There is increasing attention to the centrality of idealization in science. One common view is that models and other idealized representations are important to science, but that they fall short in one or more ways. On this view, there must be an intermediary step between idealized representation and the traditional aims of science, including truth, explanation, and prediction. Here I develop an alternative interpretation of the relationship between idealized representation and the aims of science. In my view, continuing, widespread idealization (...) calls into question the idea that science aims for truth. I argue that understanding must replace truth as the ultimate epistemic aim of science. Additionally, science has a wide variety aims, epistemic and non-epistemic, and these aims motivate different kinds of scientific products. Finally, I show how these diverse aims---all rather distant from truth---result in the expanded influence of social values on science. (shrink)

This paper argues that the appraisal of theory is in important respects closer in structure to value-judgement than it is to the rule-governed inference that the classical tradition in philosophy of science took for granted.

The question of the relationship of the making of value judgments in a typically ethical sense to the methods and procedures of science has been discussed in the literature at least to that point which e. e. cummings somewhere refers to as “The Mystical Moment of Dullness.” Nevertheless, albeit with some trepidation, I feel that something more may fruitfully be said on the subject.

Although epistemic values have become widely accepted as part of scientific reasoning, non-epistemic values have been largely relegated to the "external" parts of science (the selection of hypotheses, restrictions on methodologies, and the use of scientific technologies). I argue that because of inductive risk, or the risk of error, non-epistemic values are required in science wherever non-epistemic consequences of error should be considered. I use examples from dioxin studies to illustrate how non-epistemic consequences of error can and should be considered (...) in the internal stages of science: choice of methodology, characterization of data, and interpretation of results. (shrink)

Most people working on linguistic meaning or communication assume that semantics and pragmatics are distinct domains, yet there is still little consensus on how the distinction is to be drawn. The position defended in this paper is that the semantics/pragmatics distinction holds between encoded linguistic meaning and speaker meaning. Two other ‘minimalist’ positions on semantics are explored and found wanting: Kent Bach’s view that there is a narrow semantic notion of context which is responsible for providing semantic values for a (...) small number of indexicals, and Herman Cappelen and Ernie Lepore’s view that semantics includes the provision of values for all indexicals, even though these depend on the speaker’s communicative intentions. Finally, some implications are considered for the favoured semantics/pragmatics distinction of the fact that there are linguistic elements which do not contribute to truth-conditional content but rather provide guidance on pragmatic inference. (shrink)

: The underdetermination argument establishes that scientists may use political values to guide inquiry, without providing criteria for distinguishing legitimate from illegitimate guidance. This paper supplies such criteria. Analysis of the confused arguments against value-laden science reveals the fundamental criterion of illegitimate guidance: when value judgments operate to drive inquiry to a predetermined conclusion. A case study of feminist research on divorce reveals numerous legitimate ways that values can guide science without violating this standard.

Mathematics is often taken to play one of two roles in the empirical sciences: either it represents empirical phenomena or it explains these phenomena by imposing constraints on them. This article identifies a third and distinct role that has not been fully appreciated in the literature on applicability of mathematics and may be pervasive in scientific practice. I call this the “bridging” role of mathematics, according to which mathematics acts as a connecting scheme in our explanatory reasoning about why and (...) how two different descriptions of an empirical phenomenon relate to each other. I discuss two bridging roles appearing in biological and physical explanations. (shrink)

This paper looks at philosophical questions that arise in the context of AI alignment. It defends three propositions. First, normative and technical aspects of the AI alignment problem are interrelated, creating space for productive engagement between people working in both domains. Second, it is important to be clear about the goal of alignment. There are significant differences between AI that aligns with instructions, intentions, revealed preferences, ideal preferences, interests and values. A principle-based approach to AI alignment, which combines these elements (...) in a systematic way, has considerable advantages in this context. Third, the central challenge for theorists is not to identify ‘true’ moral principles for AI; rather, it is to identify fair principles for alignment that receive reflective endorsement despite widespread variation in people’s moral beliefs. The final part of the paper explores three ways in which fair principles for AI alignment could potentially be identified. (shrink)

Recent efforts to argue that nonepistemic values have a legitimate role to play in assessing scientific models, theories, and hypotheses typically either reject the distinction between epistemic and nonepistemic values or incorporate nonepistemic values only as a secondary consideration for resolving epistemic uncertainty. Given that scientific representations can legitimately be evaluated not only based on their fit with the world but also with respect to their fit with the needs of their users, we show in two case studies that nonepistemic (...) values can play a legitimate role as factors that override epistemic considerations in assessing scientific representations for practical purposes. (shrink)

