The Hard Problem of Future of Science

There exist a serious concern of whether possible futures of science can be estimated at all. The main argument against such a possibility stems from the idea that important scientific results involve conceptual innovations that cannot be predicted: if we could predict those conceptual innovations, we would already have the new conceptual apparatus (McIntyre 2007, Finocchiaro 1973) – otherwise we are not even able to formulate what, exactly, we are predicting. For example, if someone predicted, in 1901, that the general theory of relativity will be formulated, that person would have known the Einstein field equations. Otherwise the person could not have specified in necessary detail what it is that will be formulated. And if the person already knew the field equations, the equations would no longer need a formulation.

In my view, this argument can be seen both as a conceptual puzzle (even as a “paradox”) and as an insight on the role of science in our attempts to understand the reality and our place in it. In this post, I will discus the latter perspective. My (initial) diagnosis of the argument proceeds by reducing it to a more general problem that concerns science as a source of knowledge in future estimations.

The problem is that science itself is a source of knowledge that is used in estimates of the future. The use of science as a source of knowledge is based on the assumption that it is a trustworthy and well-organized epistemological practice. However, the whole point of estimating the future of science depends on the view that science will change in the future. This means that in order for there to be estimations of possible futures of science  we need to assume both (i) that our science is well-organized and has achieved trustworthy results, and (ii) that there could be a science which achieves different results and/or is organized differently from the present science.

Of course, every science-based estimate is subject to uncertainty and possible improvement and therefore the assumption (i) does not generate any novel philosophical issues. In the ordinary estimation-tasks, the only thing that we can do is to assume that the present science is good enough or wait for more decisive results. However, estimating futures of science (EFS) is not that kind of ordinary estimation-task. The difference is that, in EFS, we are explicitly concerned with the possibility of there being a different science. We cannot just bypass the possibility of a different science as a fact of our fallibilistic life because that possibility is the very subject we are interested in. This makes the combination of (i) and (ii) more paradoxical in EFS than in ordinary estimation-tasks.

How to solve this paradox is one of the main themes that I will discuss in this blog. It is too wide a topic to be discussed in a single post. However, I would suggest (being biased by a background in philosophy of science) that the the way out from the paradox is to analyze theories of science (i.e. theories that describe how science works, not scientific theories themselves) and compare their relative merits in foresight activities. Theories of science are no less fallible than science itself and therefore we cannot choose one of the theories as “the truth” and use it to guide our estimations. Therefore, we need to study (i) to what extent a given theory of science allows us to estimate the future of science, and (ii) what kinds of futures are possible according to the theories. On the basis of (i) and (ii) we can critically analyze different scenarios concerning the future of science with respect to their contents and coherence.


Finnocchiaro, Maurice A (1973). History of Science as Explanation. Wayne State University Press.

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

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