This article discusses Sven Ove Hansson’s corpus model for the influence of values (in particular, non-epistemic ones) in the hypothesis acceptance/rejection phase of scientific inquiry. This corpus model is based on Hansson’s concepts of scientific corpus and science ‘in the large sense’. I first present Hansson’s corpus model of value influence with some introductory comments about its origins, a detailed presentation of the model with a new terminology, an analysis of its limits, and an appreciation of its handling of controversial (...) non-epistemic values. I conclude that it is a very good candidate for managing value influence, because contrary to other models in the literature it is fairly simple, it provides a universal and systematic procedure for dealing with values, and it syste- matically preserves the epistemic integrity of science. I then study some difficulties associated with the model’s central feature of taking the maximum level of evidence required by the applications of a claim in order for the latter to enter the scientific corpus: the difficulty to identify this maximum requirement; the non-optimality of this requirement with respect to other less demanding requirements; the potentially detrimental consequences of the preference for false negatives over false positives on which it relies; and the issue of whether there can nevertheless be requirements higher than this maximum. I show that these issues may potentially challenge the corpus model. Finally, I call for empirical work (in particular, an investigation of scientists’ and engineers’ own normative views) in order to better assess these issues. (shrink)

In their proof-of-concept study, Meier et al. built an algorithm to aid ethical decision making. In the limitations section of their paper, the authors state a frequently cited ax...

In this essay, I reflect on the implications of intellectual virtues in scientific endeavor. To this end, I first offer a depiction of scientific endeavor by resorting to the notion of academic attitude, which involves aspects concerning the generation and possession of knowledge. Although there are differences between these activities, they have in common the engagement of diverse intellectual agents (scientists). In this sense, I analyze how intellectual virtues are linked to 1) scientific research tasks, such as theory appraisal, and (...) 2) those tasks of vigilance and intervention in the uses of scientific knowledge. I conclude that intellectual virtues play a leading role in achieving higher quality scientific research and adequate foresight on the uses and impacts of scientific findings. In this order of ideas, I propose an agenda for further inquiries on these matters, highlighting the relevance of reflecting and empirically researching the relationship between intellectual virtues and science, as well as cultivating intellectual virtues in various stages of scientific training. (shrink)

The purpose of this paper is to discuss the responsibility of AI experts for guiding the development of AI in a desirable direction. More specifically, the aim is to answer the following research question: To what extent are AI experts responsible in a forward-looking way for effects of AI technology that go beyond the immediate concerns of the programmer or designer? AI experts, in this paper conceptualised as experts regarding the technological aspects of AI, have knowledge and control of AI (...) technology that non-experts do not have. Drawing on responsibility theory, theories of the policy process, and critical algorithm studies, we discuss to what extent this capacity, and the positions that these experts have to influence the AI development, make AI experts responsible in a forward-looking sense for consequences of the use of AI technology. We conclude that, as a professional collective, AI experts, to some extent, are responsible in a forward-looking sense for consequences of use of AI technology that they could foresee, but with the risk of increased influence of AI experts at the expense of other actors. It is crucial that a diversity of actors is included in democratic processes on the future development of AI, but for this to be meaningful, AI experts need to take responsibility for how the AI technology they develop affects public deliberation. (shrink)

The proper role of non-epistemic values such as moral, political, and social values in practices of justification of policy-relevant hypotheses has recently become one of the central questions in philosophy of science. This strand of research has yielded conceptual clarifications and significant insight into the complex and notoriously contentious issue of the proper relationship between science, non-epistemic values, and policymaking. A central part of this discussion revolves around whether scientists should aspire for the value-free ideal, according to which non-epistemic values (...) are unacceptable in the justification of hypotheses. By so doing, scientists can... (shrink)

This paper examines the conditions of trustworthy science advice mechanisms, in which scientists have a mandated role to inform public policymaking. Based on the literature on epistemic trust and public trust in science, we argue that possession of relevant expertise, justified moral and political considerations, as well as proper institutional design are conditions for trustworthy science advice. In order to assess these conditions further, we explore the case of temporary advisory committees in Norway. These committees exemplify a de facto trusted (...) and seemingly well-functioning science advice mechanism. Still, this mechanism turns out to poorly realize some central conditions of trustworthy science advice. From this we draw three lessons. Firstly, it remains crucial to distinguish between well-placed and de facto trust. Secondly, some conditions of trustworthy science advice seem more significant than others and there are thresholds for realizing each condition. Thirdly, not only does the institutional design and organization of science advice matter more than often recognized; the trust and trustworthiness of the broader social and political context and institutional environment make a difference as well. (shrink)

Machine learning and other forms of artificial intelligence can improve parts of clinical decision making regarding the gathering and analysis of data, the detection of disease, and the provis...

In this article we develop a pragmatist-inspired notion of intelligence that should lead to a better understanding of the notion of scientific expertise. The notion of intelligence is drawn from Dewey and is therefore used here in its technical sense. Our thesis is that scientific knowledge is a necessary but not sufficient condition for scientific expertise; intelligence should also be added. Conceived of as the capacity to apply general knowledge to particulars, we reach the conclusion that intelligence is a necessary (...) requirement for scientific experts in the wake of Dewey’s logic of inquiry. In particular, we argue that an all-important task that scientific experts are asked to accomplish, and which puts their expertise to the test, is to transform indeterminate situations into problematic situations, and that such a goal can only be achieved if scientific experts succeed in paying attention to all the contingent and precarious aspects that make the situation they face unique. (shrink)