Innovation for Inclusive Growth

Symposium's blogs

This page aims to gather different views on the topics of discussion of the Symposium on Technology, Innovation and Inclusive growth, that will be held on 28-29 April 2016.

To submit your blogs, please send an email to inno4dev@oecd.org, indicating your name, position, institution and country.

 

The opinions expressed in this page are those of the blogs' authors and do not represent the views of the OECD or its member countries. 

Marco Annunziata,  Chief Economist and executive director of global market insight at General Electric Co.

New technologies are revolutionizing industry. Digitally driven productivity gains are unlocking growth potential across markets.  And these innovations are multiplying, spawned by the Industrial Internet: a convergence of digital and physical technologies, powered by cloud-based analytics.

Wind turbines can ‘talk’ to each other and react to a shift in wind patterns by adjusting the pitch of their blades in a coordinated manner. This maximizes the power output for the wind farm as a whole.

Digital innovations are set to transform the entire energy value chain, opening the way for distributed generation and storage and two-way flows of both energy and information. This will result in fewer outages, optimization of the fuel mix with greater reliance on renewables, and more cost-effective decisions by both consumers and producers. And these are just a few examples. Across industry, these innovations are enabling a shift to predictive, condition-based maintenance: fixing machines only when needed, and before they break. This results in dramatic reductions in unplanned downtime, lower costs, and greater efficiency.

How powerful are these innovations? Last year we estimated that GE’s industrial internet solutions offer our customers an average performance improvement of 20%. As the industrial internet scales throughout the economy, they will have a major impact on productivity growth.

Yet many still underestimate the growth opportunity this presents. While innovation is accelerating, in many advanced economies, productivity is actually slowing. What can explain this paradox?

First, digital innovations have just begun to spread to the industrial world—where they will translate in faster productivity growth. Second, subdued investment over the last few years has slowed the pace at which these innovations scale through the global industrial system.

To accelerate this transformation, industrial companies need to become digital-industrial companies, bolstering their digital know-how. Digital innovations require greater speed and flexibility. They require openness: as success depends on a mix of new abilities, no single company can succeed in isolation; ecosystems and networks are essential. Business models need to change.

Advanced manufacturing techniques, from 3D printing to a "digital thread" , will change the way we work. Advances in robotics, AI, and new portable and wearable devices will create a closer collaboration between humans and machines, augmenting the abilities of workers at all levels of the skills distribution. This can increase productivity and wages for most workers—not just data scientists and engineers—and help reduce income inequalities.

We have a lot of work to smooth this transition. Policies should focus on (1) bolstering education, raising the bar on science, technology, engineering and mathematics but also emphasizing problem-solving and creativity; a closer dialogue between schools and industry is needed; (2) promoting openness: these innovations rely on the free circulation of ideas, data, people and services; (3) designing smart social safety nets, to support workers temporarily displaced by new technologies and help them retrain for new opportunities.

A strong focus on human capital is the best way to unleash the full potential of this new wave of innovations.

Robert Atkinson, Founder and President of the Information Technology and Innovation Foundation (ITIF)

We hear almost daily on how the world is poised on the edge of a new industrial revolution, even greater in magnitude than the “industrial revolution.” Technologies from robotics to AI to nanotech will revolutionize economies, driving productivity like never before and, according to this narrative put at risk the very notion of employment for most workers. Time to keep calm and mind the gap. In other words, there is no evidence to suggest that these technologies will emerge upon us fully baked and ready to go anytime soon. There is no reason why the development of these technologies will not be like the development of all other technologies over the last 200 years: a gradual process of improvement and adoption. Most of the technologies people rave about today are far from ready for prime time, and that includes autonomous vehicles and quantum computing. For most of the emerging technologies in the news, much more work is needed to improve performance and bring down costs, to the point where they will be widely adopted.

If there is any risk for the future it will not be that we have too much innovation, too fast; it is that we will have too little, too slow. Global productivity rates since the financial crisis are close to record lows and show no signs of improving. And even if technologies come faster than I think they will, there is no reason to worry about job loss. Technology-driven productivity has never led to fewer jobs in the past. As the OECD has shown, if anything it leads to more. This is because the second-order effects from higher productivity (more spending from lower prices and higher wages) create jobs. So there is absolutely no reason to fear that new technologies are a threat to jobs. Nor are they a threat to inequality. There is plenty of evidence that technology has not been the driver of inequality. The threat, to the extent there is one, is from inadequate policies to smooth adjustment in the labor market as individuals shift from one job or occupation to another.

So the implications for policy are clear: if nations want increased economic opportunity for all their citizens they need a national tech-driven productivity strategy. And this strategy needs to go far beyond the conventional nostrums of just getting market conditions and factor inputs right. If nations are to effectively drive productivity growth they need to embrace an array of policies focused on driving productivity by all organizations, particularly polices focused on remedying market failures at the firm level; developing R&D strategies to support productivity-supporting innovations and working to drive the adoption of a wide range of platform technology systems, such as Internet of Things. 

