Recent philosophical literature has turned its attention towards assessments of how to judge scientific proposals as worthy of further inquiry. Previous work, as well as papers contained within this special issue, propose criteria for pursuitworthiness (Achinstein, 1993; Whitt, 1992; DiMarco & Khalifa, 2019; Laudan, 1977; Shan, 2020; Šešelja et al., 2012). The purpose of this paper is to assess the grounds on which pursuitworthiness demands can be legitimately made. To do this, I propose a challenge to the possibility of even (...) minimal criteria of pursuitworthiness, inspired by Paul Feyerabend. I go on to provide a framework for identifying the contexts in which pursuitworthiness criteria may promote the efficiency of scientific inquiry. I then spell out some implications this framework has for values and pursuit. (shrink)

Decisions where there is not enough information for a well-informed decision due to unidentified consequences, options, or undetermined demarcation of the decision problem are called decisions under great uncertainty. This paper argues that public policy decisions on _how_ and _if_ to implement decision-making processes based on machine learning and AI for public use are such decisions. Decisions on public policy on AI are uncertain due to three features specific to the current landscape of AI, namely (i) the vagueness of the (...) definition of AI, (ii) uncertain outcomes of AI implementations and (iii) pacing problems. Given that many potential applications of AI in the public sector concern functions central to the public sphere, decisions on the implementation of such applications are particularly sensitive. Therefore, it is suggested that public policy-makers and decision-makers in the public sector can adopt strategies from the argumentative approach in decision theory to mitigate the established great uncertainty. In particular, the notions of framing and temporal strategies are considered. (shrink)

The phenomenon of interactive human kinds, namely kinds of people that undergo change in reaction to being studied or theorised about, matters not only for the reliability of scientific claims, but also for its wider, sometimes harmful effects at the group or societal level, such as contributing to negative stigmas or reinforcing existing inequalities. This paper focuses on the latter aspect of interactivity and argues that scientists studying interactive human kinds are responsible for foreseeing harmful effects of their research and (...) for devising ways of mitigating them. (shrink)