Motivating Causal Layered Analysis of Scientific Practices

The philosophy of science has improved our understanding of science, but this understanding has not been developed into future-oriented thinking. However, there are many interesting connections and similarities between the philosophy of science and causal layered analysis. Explicating these connections and similarities makes it possible to open “up the present and past to create alternative futures” and to reveal “deep worldview committments behind surface phenomena” (Inayatullah 1998, 815) with respect to the possible futures of science.

Opening up the present and past of science to create alternative futures and revealing deep worldview commitments with respect to science and the future of science is important for three reasons.

First, science has changed considerably during its history. Not only have the contents, methods, goals, and assumptions changed but so have its technological, social, and cultural settings. Moreover, many, if not most, aspects of science are dependent on these settings. The technological, social, and cultural settings are in constant flux and it seems reasonable to conjecture that the rate of technological, social, and cultural change will increase in the 21st century. The conclusion, that (at least some aspects of) science will therefore also change in the future, follows immediately.

Surprisingly, very little has been said about the estimating of possible futures of science (or sciences, to be exact). Only fragmented lines of thoughts concerning the estimating of the future of science are present in the literature.[1] While there are many reports (e.g. EU; NATO) that summarize possible future topics and methods in science, there has been very little reflection on how the future of science can be estimated. As the philosophy of science has shown, science is opaque and difficult to understand. Given the opaqueness, the reports concerning the future of science appear hopelessly simplistic without reflection on the conceptions of science that they embrace. The problem is that the philosophy of science has not been much of a help here. Even though history and the philosophy of science have deepened our understanding of science, explicit conceptual tools to understand the estimating of possible futures of science are missing from its repertoire. Connecting CLA and philosophy of science is one possible way to improve the situation.

A similar blind spot with respect to science can be found within futures research. No systematic account of the development of scientific practices from the past to the future exists. Scientific practices consist of an intertwined web of theories, models, concepts, ontological assumptions, values, methods, instruments, communication, and so on. The nature of the different items on the list varies between different times and different scientific subfields. The complexity and heterogeneity that characterizes science and its history are difficult to tame intellectually. Still, the idea of a “modern science” as some sort of a monolith dominates futures research. For example, Inayatullah writes, in connection to CLA, about “alternative sciences” and argues that “Part of futures studies, then, is dramatically rethinking our categories, including the category of the empirical. Instead of one science, an interpretive perspective allows for a world of many sciences, of many ways of knowing the real. Each culture can have its own science, its own view of the real.” (2004, 65). Now, assume that the category of science is transcultural and transhistorical (which is debatable, see Daston 2009; Dear 2012; Cunningham 1988). Even then the question about alternative sciences is not limited to intercultural comparisons. There are many important questions concerning the nature, history, and future of the complex phenomena we are accustomed to calling “science” and which has been the main subject of study in the philosophy and history of science and science studies. In terms of CLA itself, the existence of some monolith science is a myth that is often repeated and that hinders us from understanding science-related issues in the futures research. In order to remedy this dominance of the myth, we need to make systematic inquiries into the nature and development of science from a future-oriented perspective.

Secondly, the future of science is too important a topic to be left without attention. Not only funding decisions and science policy depend on some estimates of how science can develop but also – and more importantly – our ability to understand the future of society in general. There are countless ways in which the future of science and the future of conceptions of science affect society: What technologies we have (e.g. EU; NATO), who we consider as epistemic authorities (e.g. Mede & Schäfer 2020), how we perceive the human-nature relations (e.g. Allen 2018), how to generate novel innovations (e.g. Kuhlman & Rip 2018), and so on. Our ability to anticipate and prepare for changes in such areas depends on our ability to estimate the future of science. Simplistic pictures of science will not enable us to achieve this goal any more than simplistic pictures about other areas of life. We need deep understanding about the nature and development of science and we have to critically analyze our conceptions of science.

