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The politicians, bureaucrats, businesspeople, and academics that take part in the perpetuation of society’s obsession with innovation, all have in common that they view innovation in very positive terms—arguably, too positive—and seem to believe in an almost magical capacity of innovation and entrepreneurship to create jobs, grow the economy, solve sustainability challenges, and make life better for everyone. This overconfdence has metamorphosed into “innovationism”, a belief system or ideology that is conceptually distinct from innovation in a real or technical sense (Valaskivì 2012: 133). Innovationism has no intrinsic capacity to improve anything. Quite the opposite: It entails a strong appeal to national or regional identity (Chap. 5), combined with a constantly invoked message of competitiveness. This means that on a very subtle level, it risks turning its overpositive message into a rhetoric of fear of falling behind in the highly competitive and globalized knowledge economy. Innovation is often presented as the only means for national (or regional) survival in a hostile world. It is not uncommon for this to be summarized with the catchy but rather intimidating phrase “innovate or die” (Hasu et al. 2012: 90). In this sense, innovationism is fundamentally dishonest, as it pretends to play on feelings of optimism but breeds a worry of being left behind (Vinsel and Russell 2020: 11). Such a rhetoric of fear, especially if indirectly deployed using grandiose slogans and a dazzling surface, is arguably counterproductive both on overall societal level, in the long run, and specifcally in relation to those young minds that are necessary to encourage and stimulate to innovate.

Other destructive consequences of innovationism, and of society’s obsession with entrepreneurship and growth, are of course more plain and concrete. Among the most obvious ones—already hinted in previous chapters—are wasteful spending. The huge and centrally planned programs of “the entrepreneurial state” (Chaps. 2 and 5), have been amply criticized on theoretical and empirical grounds. Especially questionable is the seeming lack of effciency with which the programs launched under the auspices of the entrepreneurial state ideology do actually support technological development and sustainability transitions (Harford 2011; Karlson et al. 2021; Wennberg and Sandström 2022; Larsson 2022). Similarly, the entrepreneurship industry (Chap. 4) seems to be a formidable source of free money for those capable of selling a product of service to these would-be-entrepreneurs. Veblenian entrepreneurship—amounting to the “conspicuous consumption” of such products or services to maintain a particular lifestyle (Hartmann et al. 2020)—becomes really problematic when taxpayers’ money or private capital are spent to support such lifestyles, under the pretext that it is spent to support the development of the economy (Brattström 2022: 148).

For writers such as Steven Pinker (for example, in his book 'Enlightenment Now'), the human condition is steadily improving, and this improvement can be picked up across a range of indicators: fewer homicides, fewer infant deaths, longer life expectancies, improving human rights, increasing literacy, increasing average education, increases in mean (and also median) wealth, fewer people in extreme poverty (less than 1 USD/ day), etc.

However, while not denying significant progress in some areas, particularly the reduction in violence, cherry-picking data to support a comforting Whiggish conclusion is unlikely to generate robust evidence.

We are said to live in a time of remarkable innovation, with the computer/information revolution often compared to the Industrial Revolution in allowing people to produce more while working less. Economists, consultants, and other business gurus are striving mightily to quantify this revolution and to understand its sources and implications.

One popular metric is the number of new patents issued each year. For example, the pace of innovation might be gauged by the fact that there were 669,434 US patent applications and 390,499 new patents awarded in 2019, each triple the number in 1997. Lists of the most innovative companies, industries, and nations are often based on the number of patents, and patent analysis has now become a dominant method for studying innovation. The number of research papers in Google Scholar that contain the phrase “patent citation” rose from fewer than 10 in 1998 to more than 900 in 2014. Of the 20 papers published in the American Economic Review during the past decade on product, process, and service innovations, 9 used patent analyses. For Management Science, the leading management journal on innovation, it’s 11 of 15.

Myth 4: We Live in a Knowledge Economy – Just Look at all the Patents!

Similarly to the myth that ‘innovation is about R&D’, a misunderstanding exists in relation to the role of patents in innovation and economic growth. For example, when policymakers look at the number of patents in the pharmaceutical industry, they presume it is one of the most innovative sectors in the world. This rise in patents does not however reflect a rise in innovation, but a change in patent laws and a rise in the strategic reasons why patents are being used. In ICT there has been a shift in the use of patents from the development and protection of proprietary technologies, resulting from in-house R&D, to cross-licensing in open systems, with the purpose of buying in technology (and the related patents) produced elsewhere (Chesbrough 2003; Grindley and Teece 1997). This has caused the R&D budgets of large companies, such as IBM, to fall at the same time that their patent numbers rose (Lazonick 2009, 88–9). Not recognizing these dynamics cause a focus on the number of patents to be misguided.