Finally, when it comes to making sure that growth is inclusive, the most important thing government can do is to drive productivity growth, for without growth it will be impossible to raise incomes. At the same time governments should work to help support innovations that automate low-wage jobs, for it will be impossible to raise incomes for low-wage workers unless nations can shrink low-wage occupations. Finally, all this needs to be coupled with robust training and labor adjustment policies so that workers can move to growing, higher paid sectors. 

Jennifer Blanke, Chief Economist at the World Economic Forum

Nearly a decade on from the financial crisis, the global economy remains sluggish and productivity is stagnating. At all income levels, many countries have experienced rising or persistently high inequality. At the same time, radical changes unleashed by new digital, robotic and AI technologies, are transforming what we produce and do, how and where we do it and how we earn a living.

Historically, such changes have been good for productivity growth, because workers can do more with less. Yet the likely size of the impact is debated. According to “techno pessimists” most transformations have already manifested themselves – the productivity gains are almost over. On the other hand, “techno optimists” believe that the world has reached an inflection point that will soon generate faster growth and productivity. The dispute is largely due to the fact that measuring the impact of technology is so hard, New technologies and business models of companies like Uber and AirBnB are not fully accounted for in calculations of GDP. We are increasingly producing and consuming much more value than our economic indicators tell us.

And while discussions of productivity and measurement remain somewhat theoretical, nothing can be more concrete than the impact on what is arguably most fundamental to our sense of economic worth: gainful employment. New products and processes can simultaneously open up sources of growth and displace workers. And this is no longer just about repetitive factory jobs: computing and robotics now threaten professions that had seemed “safe territory”, such as accountants, taxi drivers and paralegals.

New technologies will create jobs we haven’t even thought of. The main question in the meantime is how long this disruption will last and how far it will go. A recent study estimated that nearly half of total employment in the US is at risk, over the next decade or two. One can expect that low-skill activities will be progressively replaced by higher skilled ones. This will exacerbate inequality and as this happens social tensions will rise.

Given that the dislocation will be significant and that the transition between the old and the new jobs will take time, what can be done to foster better outcomes and support those caught in the transition? One response is to adapt educational systems to anticipate future knowledge and skills requirements. It could also be that the time for a universal basic income has come. More broadly, economies will need to ensure a much more inclusive growth process if they are to provide sustained improvements in living standards for citizens.

In an effort to better understand these issues, the World Economic Forum recently released the first edition of The Inclusive Growth and Development Report. This presents a framework for thinking about specific policy areas that drive social participation in the process and benefits of economic growth. There is a wide spectrum of policy levers that can foster growth and social inclusion at the same time.

These include responses frequently discussed, such as progressive redistribution and education, but also some that feature less often. Entrepreneurship, access to finance for real economy investment, good basic services and lack of corruption are just as critical to a country’s success in advancing living standards and ensuring productive employment. The framework shows that although technology has negative effects, in many ways it is making the growth process more inclusive. For example, mobile banking has brought into the financial system so many who were previously excluded. Similarly, new technologies enable adaptive and inclusive learning – in and out of the classroom.

Technology is a double edged sword when it comes to inclusive growth, at least in the short to medium term. By taking a holistic approach to how economies can generate inclusive growth, technology can be effectively harnessed for the good and help to mitigate the downsides.

Jacques Bughin, Director, McKinsey Global Institute

 

How will disruptive tech affect growth?

In the long run, prosperity depends on total factor productivity growth, the combination of forces that shifts the “frontier” into a higher gear of production. These forces include creativity, innovation, and the channels that spread new innovations into mainstream (such as cross-border flows and digital platforms).  Recent research from the McKinsey Global Institute (MGI) identified 12 breakthrough technologies with the potential to transform current value chains and achieve worldwide adoption by 2025. The list, which among others includes cloud technologies, the Internet of Things, the automation of knowledge work, or advanced robotics, may contribute up to half of secular total factor productivity growth in the years ahead. Moreover, the possibilities can be conjectured as bigger when emerging technologies are used in combination. Consider the intersection of robotics and artificial intelligence, or how materials science, physics, and IT are pushing green technologies forward. The ultimate prize may well be combining synthetic biology, big data analytics, and next-generation genomics to transform health care.

While most advanced economies have experienced a decline in total productivity growth—this decline cannot be entirely be attributed to better consumer surplus, mismeasurement, or the aftermath of the global financial crisis. Pushing disruptive innovation forward is likely critical key to reversing this trend and revitalizing growth.  

Will that growth be inclusive?

The "luddite" argument maintains that tech-driven innovation is fundamentally labor-saving and inevitably replace human jobs.  Recent history doesn’t bear this out: if some jobs have been lost, technology also creates the need for new roles. The real difficulty comes for workers caught up in the period of transition. In the long run, however, tech-driven innovation has been sustaining growth, generating more employment as a secondary effect. 

