For decades, innovation has been seen as the answer to our greatest challenges, from climate change and energy scarcity to economic stagnation and public health. Technological breakthroughs, from COVID-19 vaccines to advances in artificial intelligence, reinforce the narrative that human ingenuity can overcome any limit.
However, while this perspective has some validity, it is increasingly misleading, even dangerous.
Recent research from various fields reveals a concerning long-term trend: innovation is becoming more expensive, more complex, and less productive per unit of investment. This phenomenon, known as diminishing returns to innovation, has significant implications for policy planning, particularly in areas that require sustained scientific, technological, and infrastructural commitment.
1. The Rising Cost of Innovation
Philosopher of science Nicholas Rescher argued in the late 1970s that scientific progress becomes more expensive not only in absolute terms but also relative to national resources, particularly in terms of personnel and funding.
This observation has since been substantiated by large-scale empirical studies:
-
Bloom, Jones, Van Reenen, and Webb (2017), “Are Ideas Getting Harder to Find?” NBR Working Paper No. 23782. The authors analysed sectors like semiconductors, medicine, and agriculture. They found that while R&D spending has grown exponentially, research productivity has declined, in some cases by a factor of 10 over recent decades.
-
In “The Burden of Knwoledge and the ‘Death of the Renaissance Man’: Is Innovation Getting Harder?”, Economist Ben Jones (2008) demonstrated that as knowledge frontiers expand, it becomes harder for individuals to master enough to innovate. The average age at which scientists make major contributions has increased, and team sizes have expanded, resulting in higher coordination costs.
2. Innovation Teams Are Growing—but Output Is Not
Researchers Luis Bettencourt, Deborah Strumsky and José Lobo analysed over five million U.S. Patents. In 2004, they published their findings in a working paper titled “Invention in the City: Increasing Returns to Scale in Metropolitan Patenting”. They found that innovation increasingly relies on larger teams, but even with this shift, the productivity of innovation declined by 22% over one generation, across both mature and emerging technology sectors, including nanotechnology and biotechnology.
This trend mirrors other findings that show a growing disconnect between scientific input (funding, personnel, time) and measurable output (breakthroughs, patents, productivity growth).
3. High-Profile Breakthroughs Depend on Deep, Costly Infrastructure
Breakthroughs like the rapid development of COVID-19 vaccines are indeed extraordinary, but they rest on decades of prior foundational research (e.g., mRNA platforms, public health data systems, international cooperation). Similarly, recent progress in AI is powered by:
-
Data pipelines built over decades,
-
Specialised compute infrastructure,
-
Billion-dollar investments by public and private actors.
As Joseph Tainter, author of The Collapse of Complex Societies, argues: “Complexity increases system costs faster than it increases system benefits.” At the 2010 International Conference on Sustainability, he cited Norman Augustine’s Law #16, which humorously projects that if defense spending trends continue, the U.S. will afford only one aircraft, which will need to be shared between the different branches of the armed forces, by 2054—a satirical but sobering reflection on cost escalation.
4. The Nature of Innovation
Transformative innovations typically emerge from environments that foster intuition and creativity, rather than being forced by management. Management can only create a culture that encourages exploration and experimentation, and hope that the groundbreaking concepts needed will surface naturally.
From an outsider’s perspective, certain advancements may seem revolutionary, often due to the selective presentation of information. Organisations frequently safeguard their knowledge for reasons of national security or competitive advantage, concealing the inherent structural costs and complexities associated with these changes from society.
This dynamic explains why established companies often acquire start-ups. Although these incumbents typically pay a premium, sometimes overpaying due to inflated expectations, the true value of such innovations can be clouded by hype. Moreover, a more cynical view suggests that some innovations may pose risks to the cash flow of existing business models, rendering them too disruptive for established players to allow.
The motor vehicle industry illustrates these innovation dynamics clearly. Major manufacturers released the current generation of competing electric vehicles, cars that closely resemble their internal combustion predecessors, almost simultaneously. Yet, electric vehicles are not new. In postwar Japan, gasoline scarcity spurred government support for electric cars, including the 1947 Tamahttps://www.nissan-global.com/EN/HERITAGE_COLLECTION/tama_electric.html, now in Nissan’s museum. Similarly, Britain’s electric milk floats were in service for decades. These examples demonstrate that innovation frequently revives older ideas in response to changing constraints, yet they are presented to society as completely new solutions.
5. Why This Matters for Policymakers
Fundamentally, policymakers should be aware of this for three reasons:
-
Sustainability Planning: If innovation cannot scale indefinitely, strategies must shift toward resilience, redundancy, and sufficiency, not just efficiency or techno-optimism.
-
Public Investment: Governments should ask whether additional R&D funding yields proportional benefits, or whether alternative investments (education, community infrastructure, circular economies) may offer greater long-term value.
-
Risk Management: Overreliance on future breakthroughs can delay necessary structural reforms. Policymakers must balance possibility with probability.
6. Conclusion: Innovation Is Real, but So Are Its Limits
Innovation is not “dead,” but its return on investment is diminishing, and its complexity is growing. Recognising this reality is not anti-science; it’s a vital step toward a smarter, more resilient society. We must support research, yes, but also invest in systems that can thrive even when innovation slows. To rely on innovation to provide solutions to problems is a mistake.
In an age of finite resources, the most responsible course is one that blends creativity with prudence, and optimism with a clear-eyed view of complexity.