Long Read

The Geopolitics of Innovation Revisited

Innovation is the primary driver of real-world economic growth, social development and productivity. The future revolves around competition for ideas. Calls for radical, systemic innovation to address climate change, the collapse of the biosphere and pollution grow louder. Fears about how robots and artificial intelligence (AI) will create long-term unemployment shape election outcomes and in turn international politics.

Yet this largely secret world is hidden from public attention and mainstream policy making. The financial markets have a similar blind spot, so forecasts underestimate radical change.

The rise and rise of intangibles and weak signals that suggest we may see the emergence of machines as inventors foreshadow volatility and radical change. On the horizon, a marketplace of ideas based on openness and codified knowledge-sharing, patent exchange and machine creativity. In this scenario, systemic innovation will drive structural disruption across all industry sectors and asset classes.

There is a darker side: a battle for supremacy, a culture of rivalry, conflict, theft and mass-scale replication, cyberwar and challenges to national pride. Political leaders are rarely visionary innovators. Lack of imagination turns them to basic instincts, driven by fear: protectionism, isolation and illusions of self-sufficiency.

This essay extends an earlier version, written in June 2017, that foreshadowed the current US-China trade wars. Beneath the surface, these tensions are about ideas, intellectual property, patents and technology transfer. As Mat Burrows put it in “A Chinese Sputnik Moment for the West?” in December 2017: “the speed with which China is catching up and potentially surpassing the West is no longer hypothetical”.

1   Innovation is Political

Picture this: over the next two decades systemic, accelerating and radical innovation will bring growth and new sources of wealth, contrary to the argument that the age of fundamental change has ended. Yet with this, we will see deepening inequality and high levels of unemployment. With that, a surge in economic nationalism and battles to dominate emerging technology sectors. The collaborative, largely open exchange of ideas and technology may give way not to a cold war, or a trade war, but a war for ideas and talent.

In another scenario, entirely novel forms of environmentally sustainable and socially inclusive innovation will change the trajectory: a new moral economy will emerge, focused on long-term social well-being and quality of life. Climate change may yet create a new form of shared political and inventive purpose. Above all, the ‘sustainability economy’ has the potential to create new jobs.

However these scenarios may play out, the fact is that innovation is moving faster than ever.  The structural fault line is that political leaders are slow to anticipate and adapt, let alone shape future outcomes by supporting positive innovation and regulating against potential strategic risks. In a speed-dominated media and political environment, short-termism wins over long-term thinking.

The globalisation narrative, together with the corporate, institutional and financial frameworks that support it, stands charged of failing to deliver broad benefits around the world. Unless national leaders learn how to act early to forestall the impact of disruptive technological change long before events overwhelm them, then social chaos and revolution may be inevitable. The more disruptive the innovation, the greater the risks.

The fundamental uncertainty is whether political and social systems, at all levels, can adapt not only to potential global and climate catastrophes, but to runaway technological change.  The present-day reality is that overstressed social systems are ill-equipped to deal with increasingly chaotic conditions, as events in Europe, the US and the Middle East illustrate.  Entire communities are not only left behind but lack the mobility to shift direction and adapt.

There are clear signs that many people, not only in the West, are experiencing anxiety and a sense of helplessness about the unknown, climate-ravaged, technology-driven future.

Meantime, the transparency and immediacy of global media networks is not only technologically disruptive in itself, but intensifies the emotional impact on people’s lives, bringing a continuous flow of world events to everyone.  This has fundamentally changed cultural and political landscapes over the last two decades, breaking down boundaries between national and local communities and threatening local social cohesion.

The strategic, long-term challenge to political, corporate and institutional leaders is clear: create a sense of hope and stability in a period of turbulence and structural change. Time will tell whether the challenge is beyond them.

2   Secret Worlds: why forecasters fail

Politicians are not alone in facing the complex uncertainties associated with climate, technological and social disruption.  The potential impact of systemic innovation, in particular, is understated in financial market forecasting.

Analysts are typically silent on the broad potential influence of disruptive ideas, in part because they are not yet articulated, or even imagined.  Ideas belong to a secret world.  Why secret?  Inventors in small firms and corporates alike protect big ideas with their lives.