However, the past may not be reliable road map this time, for several reasons. First, labor’s share of national incomes is flat or declining in many countries. Second, technology diffusion is accelerating, demanding more agility from individuals and companies alike. Workers face a higher risk of mismatches and limited re-employment options. Third, the labor market is growing more polarized, with excess demand for specialized positions like big data analysts but a large excess supply of low-skilled labor.  

These trends do portend a period of accelerating change and even social disruption, but may not entirely invalidate the relationship between employment and productivity growth. In particular, there is growing anxiety about the effects on automation on employment, but it is critical to view these risks through the right lens. Much of research into this topic focuses on the number of jobs that could be lost. Yet automation is not aimed at eliminating specific occupations; it is designed to handle tasks. Recent MGI analysis suggests that only 5 percent of US jobs are likely to have 100 percent of their tasks automated by currently demonstrated technologies. More striking is the fact that 60 percent of US workers could have 30 percent of their tasks automated; even highly skilled workers will not be immune. So we need to prepare for a widespread redefinition of jobs rather than wholesale destruction.

What can one do about it?

Rapid technology-driven change raises a host of implications. Here are five. 

1. Because we are entering uncharted territory, the first order of business is that we must launch deeper research into these issues, so as to have the right framework against which to take actions. We need more research entities to step up and study the full picture of wages and employment, including new models outside of the traditional employer-employee relationship.

2. We may need to consider whether our educational systems and labor market structures are up to the challenge. We know, for instance, automation via artificial intelligence is still inferior to human intelligence for creative tasks, for task with unknowns, and for emotional intelligence. Are we doing enough to nurture this kind of creativity in education systems, within companies, and across the workforce as a whole? Are we ensuring the best complementary between jobs and the machine? My own recent research has found, for example, that 40 percent of returns on investing in big data arise from coordination and complementarity between IT and data scientists.

3. We also need to nurture new forms of being employed . While still a small portion of employment, on-demand jobs are growing fast, and we are finding that online talent platforms such as Linked In, Mechanical Turk, TaskRabbit and others help create a better matching of skills with companies’ labor demand and generate some of the data we need to design more effective training pathways. How can we make sure those platforms are better harnessed?

4. There is likely a value in experimenting the charge. If automation leads to better macro growth, it also leads to the redistribution of profits in favor of companies that can harness these technologies to their own competitive advantage. It has been widely discussed that the intersection of data, automation, and manufacturing could lead to “industry 4.0.” Research by Steffen Kinkel and colleagues has found that the use of advanced robotics in manufacturing tends to support both better labor and total factor productivity—and less offshoring, which could imply more local employment.

5. Finally, given the enormous possibilities for cross-fertilization across different fields, are we giving the right incentives to industry, education, and communities to create the right cross-disciplinary environment where collaboration and innovation can thrive? 

Dimitri Corpakis, Head of Unit, European Commission's Directorate General for Research and Innovation

1. What is the potential of new technologies as engines of growth? What factors are critical to competing in the emerging global economy?

The last part of the 20th century has witnessed a major acceleration in terms of scientific and technological advances. The advent of the Internet as a result of a long term development process in the field of information and communication technologies in the mid-90’s has completely changed the innovation paradigm, enabling the reconfiguration of the process of disruptive innovation: a large new base of generic technologies has been made available through a model that favoured new views and approaches, heavy user feedback and involvement and new methodologies for rapid prototyping and product / process initiation.

The nature of the new innovation process is so important, in the sense that it has set-up and is being fed by new creative platforms where a lot of converging technologies meet each other and in the process, they generate new models for introducing new concepts and paradigms, in an endless reconfiguration continuum. A major characteristic of these new platforms, is, that they do not necessarily need completely new technologies to run and produce their effects: the power of the platform approach resides in the self-organising profile of open technologies and services that create new opportunities in driving forward convergence, which is the major model for disruptive new approaches in product / process generation. ICT emerged as a powerful enabler for global convergence, creating new devices and new services through an ever –progressing combination of features, generic technologies and scientific domains.

Countries and regions that are able to integrate the new platforms and position themselves accordingly, may compete in the global economy. Those that have difficulties doing so, will see themselves marked by a dangerous marginalisation process that may be difficult to reverse.

2. How disruptive are technologies, such as automation, for industry and people? How do they impact the income distribution?

The effects of new technologies are heavily marking all areas of products, processes and related services. The digital revolution has now entered a new phase with emphasis on data and analytics, promising to modify completely the production chain (industry 4.0, 3D Printing, big data for cities management) as we knew it. A second wave of new and disruptive technologies has hit the market and creates already a huge impact on reconfiguring the technological offer available to modern economies.

The knowledge economy however, has changed dramatically the way countries integrate the global financial environment, creating harsh conditions in terms of competitiveness, growth and jobs, as many nations have difficulties in positioning themselves within the new global value chains. Income generation and income distribution follow asymmetric paths as global value chains reconfigure largely independently of any will or control of governments. In the future, automation and artificial intelligence will create more problems in the labour market as the speed of creation of new job profiles will not probably compensate the loss of mass employment in related impacted sectors.

