters – creating perceptions of an almost existential threat to our way of life.
While the dystopian vision painted by Blade Runner captures the imagination, the reality is more complicated, nuanced – and hopeful.
AI is most effective when it works collaboratively with humans. When we play to our strengths, we can achieve things that would have been impossible for either computers or humans separately. Machines don’t know what they don’t know, and they don’t know how to interact with humans. That’s why the best applications of AI combine human judgment and empathy with the speed and efficiency of computers.
More than that, as AI changes so many parts of our economy and society, it is vital that these transformations are driven by a diverse community of innovators.
Universities are, and must remain, central to this. They are home to world-leading academic talent, bright and creative students, and innovative startup companies. They are uniquely placed to develop AI ecosystems like those emerging in London, Pittsburgh and Shenzhen.
In my own university, Imperial College London, the Enterprise Lab gives student and research-led startups the support and space to test out their ideas, develop their fledgling businesses and, crucially, to pivot as they find their niche.
One student, Pae Natwilai, developed a ‘magic wand’ to control drones and other robots by pointing where you want them to go. It seamlessly brings together human and AI controls to these semi-autonomous robots.
Pae initially thought that the technology could work as a toy, but, with the support of Imperial’s WE Innovate program for women entrepreneurs, she realised that her innovation could have much stronger applications in industry. Few corporate R&D centres can be as nimble as Pae was, as her academic environment supported her pivot.
Her startup, Trik, is now using this technology to develop an autonomous drones system for structural inspection, providing a safer, cheaper, and faster way to check for damage or defects to large structures such as oil rigs, bridges, or multi-storey buildings.
AI innovations that spring from universities are often driven by societal benefit rather than a profit motive. This year’s WE Innovate finalist, postgraduate Charlotte McIntyre, is developing a machine learning technique to predict the likelihood of a patient developing thyroid cancer, by analysing ultrasound scans, needle biopsies and medical history at great speed and accuracy. Of course, the machines have great limitations, but human-AI collaborations can greatly enhance healthcare outcomes.
My own team worked with disaster recovery charity Rescue Global following the Nepal earthquake. By combining trusted human observations with AI analysis of the huge amount of data flooding in we were able to determine the best placement of water filters around Kathmandu, reducing the risk to many thousands of endangered people.
Tech giants recognize the creativity within this ecosystem. It is in their interest, as well as wider society’s, to preserve it. From Imperial College alone, we’ve seen virtual reality start-up Surreal Vision snapped up by Facebook’s Oculus, audio detection start-up, Sonalytic bought by Spotify, and machine learning image recognition firm, Magic Pony acquired by Twitter. It is doubtful whether these innovations could have emerged from in-house R&D. The university was indispensable.
This plural wave of innovation has nimble start-ups, academics and tech giants driving change. The AI revolution is set to keep benefiting society as a whole. Universities must remain at its heart.