Innovation is also understated because, at a macro level, systemic innovation is non-linear.  Open, highly networked innovation has emergent properties and so is inherently unpredictable.  It is difficult to estimate outcomes, even when patterns become clear.  Whilst combinatorial patents are ballooning, as often disparate inventions are brought together, the linkages are not obvious.  This largely hidden world drives what Paul Romer calls ‘compounding’ and suggests that faced with uncertainty, the more pessimistic forecasts lack imagination:

“Only a failure of imagination—the same failure that lets people think that all the big ideas have already been discovered—could convince us that with our current institutions of science, we have already found the best of all possible systems for encouraging the production and distribution of new ideas.  There is surely room for improvement. Improvement might increase the rate of growth by a little bit.  The benefits that follow will accumulate faster than people realize.”^[1]

Many inventions are latent in the ‘white space’ of new markets targeted by the most sophisticated corporates and by leading edge sovereign funds. White space is usually defined as an area at the intersection of technologies and markets where the products or patent coverage is weak or non-existent, but commercially valuable.  Inventing in white space is about creating new paradigms and market leadership. It promises high margins and sustainable differentiation.  In contrast, innovation hot spots are overcrowded, with many overlapping and competing claims, patent ‘clusters’ and ’thickets’ that ultimately mean low returns.

The secret world is a primary source of weak signals – the ambiguous, often outlandish competing ideas that too often are met with ‘it will never work’ and an array of similar objections.

The conundrum then, at first sight, is simple: how to forecast the future value and risks associated with innovation as the world becomes more interconnected, complex, fast moving and more uncertain.

3  Emerging Driving Forces

There are many competing and conflicting innovation philosophies at work. All have cultural and political roots.  In simple terms, the tension is between ‘open innovation’ and commercial and international competition. Yet this is not a straightforward dichotomy: the future innovation landscape will most likely be diverse, heterogeneous and itself the result of Schumpeter-style ‘creative destruction’.

Open Innovation

Some open innovation examples like the ‘open data’ movement are obvious.  Many national governments are making public sector information available to encourage public interest innovation, in everything from food standards, to security and crisis management. At the same time, governments are promoting open and freely available, publicly-funded research.

Open innovation is pervasive in the private sector, in part inspired by the ‘public good’ idea that inventions belong to society as a whole.  As a student, Perry Alagappan invented a water purifier, designed to deal with toxic ‘e-waste’. In the past it would have been patented, but it was gifted to the world.^[2] The Creative Commons movement, essentially a means by which intellectual property can be shared openly, with simple rules of attribution, has become mainstream.

There is also growing evidence that philanthropists are focusing on long-term grand challenges and seeding global innovation by gifting inventions to the public.  Elon Musk’s artificial intelligence initiative, OpenAI, has lost some of its early idealism and altruism by creating a ‘capped’ commercial and business model to attract investment, but its ambitions to bring the benefits of AI to all remain. A growing number of inventive academic researchers are backed by foundations that support a key principle: inventions are free to use, even if they are patented.

In parallel, ‘mass innovation’, illustrated in part by ‘maker culture’, brings 3D manufacturing designs to open networks via the web for local production, assembly and distribution.  This is taking hold as one of many examples of grass roots ‘mass flourishing’.^[3]  Maker culture, within which open innovation is central, echoes ‘garage inventors’ in the US and took off at large scale in China, is moving from the margins to the mainstream.

Yet this disguises one of the fundamental structural problems: Roberto Unger, author of The Knowledge Economy, said in a recent interview that “The advanced practice of production, rather than deepening or spreading, is confined to insular vanguards that exclude the vast majority of businesses and workers”.^[4]

We might substitute ‘innovation’ for ‘production’. In this context, the current patent, intellectual property and innovation systems favour major companies and elite groups with the resources and expertise to understand the risks of theft in sharing ideas; the importance of prior art; and ‘patient capital’ for taking promising ideas through to production. It rewards specialists and promotes rent-seeking behaviour amongst investors. It also favours developed countries and inhibits cross-border, global trade in ideas.