3. What are the key implications for policy? What can be done to support the successful implementation of technology to serve inclusive growth?

Policy makers have a hard time to face the new realities, as they fight a series of constraints, linked to the economy, skills, technology and the evolving nature of the labour market. It is precisely in this context that the added value of research and innovation can make a difference for countries under similar threats. As an example, European countries that by definition adhere in a social model of a social market economy, have few alternatives for regaining competitive advantage and repositioning themselves in the global economy while working on inclusive growth. One way forward could be to maximise the quality of their research and innovation investment and design an effective place-based strategy for using an efficient research and innovation eco-system to translate within reasonable timing these investments in tangible economic and social benefits, for growth and jobs (Smart Specialisation). This must be accompanied by an overall package of measures for improving the output of education and training systems.

Mete Çakmakcı, Secretary General of theTechnology Development Foundation of Turkey (TTGV)

“Technology is a commodity” as a cliché is becoming more a reality in the emerging global economy. Any technology is valorized only when it is matched with an application to create new access and efficiencies to those use it. The earlier notion that “most sophisticated proprietary technology delivers the best value” is no longer valid. Creative skills to match a technology with a real tangible need are becoming as valuable as the skills to develop the technology itself. Be it big advanced analytics creating nano-banking through telecom infrastructure in Africa leading to new access or wearable technologies for pre-diagnosis monitoring that lead to efficiencies in the healthcare system, technology is carrying us towards better resource distribution hence sustainable growth. Identifying under-served needs, developing lean human centric designs and delivering the good apps through the means of technology are steadily becoming the new basics for new product and services development.

Much has been said about the impact of automation in industry on employment. Automation in industry will definitely change the labor dynamics towards a more digital savvy gray collar profile. Skills to create, distribute and process digital data will be more valuable. Digital data will be the currency of the new industrial model, creating more open supply chains, flexible production for much thinner batch lots and new service business models. New opportunities opened up by “hardware as a service” models will lead to new ventures based on cost engineering. It is not that far fetched to imagine a future where sustainable smart cities with distributed home manufacturing create a cellular network of micro economies.  We may as well call that “Industry 5.0”. High tech urban farming supported by ioT technologies will definitely be a part of that future. Not much is talked about services automation such as Internet banking, credit cards, RFID that have been recent productivity drivers. Smart applications in logistics have been providing many independent transporters access to more work and efficient utilizations of trips, therefore creating additional income. As smart grid and smart building applications demonstrate, simple technology accessible to anybody anywhere can lead to globally scalable yet easily replicable solutions. Deployment of technology in services and utilities to improve quality of life by making them more accessible and efficient should be aligned with the policy priorities to create new wealth through breakthrough innovation.

Plain digitization of current service models in health, education etc. will not yield the benefits expected unless we have an overhaul of the underlying designs. Current system of strong regulation and certification is probably the biggest hurdle preventing technology from delivering the transformative disruption it offers. Technology drives for stronger customization and personalization of applications, which are hard to accommodate under the current framework of standardized regulation. Many new generation technology ventures are struggling to scale in a regulated market that favors legacy incumbents. A fresh bottom up interpretation of societal challenges and better facilitation of innovation through technology are needed to let benefits touch a much wider part of the greater society. 

Andreas Esche, Member of the Management Committee and Director of the Shaping Sustainable Economies Program at the Bertelsmann Stiftung in Gütersloh

Innovations unquestionably have significant effects on our economic, social and environmental systems that can lead to major changes within these systems. The phenomenon of "creative destruction" described by Schumpeter is not new to us. Since the dawn of industrialization in the 18th century, we have repeatedly been witness to economic structures crumbling from within and replaced by new economic structures. As the engine driving productivity rates upward, innovation is critical to growth and societal wealth.

However, the destruction of structures inevitably means that there are parties to the process who will suffer negative effects. All industrialized countries have developed over time their specific models of the welfare state in which they minimize the risks of the unforeseen individuals face in economic processes, recalibrate the worst inequalities created by these processes and the persistent structural changes they generate, and establish the foundation of economic life through educational systems and regulated labor markets. For decades, the welfare state has guaranteed societal stability and elasticity, both of which the modern economy has needed to grow. This dynamic has led (at least in Western industrialized countries) to what others have called a virtuous cycle of education, innovation, productivity growth and rising societal wealth.

The basic mechanism of “creative destruction” hasn’t changed. But today we can identify four trends associated with the “digital tsunami” that alter the rules of the game:

(a)   A new velocity: The pace of what we formerly referred to “creative destruction” has become faster and faster. This is due in particular to knowledge-driven technological change in ICT, robotics, 3D printing and nanotechnology.

(b)   A new dimension of pervasiveness: The (primarily) ICT-driven economic and societal changes are disruptive: Entire business segments can disappear virtually overnight, and new business models or markets pop up from one day to the next.