New research shows immigration and a diverse population propelled America’s rise as a superpower in innovation. The study examined surnames, counties and patents from the 1850s to the 1940s to reach its findings. The research, bolstered by other recent studies, shows increasing immigration likely enhances innovation, productivity growth and labor force growth—essential elements to raising economic growth and producing a higher standard of living in America.

Smith, Jones and Patel

Nvidia’s rocket-ship ride in the stock market underscores the extent to which chip quality and availability will dictate the winners in the generative AI era. But there’s another aspect to measuring early leads in the space. In China, which is angling to produce its own chips or get more from Nvidia, no dominant gen AI contender to OpenAI has emerged yet among dozens of Chinese tech titans and startups.

Late to the game, China is seeking to catch the lead of OpenAI in a wider U.S. AI market shaped by tech titans Microsoft, Alphabet’s Google and Amazon, and well-financed startups including Anthropic, which this week received a $2.7 billion infusion of cash from Amazon.

However, the federal government’s ambitions extend beyond semiconductors. The Inflation Reduction Act, also passed in 2022, is stimulating a significant wave of investment in climate tech. And the Biden administration aims to bolster US strengths in the biotech and quantum sectors, too. It recognises that the US has previously failed to capitalise on its early technological lead in some critical areas — telecommunications infrastructure equipment and batteries, for example — and does not want to repeat that mistake.

There is, of course, only so much that Washington can do. But the US private tech sector is independently enjoying a surge of new funding as investors bet big on the transformative power of artificial intelligence. US companies, led by Google, OpenAI, Nvidia, Microsoft and Anthropic, already dominate the field of generative AI. Goldman Sachs estimates that AI-related investment could rise to between 2.5 per cent and 4 per cent of GDP in the US, compared with 1.5 per cent to 2.5 per cent in other leading economies.

Closely watched science and technology indicators from Washington DC show the US is still the world’s biggest spender on research and development, confounding expectations that China would takeover the lead.

A faltering Chinese economy and plummeting birthrates have driven a conversation over whether the world has reached ‘peak China’, where Beijing’s economic and geopolitical ascendancy over the US no longer looks inevitable. Now, a similar debate is happening in the domain of R&D.

HONG KONG – The United States has long dominated much of the knowledge economy, not least owing to an innovation environment that has proved highly attractive to foreign talent. But China has been watching carefully, adapting crucial lessons from the US to the local context. And its efforts are bearing fruit.

America’s lead is significant. In 2000-19, the US had far more Fortune Global 500 companies than any other country. In 2000, the US boasted 179, compared to 107 for Japan and just ten for China. Though China surpassed the US in 2020, the US companies have retained an absolute advantage in market capitalization, profitability, and technological innovation.

The circular economy is at the heart of Novo Nordisk’s approach to pharmaceutical waste. Novo Nordisk is a global healthcare company headquarted in Denmark, and a leader in diabetes care. The company’s new environmental strategy, Circular for Zero, sets a new direction for the organization as it transitions from a linear economy of “take-make-dispose” to a circular economy based on three principles: Design out waste and pollution, keep products and materials in use, and regenerate natural systems. The company’s ambition is to have zero environmental impact and to reach a point where it is producing zero landfill, water, energy and material waste. Today 77% of Novo Nordisk’s power comes from renewable sources and it expects to reach 100% by 2020.

For Novo Nordisk’s production of biological medicines, “yeast by far represents the largest amount of waste, and for this we have a very good setup,” says Dorethe Nielsen, Senior Director of Corporate Environmental Strategy at Novo Nordisk. “We convert the yeast into biogas so that all our waste from the fermentation process goes into our biogas plant and is converted into biogas. Anything left after being converted to biogas is used as fertilizer on farmland as there are a lot of nutrients left. Our process is a closed loop, you could say.”

Like corporate social responsibility, green chemistry is a field in which it is easy for big firms to make big declarations (and to employ a range of different metrics and measurements) without taking much action. Companies also tend to refer enquiries to the corporate website rather than answer questions directly. But changes are happening, some of which have become part of the mainstream.

Pharmaceutical companies have switched the manufacturing processes of several well-established medicines — including the diabetes drug sitagliptin, the malaria treatment artemisinin and the painkiller ibuprofen — to less environmentally damaging ones in recent years.