From another perspective, technological innovation will follow an inexorable path, regardless of social outcomes.  Manufacturing businesses, for example, will face the convergence of 3D printers, artificial intelligence and robotics forcing them, for competitive reasons, to substitute machines for labour, likely leading to what Tyler Cowen has called ‘radical onshoring’.

This will put pressure on the West, but will also lead to early de-industrialisation and large-scale unemployment worldwide.  The signs were clear three or four years ago: Asian textile and footwear manufacturing businesses began switching rapidly to low cost robotics, particularly to China.  According to International Labour Organisation, this threatens millions of jobs over the next decade.^[5]

Over the long-term, we can expect manufacturing to become increasingly localised, using remote 3D techniques to produce everything from volume consumer and household goods to food.  This will cut demand for international transport. Instant copying and the global distribution of ideas via digital ‘Apps’ will decentralise production. Why ship around the world if low cost production is just across town, everywhere?  Replication, already pervasive, will become the norm.

Patents and Commercialisation: on the rise

Open sharing of ideas has exploded, but the instinct to hoard, protect and commercialise via patents is following a similar pattern. This is partly reflected in the rapid increase in new patent filings. Measured by the World Intellectual Property Organisation (WIPO), PCT applications rose by 3.9% in 2018 over 2017. China’s filings increased by 9.1%to 53,345, just short of the US total of 56,142. Huawei alone filed 5,405 patents. Japan was third, rising 3.1% to 49,702. There was significant growth from India and South Korea. According to WIPO’s director general:

“Asia is now the majority filer of international patent applications via WIPO, which is an important milestone for that economically dynamic region and underscores the historical geographical shift of innovative activity from West to East.”

This shows that the geography of innovation is changing quickly, with China set to become the world’s largest investor in both R&D and in patent protection by 2020.  Trademark applications showed similar growth.

Though there is a caution that patent applications numbers are only one way of looking at growth, performance and future value and quality is more decisive, patents remain an important broad indicator. Headline numbers tend to cloud more important underlying trends: there is continued growth in investment in digital technology, but growth in energy-related patents has stagnated and declined, after almost doubling between 2005 and 2013. Whilst invention in nuclear and renewables has slowed, inventions in energy conservation and green transport has continued growing.

For all the concerns that surround trolling and failings in the global system, they are a primary means by which to protect commercial returns.  Research in the US found that the ‘patent premium’ averages 50% over ‘no patenting’, ranging from 60% in health-related industries to 40% in electronics’.^[6]   Global small business patent filing, venture funding, corporate open innovation and off-balance sheet R&D continues to rise, despite the challenges.

Hybrids

Hybrid approaches, such as, ‘patent pooling’ and collaborative cross-licensing are long established in digital technology manufacturing and will grow rapidly in all sectors.  They are particularly important in areas such as sustainable development, where there is a strong public-good argument.

Similarly, in healthcare, novel methods will be designed to further social benefits, rather than necessarily drive profit.  This is critical in structural terms, because of the scale of the challenges facing national governments in dealing with aging populations

For example, Shinya Yamanaka of Kyoto University, Japan who won a Nobel Prize for his work on induced pluripotent stem cell technology,^[7] adopted an open, non-exclusive patent licensing approach that aims to protect the core IP but maximise public benefits. The design approach is to avoid the core IP falling into the wrong hands and at the same time to encourage large-scale collaboration in spin-off application development.

We can expect social entrepreneurs to take a similar route: invent, file patents and distribute free to the world to prevent commercial interests developing so-called derivative works and capturing consumer relationships and markets. Patents do not necessarily equate to commercialisation.  The idea of the moral economy may re-emerge in new forms, particularly as the sustainability agenda gains momentum.

Over the long term, the contest between the cultures of hoarding and openness will intensify.  The pressure to find socially and economically coherent models will increase.

Meantime, some technologies have potential for good, yet are unlikely to form part of the true open innovation culture, given the uncertainties and risks associated with widespread distribution and potential misuse.

Once again, innovation is political.

Take two examples.  First, the scenario of true machine intelligence, of runaway ‘superintelligence’ envisioned by Nick Bostrom, which has already created widespread fear, even amongst AI researchers.  Self-replicating systems may not only make humans irrelevant but create existential risk.