(c)   A new dimension of interconnectedness and globalization: Global schemes of production and value chains are undergoing a complete reconfiguration. Some of the new business models tend to create global monopolies.

(d)   New inequalities: We are witnessing not only a marked increase in income inequality worldwide as a result of skill-biased technological change but also a decline in the share of wages in GDP, which is taking place despite rising labor productivity. The fact that productivity growth no longer seems connected with a growth in wages is challenging our traditional model that attributes value to human labor. Moreover, recent innovations seem to alter the nature of manufacturing. Structural change may increasingly take place without creating large numbers of new jobs.

In sum, the opportunities and challenges associated with innovation are much more complex than ever. But inclusive growth is still achievable. Countries need to pursuit a comprehensive agenda for productivity, innovation and inclusiveness. For those countries able to provide the appropriate human skills, which includes entrepreneurship and a manufacturing basis, opportunities will expand. Concrete policy responses include: Extending the quality and scope of higher and vocational education, fostering technological innovation and entrepreneurial ecosystems and expanding our institutional flexibility and capability to deal with radical change.

Christine Greenhalgh, Professor of Applied Economics (emeritus), Department of Economics, University of Oxford, and Emeritus Fellow, St Peter's College, Oxford; Adjunct Professor, Centre for Transformative Innovation, Swinburne University of Technology 

Views on the issues to be raised at the Symposium:

1. What is the potential of new technologies as engines of growth? What factors are critical to competing in the emerging global economy?

New technologies will continue to enhance economic growth in income per capita by improving the productivity of existing factors of production. Several new technologies are increasingly offering novel general purpose technologies across many areas of industry and services. Sophisticated computer software and artificial intelligence are already making an impact as we see such processes as computer aided design, machine failure diagnostics, and automatic trading of financial assets becoming increasingly common. In future we can expect to see 3-D printing processes and self-repairing machines in use in the home as well as being widespread in factories. These additive manufacturing techniques can revolutionise the location of production internationally when a design from one country can be almost instantly produced in another location. This could greatly reduce the transportation of goods making their production and delivery more like many financial services which are already communicable over the internet. The factors that will become ever more critical for competing in the new global economy will be the human skills enabling the domestic workforce to design and operate automated and semi-automated systems of production. These skills will include large elements of computer and communication skills, combined with knowledge of a conventional science-based field such as engineering, medicine, chemistry or biotechnology. But important complementary factors are the availability of cheap and reliable electricity, modern capital equipment including computers, and effective governance and legal structures including efficient intellectual property systems.

2. How disruptive are technologies, such as automation, for industry and people? How do they impact the income distribution?

In advanced countries new technology in the form of increasing capital intensity has been making inroads into the employment of semi-skilled workers in manufacturing for several decades. The growth of imports from low wage countries like China has also undermined the employment of unskilled labour in high wage countries. These factors have already led to a widening of the earnings distribution in much of the Western world. The new technologies will not be likely to reverse these trends and could increase the pace at which occupational structure changes in favour of the highly skilled and lower skilled workers are displaced by new technology or imports. 

3. What are the key implications for policy? What can be done to support the successful implementation of technology to serve inclusive growth?

Public policy to achieve full employment will be severely challenged in both advanced and emerging countries as demand for domestic labour producing traded goods and services and the nature of occupations will change quite rapidly. In all countries being able to adopt new technologies and apply these in innovative ways will be the key to sustaining jobs. Education and vocational training investments will need to be prioritised to avoid too many unskilled people competing for jobs in the lower skill section of the non-traded sector. However new technology itself offers increasing opportunities for lifelong learning to those with Internet access.

Agrita Kiopa, Deputy State Secretary and Director of the Higher Education, Science and Innovation Department at Ministry of Education and Science of Latvia

1. What is the potential of new technologies as engines of growth? What factors are critical to competing in the emerging global economy?

The potential of new technologies as growth engines have many facets. Most recent expert predictions about technology developments in artificial intelligence and robotics, for example, point at technology induced changes in many industries – health care, transport and logistics, to name the few. Moreover, the nature of innovation has changed. For countries to compete in the global emerging economy the most critical factor will be the ability to participate in new modes innovation and markets. This brings forward the challenge of creation of local S&T talent and finding new ways of creating productive relationships between local and global communities.

2. How disruptive are technologies, such as automation, for industry and people? How do they impact the income distribution?

The available empirical evidence suggest that technologies are disruptive and that changes induced are likely result in decline of employment in routine task-intensive production and occupations, and increase of employment in abstract and manual-task-intensive occupations.  At the same time it is likely that new industries will emerge that will provide new opportunities for work and innovative ways of making living. Technologies will eliminate jobs not work. However the speed of creation of new types of jobs and ways of making living will be a serious challenge. Given that abstract and manual-task-intensive occupations currently encompass the highest and lowest paid jobs, it is likely that income inequalities will increase.

3. What are the key implications for policy? What can be done to support the successful implementation of technology to serve inclusive growth?

