AI, digital technology is changing innovation landscape

The rise of technologies such as artificial intelligence or AI, data analytics and other digital technologies is changing the innovation landscape in a way that is more conducive to university-industry research and development collaborations than in the past, according to Tan Chorh Chuan, outgoing president of the National University of Singapore.

In addition, universities themselves are changing the direction of research to create greater translational impact from their highly intellectual research.

Speaking at the 14th annual lecture of the Higher Education Policy Institute, held at London’s Royal Society, on the perspective from Asia of major shifts in global higher education, Tan said “the landscape is changing because industry is shifting now to much more open innovation approaches to welcome universities, to identify and recruit in turn from universities and to insource intellectual property from the universities”.

“At the same time, universities are responding to this, understanding the opportunities that it creates. Many more universities are embracing innovation enterprise as core to their missions,” he said in his lecture organised by the Higher Education Policy Institute, a United Kingdom education think tank.

Traditionally, a number of mismatches impeded close partnerships between universities and industry in research and development, including the research timeframe, types of incentives and differences in research culture – academics “like the freedom to explore the space to discover new things whereas industry is about timelines, schedules and deliverables”, Tan said.

But he noted that changes in the innovation landscape mean there is now “better alignment between the incentives and timeframes for research, and translation within universities”, which makes it easier for them to work together.

In several countries, including Singapore, the government is providing incentives to encourage universities and industry to work together in R&D in a more substantive manner.

Universities usually produce research of higher intellectual value but relatively lower translational or commercial value, but in recent years in several fields, such as software development, artificial intelligence and data analytics, the time and the barriers to move from high-quality basic science discovery to something with commercial impact have become dramatically reduced.

“As a result many more universities are now moving into these areas because they represent a sweet spot between academic value and translational value,” Tan said.

The example of China

China is a case in point with rapidly increasing investments in R&D. Much of it in the past has been spent on applied research, with less than 5% of R&D spending spent on basic research in 2013, Tan noted. Now China is moving away from the short-term and focused technological R&D, that, for example, delivered new turbine engines, high-speed trains, solar panels or drugs in 5 to 10 years.

It is now taking a longer and broader view which Tan described as representing “a very fundamental change in thinking”, moving towards more high impact academic work. “This is a very long-term strategic view of R&D which I think is very impressive."

The likelihood is that in some areas such as artificial intelligence and data analytics, where China is making massive investments and also has access to huge amounts of data which is crucial for AI systems, China may “move straight into a situation where it is creating work of a high academic value as well as commercial impact”, Tan said.

Tan pointed to Tsinghua University in Beijing whose research budget in 2016 was US$750 million. Ten years before, it was only one-third that amount. Its subsidiary, Tsinghua Holdings, is investing US$7.6 billion to support 500 start-ups with a value of about US$18 million, and aspires to set up 1,000 incubators across China.

Within China “Tsinghua is not unique in this respect”, said Tan, and within Asia it is also not confined to China. In South Korea, both Korea Advanced Institute of Science and Technology or KAIST and Seoul National University are rated regularly among the top most innovative universities in the Asia-Pacific. India is planning to set up seven new research parks and hoping to use its Indian Institutes of Technology to drive industry-academic R&D innovation, he noted.

Other even more fundamental trends “are fuelling this push, this huge momentum of universities growing innovation ecosystems”, he said, with new technology and new business models allowing individuals or small business groups with good ideas to grow them into businesses which can be scaled up, not just at a local but at a regional level as well.

In addition, rapid economic growth in Asia is creating “excellent conditions for universities to develop education, research and entrepreneurial programmes that ride on these opportunities and also offer solutions to tackle some of the very serious challenges that this rapid growth is also creating”, he said.