None of this compares with the convergence of digital systems and knowledge engineering with synthetic biology and artificial life.  This may be the next phase, as imagined by Craig Venter, by which vaccines to deal with disease outbreaks, for example, are designed and tested, then released via a new kind of ‘App’ store for local manufacture.  Once again, there are many positive applications, but more important, potential risks.

4   The Marketplace of Ideas

Taken together, the future dynamics of innovation, distinct from the inventions themselves, can be simplified in the form of two interrelated variables, from which several scenarios emerge.

The first is the degree to which ideas, knowledge and information is codified and categorised, at one extreme making the diffusion of ideas simpler and more effective and at the other, ideas remain uncodified and tacit, constraining collaboration and distribution.^[8]

The second is whether ideas and intellectual capital are hoarded, at one extreme, or openly distributed.  If they are hoarded and protected in the form of trade secrets, know-how and patents, at the extreme fragmentation, isolationism and protectionism will develop.  Intellectual property may be expensive and dominated by commercial or national interests.  At the other extreme, it may be openly distributed, in the spirit of the ‘open data’ and ‘open innovation’ culture.

One particularly important scenario may take shape, amongst many: a true open marketplace of ideas, in which intellectual capital is codified and openly distributed, or traded within an exchange system, either free of IP conditions as part of a ‘gift’ culture, or ‘securitised’ in the form of tradable instruments and licenses.  New technologies, such as Blockchain, may play a central role.

In this scenario the disruptive impact of open innovation will produce novel structures.

In a world dominated by intangibles, where products ranging from cars to access fees to large-scale computing power are provided as services, a new system of political economy will emerge.  The early signs are already there, with Microsoft, Google, IBM and Amazon, amongst many others, creating infrastructure and AI ‘on demand’, for rental fees.

This will accelerate the evolution of not only machine-driven innovation systems, but human structures and global interaction in the form of ‘social machines’, increasing pressure on social adaptive capacity and increasing levels of uncertainty.

If the marketplace, combined with computational creativity, leads to runaway machine intelligence, the impact on social systems will increase further.

5   Hotspots and White Space

Against this background, the challenge facing national governments, business and city leaders, and investors alike is how to rise to the growing challenges, not only of climate induced change and technological innovation, but to the broader structural risks and opportunities that are beginning to emerge.

The prerequisite is to navigate the emerging secret worlds, developing intelligence about early stage ideas.

Given the lag between invention and commercialisation, intellectual property landscapes – networks of ideas maps – have strategic value, since patterns of ideas give vital early indications of the shape and structure of industrial, product and economic revolutions well before commercial products and services emerge.  They are the source of important known unknowns – predictable surprises.  They also highlight network linkages that point to emerging systemic innovation – ‘hot spots’ where there is intense activity.

Yet it is only the first step.  Armed with pictures of the IP network, the second step challenges convention from a commercial perspective: invent in ‘white space’.  The principle is to avoid inventing in hot spots: search and invent precisely in the gaps. Leading inventors are white space specialists.

This is where we can expect entrepreneurial investors and specialist fund managers to look for exceptional returns.  After all, many of the most successful products, services and businesses are based on inventions in white space.

Entrepreneurial, private office investors; sovereign wealth funds; specialist industry funds; private equity; venture capital are all searching for big ideas.  Corporate venture funds, driven more than ever by competition to innovate, are outsourcing invention; taking more risks; investing for strategic reasons, rather than short-term financial returns; and investing early.  To illustrate, corporate venture investment as a proportion of total venture funding grew to 9% by 2015, with the US showing a compound annual growth rate of 39% between 2010 and 2015, according to Bain.  In China, corporate venture reached 5% of the total. Since then, corporate venturing has focused less on financial returns, but strategic investment that brings access to new technology and to source of innovative ideas.

6   Creativity Reinvented: the rise of the machines?

Innovation is not simply a business issue or the primary challenge to entrepreneurial investors looking for the next big idea, but for government leaders, who to avoid the maelstrom ahead, must learn how to act on foresight, actively driving invention and creating home-grown versions of the ‘Entrepreneurial State’.^[9]

The missing ingredient in all present narratives is the nature of creativity and invention itself.  This, like everything else, is changing at an ever-increasing rate.  What is known as ‘Computational creativity’ may soon emerge to stretch adaptive capacity more than ever.

