High technology, frontier technology, and so on, appear crucial underpinnings of foresight. The OECD talks about “synthetic biology, artificial intelligence, robotics and quantum technologies” as the pivotal exemplars (although others cite a wider range – in my view, Dr. Clovis Friere’s team at UN Trade and Development have produced the most sophisticated version on the “official” side).
Foresight as we typically know it relies on a kind of undeclared ex-ante technological determinism that makes specific assumptions about the sources of invention – recent, goal-directed, science as a primary authorial force of change. The importance of recency and goal-direction are very important. If the science on which “the future” is based were more than a few years old, but had slipped from memory, it would not be picked up. Furthermore, even if the science were to be recent, but did not name the explicit application in mind, it would remain undetected.
While it might involve occasionally consultation with citizens on the desirability of its predictions (inclusive foresight), the approach fundamentally boils down to scanning the English-language scientific literature, alongside consultation with prominent academics in relevant fields, typically from the USA or, at the least, the Global North.
The underlying mental model is at least decades old. It was given clear expression in reports such as «Sources of Medical Technology: Universities and Industry» published in 1995 by the US National Academy of Science. The model, furthermore, reflects its origins inside the US military-industrial complex and American Cold War and post-Cold War capitalism. The centrality of Moore’s Law, the idea emerging from Silicon Valley that transistors could be packed onto chips at every greater density, intentionally, as a business strategy, is one aspect of this doctrine, but not the only one.
I am not going to summarize the complex intellectual history of foresight (e.g., Eglė Rindzevičiūtė, 2023, The Will to Predict: Orchestrating the Future through Science). But I think there are two obvious twists to consider in regards to the discussion. The first is that the present model is often conservative and even reactionary in that it imagines social and economic relations remaining the same. A progressive future without billionaires, for example, is not conceived (but if it were to be, it is highly unlikely that a genuinely social democratic society would fund science and research in the same way, thereby implying different “technological” futures).
A second is that foresight makes heroic assumptions about the sources of innovation, namely, that recent, goal-directed, science is becoming an ever-more dominant source. This is an unstudied assumption. We know that innovation emerged from many different sources, including trial and error, reverse engineering, prototyping, as well as generally unspecified phenomena like tinkering, strokes of genius, flashes of insight, false premises, etc. A credible foresight process would, therefore, have to develop a more even-handed understanding of innovation.
My goal is not to dismiss ax-ante technological determinism as worthless; rather to argue it gives us a window into the state of mind of particular elites, no more, no less. But the practical question is whether that view gives us a plausible sense of how the material world is changing, and how it might change in the future, and on this point I believe it could do better.
Melt-blown polypropylene, invented in the 1950s and later used for cigarette filters, was the core technology for face masks that found mass use during the COVID pandemic (and later against dust, pollen, air pollution and facial sunburn). While, of course, infectious disease experts predicated a pandemic, I am not aware of any foresight process that anticipated melt-blown polypropylene as a crucial material factor (unless anyone knows better). Therefore, we need to ask ourselves how we could design a foresight methodology that would plausibly detect similar phenomena in the future.
Updating the current approach
David Edgerton’s book Shock of the Old: Technology and Global History since 1900, never produced the kind of deep reflection that could have improved foresight processes in the ways I am suggesting (beyond relatively marginal commentary such as noted in the table beneath). The “lessons” of that book, such as they are remembered, tend to be generic, namely, “risks” of conflating “innovation” with “technology” and “innovation” with “use”.