Thirdly, systematic inquiry into the nature and development of science and our conceptions of science is necessary in order to develop sound self-understanding about the nature of futures research as a field of research. It is rather difficult to locate futures research among different sciences if we do calmly analyze the nature and development of those sciences and the conceptions that guide our judgements about scientificity. For example, there is a recent argument according to which “Futures and foresight is still considered a pseudoscience. But the advantage of scientific theory development is that it can transform a pseudoscience into a science over time [–]. The choice remains to us of whether we want to do so” (Fergnani and Chermack 2021, 13). This argument is accompanied by a simplified model of theory-development (ibid., 6). The argument resembles old-fashioned debates concerning the demarcation problem which did not turn out to be solvable or fruitful (See Laudan 1983; Boudry & Pigliucci 2013). In most cases, a simple definition of science leaves out clear cases of science or counts as science cases that are not scientific. Therefore, the definitions do not significantly improve our understanding about the nature of science. For example, if science, by definition, must build theories, then molecular biology is not a science as “[m]olecular biologists discover and explain by identifying and elucidating mechanisms, such as DNA replication, protein synthesis, and the myriad mechanisms of gene expression. The phrase “theory of molecular biology” was not used above and for good reason; general knowledge in the field is represented by diagrams of mechanisms.” (Tabery, Piotrowska and Darden 2021, §2.1.) Even though it is not my main task to analyze the nature of futures research but the estimating of the futures of science, the use of CLA and philosophy of science together can make it obvious how complex and multilayered task it is to locate different branches of futures research among other fields of research. This improves the self-understanding of the field. Ironically, the futures research has revealed how complex a task it is to locate human activities into temporal cultural and social systems, but this understanding has not been widely reflected back on the debates about the nature of the field itself and the associated conceptions of science.


Allen, B. (2018). “Strongly Participatory Science and Knowledge Justice in an Environmentally Contested Region”. Science, Technology, & Human Values. 2018;43(6):947-971.

Boudry, Maarten & Pigliucci, Massimo (2013). Philosophy of Pseudoscience: Reconsidering the Demarcation Problem. University Of Chicago Press.

Cunningham, Andrew (1988). “Getting the game right: Some plain words on the identity and invention of science”. Studies in History and Philosophy of Science Part A 19 (3). 365–389.

Daston, Lorraine (2009). ”Science Studies and the History of Science”. Critical Inquiry 35 (4). 798–813.

Dear, Peter (2012). “Science Is Dead; Long Live Science.” Osiris 27 (1). 37–55

EU = Weak signals in Science and Technologies 2019: Analysis and recommendations.

Fergnani, A., & Chermack, T. J. (2021). “The resistance to scientific theory in futures and foresight, and what to do about it”. Futures and Foresight Science (forthcoming).

IFTF. (2006). Science and Technology Outlook: 2005-2055. Palo Alto: Institute for the Future.

Inayatullah, Sohail (1998). “Causal Layered Analysis. Poststructuralism as Method”. Futures, Vol. 30, No. 8, pp. 815–829.

Inayatullah, Sohail (ed.) (2004). The Causal Layered Analysis (CLA) Reader.

Kuhlmann, Stefan & Rip, Arie (2018), Next-Generation Innovation Policy and Grand Challenges, Science and Public Policy, 45 (4), 448-454,

Laudan, Larry (1983). “The Demise of the Demarcation Problem”. Cohen, R. S. & Laudan, L. Physics, Philosophy and Psychoanalysis. Springer Netherlands.

MacIntyre, Alasdair (2007). After Virtue. A Study of Moral Theory. Third edition. University of Notre Dame Press. 2007.

Martin, B.R. (1995). “Foresight in science and technology”. Technology Analysis & Strategic Management, 7 (2), 139-168.

Mede N & Schäfer M. “Science-related populism: Conceptualizing populist demands toward science”. Public Understanding of Science. 2020;29(5):473-491.

NATO = Science & Technology Trends 2020-2040. Exploring the S&T Edge.

Popper, Karl (1957). The Poverty of Historicism. Routledge.

Rescher, Nicholas (1999). The Limits of Science. University of Pittsburgh Press.

Small, Henry & Boyack, Kevin W & Klavans, Richard (2014). “Identifying emerging topics in science and technology”. Research Policy 43 (8). 1450-1467.

Tabery, James, Monika Piotrowska, and Lindley Darden, “Molecular Biology”, The Stanford Encyclopedia of Philosophy (Spring 2021 Edition), Edward N. Zalta (ed.), URL = <>.

Tromp, Coyan (2018). Wicked Philosophy. Philosophy of Science and Vision Development for Complex Problems. Amsterdam University Press.

[1] E.g. IFTF. (2006); Rescher (1999); Martin (1995); McIntyre (2007); (Popper 1957); Small et al. (2014); Tromp (2018).

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