This has the potential to boost the rate of innovation, shifting the focus from research to origination, as ‘general purpose learning machines’, hinted at by Deep Mind’s ‘Alpha Go’, evolve from problem solving systems to delivering novelty.  Alpha Go surprised experts not because it produced results a decade ahead of forecasts, but because there were hints at ‘intuition’, one of the defining characteristics of human creativity.

If Alpha Go showed signs of intuition, then the fourth of the so-called ‘Lovelace’ questions, quoted by a pioneer of computational creativity Margaret Boden as long ago as 1990, may be answered as ‘yes’.^[10] As Wired put it:

“From where Lee sat, AlphaGo displayed what Go players might describe as intuition, the ability to play a beautiful game not just like a person but in a way no person could.”^[11]

The Deep Mind system used deep neural reinforcement learning from human experts (similar in principle to how animals learn using dopamine reward mechanisms), together with value networks and techniques that incorporate long term planning and ‘look ahead’ search. ^[12]More recently, Deep Mind’s Generative Query Network visualisation technology can ‘imagine previously unobserved scenes’ and measure levels of uncertainty. These technologies are classic ‘weak signals’, with potentially wide-ranging potential applications. It is no coincidence that Demis Hassabis researched the neuroscience of futures thinking before founding Deep Mind.

Maurice Saatchi reportedly said that ‘Creativity is the last legal way to gain an unfair advantage’.

Machines are about to change the formula.  Vast knowledge bases that underpin invention may shift power from man to machine, from labour to capital, increasing the competitive advantage of large-scale AI-centric firms.  Alternatively, it may follow Elon Musk’s vision, promoting his argument for OpenAI:

“I think the best defense against the misuse of AI is to empower as many people as possible to have AI. If everyone has AI powers, then there’s not any one person or a small set of individuals who can have AI superpower.”

Big data, open information and more recently open innovation have been primary drivers of the knowledge economy.  Computational methods may now move centre stage and drive the development of a new creative age.  We may soon see innovation itself and globalisation transformed: an open, networked marketplace of ideas, with everything from food production to advanced manufacturing becoming part of vast, distributed network systems.

In the darker scenario, the complex relationships between ideas, patents, productivity, economic growth and national security may break the vital, collaborative linkages that have underpinned global growth for decades. An important lesson may have to be relearned: complex interdependence leaves systems fragile and vulnerable to shocks. The myriad components that make up modern communications technologies rely on cross-licensing, knowledge sharing and mutual trust. The US-China trade wars may yet set off a chain of systemic events that few have foreseen.

Peter Kingsley
May 2019

Footnotes

1. https://paulromer.net/category/blog/ ↑
2. http://www.theguardian.com/sustainable-business/2015/aug/27/texas-teenager-water-purifier-toxic-e-waste-pollution? ↑
3. Edmund Phelps, Mass Flourishing: How Grassroots Innovation Created Jobs, Challenge and Change. ↑
4. RSA Journal, Issue 1, 2019 ↑
5. https://www.ilo.org/wcmsp5/groups/public/—dgreports/—inst/documents/publication/wcms_648063.pdf ↑
6. Source: Carnegie Mellon University, Georgia Institute of Technology, and Duke University, R&D and the Patent Premium. ↑
7. http://www.wipo.int/wipo_magazine/en/2015/04/article_0002.html ↑
8. This model is based on Max Boisot’s ‘I-Space’, one example of which is explained in The I-Space: a framework for analyzing the evolution of social computing by Boisot and Benita Cox.
9. https://marianamazzucato.com/entrepreneurial-state/
10. Margaret Boden, The Creative Mind.  The fourth Lovelace question is whether ‘computers themselves could ever really be creative (as opposed to merely producing apparently creative performance whose originality is wholly due to the human programmer).’
11. http://www.wired.com/2016/05/google-alpha-go-ai/ ↑
12. http://www.nature.com/nature/journal/v529/n7587/full/nature16961.html ↑