Key policy implications, especially for economies at the periphery of larger systems, that policies have to unleash human ingenuity for building strong institutions that foster new types of innovation and productive entrepreneurship, and that make unproductive entrepreneurship unappealing. To put technology at the service of inclusive (and sustainable) growth policies have to be mindful and address both economic and social factors. Thus, policies should not only support growth, by scaling up existing domestic technological capabilities and expanding these capabilities into domains of traditional industries, but also by generating human capital that is talented, locally embedded and globally connected. Roles of existing core education institutions have to be redefined to include creation of sufficiently diverse knowledge base, generation of such locally embedded and globally connected S&T human capital, creation of innovation capacity of firms and serving as innovation resource hubs. 

Mélanie Marcel, Founder of SoScience

In a context of growing income inequalities, the question of what opportunities the new emerging economy holds for different groups in society, and what policy can do, is crucial. Among the many challenges in promoting inclusive innovation, the lack of technical expertise is one of the biggest, a serious obstacle for grassroots entrepreneurs aiming to scale up their innovation. Another challenge is that they have access to very few resources to help them develop their project.

As the OECD report dedicated to Innovation Policies for Inclusive Growth published in 2015 shows, grassroots expertise is based upon their experience of everyday life and the informal nature of their business prevents them from accessing of knowledge of existing technologies, networks and expertise of their field. Of all the actors across the innovation system spectrum, universities are the ones playing a major role in providing such expertise for two main reasons:

  • Traditional economic role: Public research is the main source for research and development as well as trained experts in numerous fields. Financed by public funds, universities have access to special equipment and data, important financial resources that enable them to provide fundamental knowledge and expertise to companies which develop innovation products. Universities are therefore the best intermediary for grassroots entrepreneurs to access expertise.
  • New economic role: In the economy of knowledge, universities take on a new role which is to participate actively in the economic growth. Connections between universities, private enterprises and the industry are thus fostered in order to facilitate the transformation of scientific research results into potential innovations suitable to feed the economy. In this context of the commercialisation of public knowledge, universities could also consequently act as facilitators to support grassroots entrepreneurs’ commercialisation efforts as the report points out.

The innovation system as it exists today seems to exclude actors of the informal economy. Indeed the report explains that what is observed today is the concentration of innovation which is also called “the search for excellence” in countries, regions, sectors, firms, universities and public research which became leaders in the economy.The concentration of innovation has positive outcomes as it helps to create advanced knowledge. However, it also creates a high concentration of knowledge, tools and resources, excluding potential economic actors.

In some ways this seems to be in contradiction with the reverse trend, of the democratization of innovation (i.e. widening of the group of successful innovators to include actors who did not previously participate in innovation processes thanks to ICTs and bottom-up initiatives which are the main drivers to the democratization of innovation).

New actors in the economy of innovation are individuals, social entrepreneurs, grassroots innovators and also citizens. The latter want to take part in the scientific research by providing data or developing their own research on dedicated platforms and spaces such as Fab-lab, DIY labs, etc (citizen science). As they collect more knowledge to understand societal issues, they want to play a role in solving them. Even though this trend is developing fast, citizen science is often under evaluated by the scientific community. However, scientific researchers have also become aware of the nature and consequences of their work. As citizens they assume a new role: they want their work to contribute to the good of society.Those two communities often depicted as separate are not that different after all !

That is why we shouldn’t consider these trends as opposites: we ought to think differently on this issue and see these trends as complementary for developing inclusive innovation.

Although the concentration of innovation can get in the way of democratizing innovation, it can also provide advanced knowledge and expertise to the remainder of the economy.Unfortunately, interactions across the field of innovation actors are almost non-existent and must be developed to promote the diffusion of knowledge and cooperation.

From this point of view, one solution to this issue and especially to the lack of expertise we mentioned above is to foster cooperations between grassroots entrepreneurs, universities and research institutes. Such a cooperation could take the shape of intermediary institutions allowing for the exchange of knowledge and information. One such example is The Honey Bee Network (India) which connects informal innovators with formal institutions, including universities and public research institutions. On the platform, for instance, the Techpedia project promotes links between technology students and innovators in the informal sector.

In this spirit, we created SoScience in France in 2011, which is the first startup dedicated to Responsible Research and Innovation in Europe. Last year, we were selected by the European Union as one of the five responsible innovation projects to take as models in Europe which demonstrate the significant importance of this trend. We collaborate with research centers and social entrepreneurs in order to foster the development of scientific answers to today’s grand social and environmental challenges. To do so, we aim to develop and test partnerships between social entrepreneurs and research institutes to integrate societal needs in research and development. We believe it is the most promising way not only to forge bonds of mutual interest between social entrepreneurs and researchers but also to develop inclusive innovation.

Dr Youngah Park,  President of Korea Institute of S&T Evaluation and Planning (KISTEP)

The rapidly changing dynamics of the global economy requires nations to endlessly adapt and evolve to maintain growth. To ensure long-term growth, nations need to devise growth strategies based on the advancement of new technologies. Needless to say, in order to achieve sustainable growth in productivity and income, continuous investment in development of new technologies is crucial.