Policy commentary that sought inspiration from Shock of the Old (examples)
| Source | Commentary |
|---|---|
| Smith, 2021, Observations on electric vehicle’s first hurrah – horse, steam and electric tram technology adoption rates in the UK 1860s to 1960s (Australasian Transport Research Forum) | “The technical limitations of new technologies and the barriers that need to be overcome to replace incumbent technologies can be quickly forgotten. Also missed is the success and persistence of older and intermediary technologies, the interplay between old and new technologies and the multiple factors that need to be in place to support a new technology transition.” |
| Marr, et al., 2019, Identifying the Mode and Impact of Technological Substitutions, in: IEEE Access* | “Edgerton has contested the role of ‘bleeding-edge’ technologies, noting that conventional technologies have a remarkably long shelf-life, sustained impact, and are capable of resurgence…Taking [Edgerton’s] notions of non-linear development into account…this study focuses specifically on failures relating to the ever more demanding performance expectations that human users impose on their technologies.” |
| Zimmer-Merkle and Fleischer, 2017, Eclectic, random, intuitive? Technology assessment, RRI, and their use of history, in: Journal of Responsible Innovation | “Typically, producers of anticipatory knowledge randomly employ an intuitive handling of the historicity of their subject matter; when it comes to the selection of literature they proceed eclectic…we call for a more deliberated treatment of ‘historical knowledge'” |
| Joly, 2015, Governing emerging technologies – the need to think out of the (black) box, in: Science and Democracy- Making Knowledge and Making Power in the Biosciences and Beyond | “[I]t is necessary to shift from attention to novelty to a heuristic of continuity, and from a focus on uncertainties to attention to what we know. The second idea is that we have to pay attention to the diversity of processes occurring at different scales, since such processes and their interactions are at the core of the emergence of a technology. Applying both ideas, we end up with an attempt to identify the main characteristics of current emerging technologies.” |
| Rejeski, 2011, Public policy on the technological frontier, in: The Growing Gap Between Emerging Technologies and Legal-Ethical Oversight | “The organizational challenge is dealing with three types of technologies simultaneously: old technologies from the past, old technologies combined in new ways, and the truly new and novel.” |
I believe a deeper reflection would have been helpful with a view to developing a practical new approach to foresight. This would have required collaborative work by many people over years and is unfortunately not something that I can produce. Nevertheless, I would try to make some suggestions about how we could operationalize these points in terms of foresight methodology. As the citations in the table above suggest, the following general notions might be helpful:
- Understanding the relationships between old and “new” devices as they make up our material world and how these relationships might change in the future.
- Historical metaphors intended to inform foresight that draw on insights from a range of perspectives among professional historians (rather than uninformed assumptions).
- Asking why our material world changes over time; identifying the main characteristics of these changes.
Furthermore, I would also consider some other specific points:
- The face masks example suggests the need to think through the objects that are important in our daily lives as well as objects that are likely to become important in foreseeable crises, and then ask how these objects are made and how the way they are made is changing. The latter is a difficult question to answer because we lack a schematic understanding of production; although, of course, experts in each industry are likely to have some answers, they may not wish to share them as the answers have commercial value. Analysis is primarily a task of synthesizing what is already known.
- Challenging the idea that there is a single frontier of science and technology; rather, a more complicated picture prevails. The wide availability of regional scientific databases (see table beneath), as well as online translation, means we can read widely from the comfort of our desks. The mindset of the analyst is also important, avoiding both overblown “high technology” as well as racist “appropriate technology” paradigms but, rather, letting frameworks emerge from what they are reading.
- The politics of horizon scanning often skews right reflecting its origins in the military industrial complex and dominant American forms of capitalism. Progressive political change is therefore typically excluded from analyses because it is politically unpalatable, for example, the idea of resurgent social democracy. Yet, politics interacts with the dimensions of science and research. For example, socialized medicine, as opposed to privatized medicine, might suggest different innovations.
- Asking how innovation has operated in the past, how it operates today, and how it might operate in the future. Again, this is a very difficult question to answer. If the answer was known we would already all be rich. “The paradigm of artisanal research” in L’horizon des sciences en Afrique by Yaovi Akakpo opens up the question but, in truth, relevant literature is vast.