AI is reshaping waste management practices, driving the transition towards a circular economy and propelling us towards a more sustainable future

Sustainable Development Goals (SDGs) have garnered increasing attention in recent years. Today, the pivotal role of technology, particularly artificial intelligence (AI), in achieving these goals is gaining prominence, sparking deeper discussions. As the world strides towards sustainable development, smart cities are embracing cyberinfrastructure to foster holistic economic growth, enhance the quality of life, and optimise resource management. However, the mounting challenge of waste management looms large over many urban areas due to the inefficiencies of traditional methods. Yet, smart cities are proactively harnessing innovative technologies like the Internet of Things (IoT), big data, and AI to revolutionise waste management, paving the way for a circular economy (CE). This transition demands a paradigm shift towards a more sustainable supply chain ecosystem.

Two key solutions to the e-waste problem have emerged: moving from a linear to a circular economy, and fostering digital sustainability, including creating more efficient IT.

The two solutions go hand in hand. In a circular economy, designers and manufacturers create products with the end of the products’ lives in mind. That means keeping products in use for as long as possible and then recycling the materials that go into them to minimise or even eliminate waste. Digital sustainability means adopting technology that has environmental, societal and financial benefits. Circularity is making this improved technology possible.

Nearly every modern industry utilizes robots for fast, precise, accurate and safe working conditions. Advanced robots reduce the human effort and risks involved in industrial processes with many other benefits like nonstop, rapid pace working with minimal errors.

E-waste recycling also requires robots for better management of electronics and electric components. Advanced robots with visual sensors allow the identification, categorization, and separation of different types of e-waste. For instance, In a 2023 study addressing the challenge of e-waste recycling, researchers implemented a 6-axis robotic manipulator to create a semi-automated industrial robotic system with collaborative human-robot interaction. The system, employing OpenCV image capture, TCP connections, and Arduino integration, aims to detect, disassemble, and segregate components of commonly discarded e-waste for proper disposal and recycling.

That’s why Bollegraaf, the world’s biggest builder of recycling plants, and the AI start-up Greyparrot are rolling out artificial intelligence systems for sorting recycling. The companies plan to retrofit thousands of recycling facilities around the world with computers that can analyze and identify every item that passes through a waste plant, they said Wednesday.

“The destiny of a product is decided by this plant,” said Ambarish Mitra, who co-founded Greyparrot. “This is where the highest impact can be made — not in the bins, not in the household, not with consumer education — because this is where the decision is really made about what’s going to happen to that product.”

But what if innovation can be underpinned by different values and purposes? In this context, we generally build on theoretical propositions developed by STS, including critical and social constructivist views on technology. However, following Walsh’s (2021) call for Marxist perspectives, we shall complement this with Gramscian concepts of hegemony and counter-hegemony. Through this lens it becomes possible to describe different modes of innovation underpinned by hegemonic and counter-hegemonic sets of societal values. We argue that current views on innovation are underlined by the hegemony’s common senses of valorisation logics explaining its depoliticisation and the general perception of innovation as apolitical. With the aforementioned lens we hope to speak to STS scholarship and more classic innovation scholars by using a Gramscian influenced perspective that makes it possible to unfold paradoxes around innovation which might otherwise be tough to observe (see Walsh, 2021).

As this special issue suggests, innovation management has traditionally focused on innovation generation, process management, and diffusion, with relatively little emphasis on sustainability and societal aspects. The argument in the above paragraphs opens up the idea that this ‘classic’ innovation management is not a natural or an a-historic construction. It can be viewed as a socially constructed ideology emerging from the imperative of valorisation and thus, not the only possible underpinning principle of innovation. Our main hypothesis is that if innovation is not underpinned by hegemonic pressures of valorisation, it can open the door to a variety of alternative social possibilities that have the potential to address social justice and environmental issues. In line with this special issues’ call for papers we interpret our task as researchers to normatively present alternative purposes for innovation. Following recent debates about post-growth and degrowth (Pansera and Fressoli, 2021), we argue that the fundamental purpose of innovation should not be to increase productivity to foster economic growth. Instead the purpose of innovation should shift towards the aim of use-value creation. By use-value creation we mean socially useful production that seeks to fulfil societal needs.1 Use-value should be understood in contrast to exchange-value (Marx, 1969 [1867]). According to Marx (1969 [1867]), use-value is subsumed under the pursuit for exchange-value generation in the capitalist mode of production. Exchange-value defines value by the potential financial gain that can be achieved through a goods exchange; meaning that under this definition value can only be generated through financial gain in market exchange. However, this does not mean that under a focus on use-value that no exchange is possible or no markets would exist. Very much to the contrary, exchange and markets still have an important role to play in a society focusing on use-value creation, that is goods and services can and should still be exchanged and traded to help fulfil societal needs. Hence, under the focus on use-value creation, exchange and the market do not become the end goal in value creation (as for exchange-value) but rather a means to an end, which is fulfilling societal needs.