We examine the problem of generating definite noun phrases that are appropriate referring expressions; that is, noun phrases that (a) successfully identify the intended referent to the hearer whilst (b) not conveying to him or her any false conversational implicatures (Grice, 1975). We review several possible computational interpretations of the conversational implicature maxims, with different computational costs, and argue that the simplest may be the best, because it seems to be closest to what human speakers do. We describe our recommended (...) algorithm in detail, along with a specification of the resources a host system must provide in order to make use of the algorithm, and an implementation used in the natural language generation component of the IDAS system. (shrink)

I suggest that civility is the display of respect, tolerance, or considerateness. Social norms enable us to successfully display these basic moral attitudes, and social consensus sets the bounds of civility, i.e., what views and behaviors are not owed a civil response. Because tied to social norms, there is no guarantee that standards of civility will exempt us from civilly responding to what, from a socially critical moral point of view, is tolerable. I raise and addresses the question: How could (...) civility be a moral virtue if it is so thoroughly governed by social norms? (shrink)

Two concepts of truth as correspondence of ideas with facts are analyzed. One of them is the thought-external fact relation, and the other is the fact-proposition one. The two maps are then composed, and the resulting map is assumed to formalize the concept of truth as adequacy or correspondence of ideas to facts. Besides, some desiderata for a correspondence theory of partial truth are proposed. Finally, the truth criteria employed in science and technology are recalled.

The ever-increasing application of algorithms to decision-making in a range of social contexts has prompted demands for algorithmic accountability. Accountable decision-makers must provide their decision-subjects with justifications for their automated system’s outputs, but what kinds of broader principles should we expect such justifications to appeal to? Drawing from political philosophy, I present an account of algorithmic accountability in terms of the democratic ideal of ‘public reason’. I argue that situating demands for algorithmic accountability within this justificatory framework enables us to (...) better articulate their purpose and assess the adequacy of efforts toward them. (shrink)

The underdetermination argument establishes that scientists may use political values to guide inquiry, without providing criteria for distinguishing legitimate from illegitimate guidance. This paper supplies such criteria. Analysis of the confused arguments against value-laden science reveals the fundamental criterion of illegitimate guidance: when value judgments operate to drive inquiry to a predetermined conclusion. A case study of feminist research on divorce reveals numerous legitimate ways that values can guide science without violating this standard.

The debate about the rational and the social in science has sometimes been developed in the context of a distinction between epistemic and non-epistemic values. Paying particular attention to two important discussion in the last decade, by Longino and by McMullin, I argue that a fuller understanding of values in science ultimately requires abandoning the distinction itself. This is argued directly in terms of an analysis of the lack of clarity concerning what epistemic values are. I also argue that the (...) philosophical import of much of the feminist work in philosophy of science is restricted by any kind of strict adherence to the distinction. (shrink)

One of the main reasons that liberal democratic societies are not ill-prepared to confront the present challenge presented by disaffection with democratic institutions, is that the type of political theory currently in vogue is dominated by an individualistic, universalistic, and rationalistic framework. This erases the dimension of the political and impedes envisaging in an adequate manner the nature of a pluralistic democratic public sphere. This paper examines the most recent paradigm of liberal democracy: 'deliberative democracy', in order to bring to (...) the fore its shortcomings. Then, the authos puts forward some element for the elaboration of an alternative model that she proposes to call 'agonistic pluralism'. (shrink)

Scientists and laypeople alike use the sense of understanding that an explanation conveys as a cue to good or correct explanation. Although the occurrence of this sense or feeling of understanding is neither necessary nor sufficient for good explanation, it does drive judgments of the plausibility and, ultimately, the acceptability, of an explanation. This paper presents evidence that the sense of understanding is in part the routine consequence of two well-documented biases in cognitive psychology: overconfidence and hindsight. In light of (...) the prevalence of counterfeit understanding in the history of science, I argue that many forms of cognitive achievement do not involve a sense of understanding, and that only the truth or accuracy of an explanation make the sense of understanding a valid cue to genuine understanding. (shrink)

As Aristotle stated, scientific explanation is based on deductive argument--yet, Wesley C. Salmon points out, not all deductive arguments are qualified explanations. The validity of the explanation must itself be examined. _Four Decades of Scientific Explanation_ provides a comprehensive account of the developments in scientific explanation that transpired in the last four decades of the twentieth century. It continues to stand as the most comprehensive treatment of the writings on the subject during these years. Building on the historic 1948 essay (...) by Carl G. Hempel and Paul Oppenheim, "Studies in the Logic of Explanation,” which introduced the deductive-nomological model on which most work on scientific explanation was based for the following four decades, Salmon goes beyond this model's inherent basis of describing empirical knowledge to tells us “not only _what,_ but also _why_.” Salmon examines the predominant models in chronological order and describes their development, refinement, and criticism or rejection. _Four Decades of Scientific Explanation_ underscores the need for a consensus of approach and ongoing evaluations of methodology in scientific explanation, with the goal of providing a better understanding of natural phenomena. (shrink)