Regional science databases by continent (examples)
| Scholarly papers | “Grey” literature | |
|---|---|---|
| Africa | AfricaBib (closed 2026), *AJOL, Langaa RPCIG, “National Science and Technology Forum Awards” (since 1998) | ACTS |
| Americas | Google Scholar, PubMed, SciELO | |
| Asia | *CNKI, GARUDA, Indian Journals, KoreaScience, J-GLOBAL, Science and Technology Policy Commons, VIP, Wangfang Data, “Top Ten Advances in Chinese Science” (since 2005) | ASEAN Centre for Energy, CNAIS, CSTEP, ThinkAsia |
| Europe | CAIRN.INFO, CEEOL, DigiZeitschriften (closed 2025), LIVIVO, Rivisteweb | Think Tank Review |
Ex-ante technological determinism
Given what I have said, it seems surprising, at least to me, that the ex-ante technological determinism I described above is expressed with such confidence. Indeed, the quality of foresight might well be falling even compared to older European initiatives like the legendary “FAST”. Therefore, the question arises as to why.
It is clear that certain devices have geopolitical potency, i.e., they draw the attention of politicians, who claim oracular powers in seeing a rosy future in which these technologies play an important role.
Attempting a rational explanation: that these technologies are felt to be “bargaining chips” in a partly symbolic, partly real, war, which plays out in the minds of elites. This must surely derive from the fact that the idea of science and technology has been shaped by the US military-industrial complex to such a degree that they cannot, as it were, see the wood from the trees.
Advances in technique, once assimilated into society have also fudged the distinction between “war” and “peace” creating uncertainty about their respective meanings which affects the forming of policy…The fudging…raises an entire range of complex problems. Industrialization during the last [19th] century increased the options open to policy; it has now reached the point of multiplying the ambiguities.
Pearton, 1982, The Knowledgeable State: Diplomacy, War, and Technology since 1830, p. 258
Therefore – almost like we are living in the Sun Tzu classic of “all warfare is based on deception” (which, indeed, fascinates Western military planners) – rhetoric and reality intermingle in the overall presentation. A quantum computer does not exist, but talking about it makes an impression. Ultimately, it is unclear who is deceiving whom, or even what is at stake: a tainted intellectual environment where it is easy to lose grip on reality.
The closest I read in terms of a recent synthesis was Warren Chin’s pessimistic account, War, Technology and the State. Chin based the book on a course he taught to military officers. Obviously there is a library of other relevant literature on the sociology of technology.
David Edgerton also regularly reminds us to avoid the word « technology » and describe what we are actually talking about. This is an important point. We can think about why we would lump together such distinct inventions as “technology”. Frontier technology is often based on claimed abilities to bend the emergent properties of silicon (computers) and carbon (biotech) to human will. But the objects themselves have little obvious commonality in physical terms. A computer is not an enzyme, for example. These thoughts, to my mind, raise telling economic and political questions that have an historical basis, such as common ancestry in the petrochemical industry (Mody, 2023). Common ancestry is also revealed in material terms.
This page is likely to change as my reading expands.
Notes:
Lu Gao, 2026, Rethinking global technology governance at a crossroads: China’s role, historical turning points and future imaginaries, in: Cultures of Science
Deirdre Nansen McCloskey and Alberto Mingardi, 2020, The Myth of the Entrepreneurial State (American Institute for Economic Research). The right take a maverick stance, stalling intellectual debate on the left.
van der Vleuten, 2020, History and technology in an age of” Grand Challenges”: raising questions, in: Technology and Culture. Tensions of Europe “transnational scholarly network and hub for transnational research, education and outreach initiatives on history, technology and Europe”.
Neri, 2020, The Risk Perception of Artificial Intelligence
Regina Lee Blaszczyk and Ben Wubs (eds.), 2018, The Fashion Forecasters: a Hidden History of Color and Trend Prediction
Nordmann, et al. (eds.), 2014, Science Transformed?: Debating Claims of an Epochal Break
Wilkie, 2010, Prototypes in design: materializing futures, in: Protoyping Prototyping
Rosalind Williams, 2003, Retooling: a Historian Confronts Technological Change
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