However, the rate at which new technologies are developed and spread has given rise to voices of anxiety and concern. These voices of caution are not without reason, as technology has been known to bring about unexpected side-effects, even when they had been developed with good intentions to enhance and enrich our world. We are all too familiar with these examples, and technology has been blamed not only for giving rise to terrors such as weapons of mass destruction, but also for creating unexpected problems such as privacy invasion, and pollution.

Despite these adverse effects, we owe much of the wealth generated in the modern world to technological advancement. Where technology has failed is in its distribution; wealth is distributed unevenly, and more alarmingly, income disparities continue to grow wider.

The question of how technological advancement may influence wealth distribution is extremely important for novel and emerging technologies, such as robots equipped with artificial intelligence, which have the potential to completely transform the labor market. The ensuing displacement of jobs will have direct consequences on people and the society at large.

The problems that new technologies give rise to, such as income disparity, and lack of jobs, can be alleviated by active policy support by the government. How the landscape of the labor market will change with the introduction of robots with artificial intelligence is still very much open to question. The changes are not happening in a state of void, and their direction may be guided or altered by the choices we make now.

In this light, KISTEP (Korea Institute of S&T Evaluation and Planning) has been conducting technology assessment since 2013 to forecast the economic, social, cultural, ethical and environmental impact new technologies will have on our society. Emerging technologies studied in recent years include 3D printing, unmanned vehicles, super skyscrapers, and gene editing. Artificial intelligence was studied most recently, and its impact was analyzed from four major perspectives: increase in productivity, change of the labor market, enhancement of the quality of life, and potential social and ethical issues due to malfunction or misuse. Such findings offer an interesting look into our future, and hold significant implications for policymaking and implementation.

 

To plan and shape the future with our own hands, we need to break free of the old frame of mind that technological advancement drives economic growth. What we need to do, while there is still time, is meticulously analyze the impact of future technologies on all aspects of life, including education, employment, and social values, and prepare for the time when they do happen.

José Saenz, Project Manager at the Fraunhofer Institute for Factory Operation and Automation in Magdeburg (Germany) and Coordinator of the Industrial Robotics Topic Group of the euRobotics aisbl

I think we’re all going to concur that new technologies have very large potential as engines of growth. Within my field of collaborative robotics, we are seeing rapid changes that are affecting how individual companies are manufacturing their products (as well as where they can be economically produced). Right now it’s mainly the large companies that are able to gain experience with these new technologies and that are working to expand their competitive advantage. A large question in research right now is how to make new robotics technologies feasible for the smaller companies, both economically and from the technical know-how needed to install and run the robots.

The aim from an idealistic, research perspective is to create a more human-centered workplace through collaborative robotics. I think there’s a huge chance to rethink production (think changeover from steam engines to electrification), and this gives companies an opportunity to put human’s and their needs at the center of it. However it would be naive to think that companies are doing anything besides trying to maximize profits. The changing nature of work will affect the distribution of income greatly. Therefore rules need to be in place to balance any effects due to changes, and to ensure that the direction of the changes are in tune with society’s needs and not just the profits of a few, large companies.

From a policy side, support includes more resources for training and re-training, as well as a policy nudge to the research side to make technology inclusive and human-centric as well as better study of the human impact of technological advances. What also helps is standardization and creating regulatory certainty for early adopters. As an example, we are testing on humans right now, where pain thresholds lie and where the biomechanical limits are for cases when robots come into contact with humans. We were surprised that even medical experts were not aware of these biomechanical limits, until we realized what a luxury problem it is; people don’t usually visit a doctor because of a bruise or a bump. Our aim is to get statistically relevant information that can go into the robotics standards, so that when people are working with a robot, any eventual contact, even due to accidents, won’t be anywhere near the statistically determined pain threshold. Nobody wants to install a collaborative robot in their factories and then later explain why somebody got hurt working with it. Having best practice information and strong standards built upon solid scientific foundations are one way to lower the barriers to adoption for all companies. 

Manuel Trajtenberg, Professor at Tel Aviv University 

Views on the issues to be raised at the Symposium:

1.     What is the potential of new technologies as engines of growth? What factors are critical to competing in the emerging global economy?

The potential of some new technologies is enormous, particularly those that qualify as “General Purpose Technologies”, that is, those that are adopted widely throughout the economy, and trigger complementary investments that change fundamentally the way things are done in the adopting sectors.

To compete in the emerging global economy the key is continuous adaptation of the local economy to shifting comparative advantage, and the consequent smoothing of factor mobility across sectors.

2.      How disruptive are technologies, such as automation, for industry and people? How do they impact the income distribution?

Once again, some technologies can be highly disruptive, in particular those that spread rapidly throughout the economy, and demand very different bundles of inputs, and in particular of skills. The impact on income distribution follows the distribution across the population of those factors of production and skills that are demanded by the new technology – the more different that distribution from the existing one, and the more unequal it is, the worse the distributional consequences. 

