Uygun Tunc, Duygu and Tunc, Mehmet Necip
(2025)
Is the value-free ideal of science untenable? Part I: Inductive risk.
[Preprint]
![[img]](https://philsci-archive.pitt.edu/style/images/fileicons/text.png) |
Text
Does inductive risk make the value-free ideal of science untenable_preprint.pdf
Download (317kB)
|
Abstract
The inductive risk argument challenges the value-free ideal of science by asserting that scientists should manage the inductive risks involved in scientific inference through social values, which consists in weighing the social implications of errors when setting evidential thresholds. Most of the previous analyses of the argument fall short of engaging directly with its core assumptions, and thereby offer limited criticisms. This paper critically examines the two key premises of the inductive risk argument: the thesis of epistemic insufficiency, which asserts that the internal standards of science do not suffice to determine evidential thresholds in a non-arbitrary fashion, and the thesis of legitimate value-encroachment, which asserts that non-scientific value judgments can justifiably influence these thresholds. A critical examination of the first premise shows that the inductive risk argument does not pose a unique epistemic challenge beyond what is already implied by fallibilism about scientific knowledge, and fails because the mere assumption of fallibilism does not imply the untenability of value-freedom. This is demonstrated by showing that the way in which evidential thresholds are set in science is not arbitrary in any sense that would lend support to the inductive risk argument. A critical examination of the second premise shows that incorporating social values into scientific inference as an inductive risk-management strategy faces a meta-criterion problem, and consequently leads to several serious issues such as wishful thinking, category mistakes in decision making, or Mannheim-style paradoxes of justification. Consequently, value-laden strategies for inductive risk management in scientific inference would likely weaken the justification of scientific conclusions in most cases.
Monthly Views for the past 3 years
Monthly Downloads for the past 3 years
Plum Analytics
Actions (login required)
 |
View Item |
![[feed]](http://philsci-archive.pitt.edu/style/images/feed-icon-32x32.png){kind=icon}