McKinney 23, [Phil McKinney (CEO of CableLabs, CTO of Hewlett-Packard’s Personal Systems Group), “Understanding the Innovation Economy and Its Impact on Our World,” Killer Innovations, , accessed 6-27-2024, 8/22/23] Mr.Mr.

Economic Growth and Prosperity

Millsap 24, [Adam Millsap (Master’s and PhD in economics from Clemson University and a BS in economics and a BA in comparative religion from Miami University in Ohio, Senior Fellow in economics at Stand Together Trust, has taught courses in economics at Johns Hopkins University, Florida State University, Clemson University, and George Mason University), "How Innovation Boosts Growth And Why We Need More Of It," Forbes, https://www.forbes.com/sites/adammillsap/2024/04/06/how-innovation-boosts-growth-and-why-we-need-more-of-it/, accessed 6-27-2024, 4/6/24] Mr.Mr.

Last week, the Bureau of Economic Analysis (BEA) released 2023 fourth quarter GDP growth data for the states. Annualized growth rates varied from a high of 6.7% in Nevada to 0.2% in Nebraska. Idaho, Utah, South Carolina, and Texas also grew by 5% or more (see map below). With better economic policies more states would grow faster.

Separately, policy uncertainties can be resolved with time, and explicit effort, through science itself. Much has been learned about how science and innovation operate, and where breakthroughs come from. Further advancing our understanding will depend on continued research effort, and the scientific toolkit is powerful here, from the expanding access to comprehensive data about scientists, inventors, entrepreneurs, and their funders, to the expanding set of empirical tools, which include experimental, network, and machine learning methods. Continuing research will sharpen our choices and promises to raise the social returns even further. 5. Conclusion Science and innovation investments are central to the national interest. These investments can create higher standards of living, longer and healthier lives, and an increasingly competitive workforce. They can support national resilience in the face of crises, like the global pandemic, and they can sustain national leadership in the world, including on economic, political, and security dimensions. Given these potential benefits, this chapter has considered whether the United States invests enough in science and innovation, and specifically whether greater public support is warranted. We have asked several related questions: What are the arguments for or against a public role in the science and innovation system? What is the evidence? How are we doing? What policy changes do we need? A primary case for public action sees new ideas – the fruits of science and innovation -- as “public goods” that the private sector will underprovide. Meanwhile, skeptical perspectives emphasize the regularity of failed R&D efforts, doubt the capacity for successful public investment, and question the role of science and domain experts in driving practical and important advances. After laying out these different perspectives and illuminating them with examples, the chapter turned to systematic evidence, including the very latest evidence. The conclusions from systematic evidence are clear. The social returns to R&D investments are enormous and greatly in excess of the private returns. Public investments in science appear closely aligned with public use, and domain experts are the primary drivers of breakthroughs in both science and marketplace innovation. In short, the U.S. science and innovation system as it stands delivers far more than its resource costs, and we underinvest in science and innovation to an enormous degree. For every $1 we invest, we conservatively receive $5 in benefit. Effectively, the public has at hand an extraordinary machine to benefit human progress and the national interest, yet we fail to use this machine anywhere close to its full capacity. To meet the national interest, policy can adapt in first-order, high-return ways. This chapter has emphasized three poles of action to reap the rewards: (1) scaling funding resources; (2) scaling the people pipeline into science and innovation careers; and (3) making diverse investments across the landscape of opportunities. These investments promise to raise our standard of living, accelerate progress against disease, increase the competitiveness of the American workforce, solve for national and global crises, and secure the nation’s leadership in the world.

Millsap 24, [Adam Millsap (Master’s and PhD in economics from Clemson University and a BS in economics and a BA in comparative religion from Miami University in Ohio, Senior Fellow in economics at Stand Together Trust, has taught courses in economics at Johns Hopkins University, Florida State University, Clemson University, and George Mason University), "How Innovation Boosts Growth And Why We Need More Of It," Forbes, https://www.forbes.com/sites/adammillsap/2024/04/06/how-innovation-boosts-growth-and-why-we-need-more-of-it/, accessed 6-27-2024, 4/6/24] Mr.Mr.

Last week, the Bureau of Economic Analysis (BEA) released 2023 fourth quarter GDP growth data for the states. Annualized growth rates varied from a high of 6.7% in Nevada to 0.2% in Nebraska. Idaho, Utah, South Carolina, and Texas also grew by 5% or more (see map below). With better economic policies more states would grow faster.