3.      What are the key implications for policy? What can be done to support the successful implementation of technology to serve inclusive growth?

Policy can incentivize the spread of new “General Purpose Technologies” (GPT’s) to promote growth, but the key is to do it in such a way as to minimize the adverse distributional consequences. Inclusive growth requires both investing heavily in human capital and skills demanded by the new GPT’s, and making sure that those investments are widely spread throughout the population. 

Shahid Yusuf, Chief Economist of The Growth Dialogue 

Most middle and high-income economies are banking on productivity gains from technological change to drive growth during the coming decades[1]. Capital investment will remain a source of growth although its contribution is expected to diminish as will the contribution of labor. Can technological advances deliver the 2 to 3 percentage annual rates of GDP growth sought by post-industrial countries and the higher rates targeted by economies ascending the income ladder? As Yogi Berra rightly opined, “making predictions especially about the future is tough” and the recent track record of economists only reinforces this observation. Depending on whose reading of the past trends one favors, technological change is either slowing or it is galloping along and delivering increments in productivity that are not being accurately measured.

Robert Gordon (2016)[2] firmly maintains that the high income countries are entering lean technological times and at best can expect a continuation of the meager 1.3% p.a. (or less) rates of productivity increase notched up by the U.S. since the early 2000s[3]. Potential growth rates will struggle to exceed 2.5% p.a. looking decades ahead[4]. The secular stagnationists eyeing ultra-low long-term bond rates are inclined to agree. But there are other voices chastising the naysayers for their pessimism. Joel Mokyr[5] and Hal Varian[6] for example, believe that digital technologies are far from exhausted and much like earlier general purpose technologies, can continue spurring productivity well into the future. Some, including Larry Summers[7], are of the view, that productivity is being mismeasured – medical care for example, has made significant leaps, the Internet plus Google has made us more productive (and distracted) and the host of digital apps at our fingertips is yielding a wealth of consumer surplus.

The likelihood of non-trivial mismeasurement has been challenged and refuted by Syverson (2016), Byrne, Fernald and Reinsdorf (2016) and Nordhaus (2015)[8], which strengthens the case of Gordon et al that we are in for slow growth in advanced economies and in middle income ones that are approaching the technological frontier.

An easing of technological change has a number of implications – and not only for growth. It is likely to diminish the entry of firms and the emergence of gazelle firms and of unicorns that harness product and services innovations to challenge incumbents and to create entirely new market opportunities. With a decline in new entry as is evident in the United States since the turn of the century[9], there will be less churning of firms, which could dampen market competition with feedback effects on the need to innovate.

Slower growth means that new jobs will be scarcer, which in the medium term might not be an issue for advanced economies where the workforce is shrinking[10] but it will be a serious concern for middle-income countries. However, if a slowing of growth is paralleled by a surge in automation, and the use of smarter machines to displace workers in a wide range of blue and white collar occupations, then the disruption will be much more severe because under conditions of slower growth overall, new jobs will materialize less rapidly than in the past.

The kind of technological change that is in the offing i.e. digital change augmented by AI, could be doubly disruptive because any job creation will require different and arguably more complex skill sets (including soft skills and a high level of computer literacy). Those laid off might have difficulty quickly acquiring the right skills and may lack geographical mobility to boot. Lengthening bouts of unemployment will also reduce employability. The upshot of this could be a perfect storm: a vicious cycle of slow growth, accelerating automation, rising unemployment, increasing (Pikettian) inequality, declining consumer demand and a further deceleration of growth.

Prompt and wide ranging policy action to arrest the spiral is urgent – and yet the fiddling goes on. What might work?

With monetary policy having largely blunted its edge, there are many voices calling for increased public spending on infrastructure to enhance productivity and crowd in private investment. This is desirable however, the multiplier effects might be small, and limited fiscal headroom in most countries will inhibit policymakers even though borrowing costs are negligible. Tax and transfer polices would reduce inequality[11] and could boost demand as could a higher minimum wage, but these will encounter stout political resistance and countries might not unilaterally want to embark on such policies for fear of losing competitiveness. Improving the quality of education and the relevance of the skills imparted (including through lifelong learning) will be of help but most likely in the longer term and it is far from clear that training more scientists and engineers[12] could raise growth by a notch or reduce unemployment[13]. Higher spending on basic research could also lead to more inclusive growth over the longer term but only if the technologies and innovations that emerge are labor using, do not increase the incidence of labor displacing automation and create jobs not just for those with higher education but also for a large legacy labor force with a modest and largely eroded base of schooling.

It maybe that if the above interventions fail (assuming that they are attempted with vigor), the nations of the world may have get used to the ‘old normal’ of slow and stately growth. 


[10] In the near term there is plenty of pain for the unemployed youth and the middle aged blue-collar workers that have been laid off.

[12] See the recent publication by Andrew Hacker (the Math Myth) and by others who have pointed to limited employment opportunities for scientists and engineers.