I consider a problem for functional reductionism based on the following tension. Say that b is functionally reduced to a. On one hand, a and b turn out to be identical, and identity is a symmetric relation. On the other hand, functional reductionism implies that a and b are asymmetrically related: if b is functionally reduced to a, then a is not functionally reduced to b. Thus we ask, how can a and b be asymmetrically related if they are the same thing? I propose a solution to this tension by distinguishing between ontological levels and levels of description.

There has been much debate among scientists and philosophers about what it means for (hypothetical) interventions invoked in causal inference to be “well-defined” and how considerations of this sort should constrain the choice of causal variables. In this article, I propose that an intervention is well-defined just in case the effect of interest is well-defined, and that the intervention can serve as a suitable means to identify that effect. Based on this proposal, I identify several types of ambiguous intervention. Implications for variable choice are discussed using case studies drawn from the sciences.

While philosophers have focused on epistemological and ethical challenges of using artificial intelligence (AI) in science, scientists have focused largely on opportunities. I argue that this disconnect between philosophical pessimism and scientific optimism is driven by failures to critically examine the practice of AI-infused science. To appreciate the epistemic justification for AI-powered breakthroughs, philosophers must analyze the role of AI as part of a wider process of discovery. I demonstrate the importance of this with two cases from the scientific literature, and show that epistemic opacity need not diminish AI’s capacity to lead scientists to significant and justifiable breakthroughs.

Symmetry principles are a central part of contemporary physics, yet there has been surprisingly little metaphysical work done on them. This article develops the Wignerian treatment of symmetries as higher-order laws—metalaws—within a Humean framework of lawhood. Lange has raised two obstacles to Humean metalaws, and the article shows that the account has the resources available to respond to both. It is argued that this framework for Humean metalaws stands as an example of naturalistic metaphysics, able to bring Humeanism into contact with the practice of actual science without giving up on the central denial of necessary connections.

Those who wish to defend the role of aesthetic values in science face a dilemma: aesthetic language is either used metaphorically for what are ultimately epistemic features, or it is used literally, but the importance of such values for science is unclear. This article introduces a new account that gets around this problem by considering an overlooked source of aesthetic value in science: the relation between form and content. A fit between the content of a thought experiment and the way in which that content is formulated can have important epistemic payoffs by contributing to scientific understanding.

My aim here is (1) to argue that the usual argument for thinking that dysfunction has no place in a dispositionalist approach to functions is deeply flawed and (2) to develop a positive account of the explanatory role dysfunction attributions play in dispositionalist-style functional analysis. I also argue that while my account undermines one common motivation for preferring an etiological over a dispositionalist approach, perhaps more interestingly, it also blurs the boundary between the two and opens a path to unifying them.

Scientific disagreements are an important catalyst for scientific progress. But what happens when scientists disagree amid times of crisis, when we need quick yet reliable policy guidance? In this article, we provide a normative account for how scientists facing disagreement in the context of “fast science” should respond and how policy makers should evaluate such disagreement. Starting from an argumentative, pragma-dialectic account of scientific controversies, we argue for the importance of higher-order evidence (HOE), and we specify desiderata for scientifically relevant HOE. We use our account to analyze the controversy about the aerosol transmission of COVID-19.

Extant accounts of trust in science focus on reconciling scientific and public value judgments, but neglect the challenge of learning audience values. I argue that for scientific experts to be epistemically trustworthy, they should adopt a cooperative approach to learning about the values of their audience. A cooperative approach, in which expert and nonexpert inquirers iteratively refine value judgments, better achieves important second-order epistemic dimensions of trustworthiness. I suggest that strong objectivity in the feminist standpoint theoretic sense is sometimes a prerequisite for trustworthiness.

If categorical equivalence is a good criterion of theoretical equivalence, then it would seem that if some class of mathematical structures is represented as a category, then any other class of structures categorically equivalent to it will have the same representational capacities. Hudetz (2019a) has presented an apparent counterexample to this claim; in this note, I argue that the counterexample fails.

Many philosophers of science have recently argued that extra-academic participation in scientific knowledge production does not threaten scientific objectivity. Quite the contrary: Citizen science, participatory projects, transdisciplinary research, and other similar endeavours can even increase the objectivity of the research conducted. Simultaneously, researchers working in fields in which such participation is common have expressed worries about various ways in which it can result in biases. In this article I clarify how these arguments and worries can be compared, and how extra-academic participation can both increase and threaten the objectivity of the research conducted.

Errol Morris has claimed that Kuhn threw an ashtray at him during a dispute about some matter in the history of science. Morris also claims that Kuhn threw him out of the graduate program at Princeton for disagreeing with him. I argue that Morris’s attack on Kuhn contains some degree of hyperbole. Further, I present evidence that shows that Morris is mistaken about key events during this period. In fact, Kuhn was supportive of Morris in his pursuit of a career in the history of science.

I present new counterexamples to the asymmetry of grounding: we have prima facie reason to think that some conditional probabilities partially ground their inverse conditional probabilities, and vice versa. These new counterexamples may require that we reject the asymmetry of grounding or, alternatively, that we reject one or more of the assumptions (regarding, e.g., the correct interpretation of probability) that enable the counterexamples. Either way, by reflecting on these purported counterexamples to grounding asymmetry, we learn something important, either about the formal properties of grounding or about the nature of probability (or both).

The compatibility of the Gaia hypothesis with Darwinism is often challenged on the grounds that (1) to be potent, natural selection requires the existence of a population (whereas Gaia is a single entity), and (2) natural selection requires the entities forming a population to reproduce (whereas Gaia merely persists). However, using the Price equation, I argue, following others, that the Gaia hypothesis can fit squarely within a Darwinian framework because Gaia can exhibit adaptations if a process at a lower level (e.g., an ecosystem) can occur, and the notion of natural selection can be extended to accommodate evolution without reproduction.

There remains no consensus among social scientists as to how to measure and understand forms of information deprivation such as misinformation. Machine learning and statistical analyses of information deprivation typically contain problematic operationalizations which are too often biased towards epistemic elites’ conceptions that can undermine their empirical adequacy. A mature science of information deprivation should include considerable citizen involvement that is sensitive to the value-ladenness of information quality, and doing so may improve the predictive and explanatory power of extant models.

I develop an account of ecological role functions—the functions of species within ecosystems—that is informed by alternative regime phenomena in ecology. My account is a causal-role theory that includes a counterfactual sensitivity condition. The account tracks and explains a distinction ecologists make between functions and various activities that are not functions. My counterfactual sensitivity condition resolves the liberality problem often attributed to causal-role theories of function while also illuminating the explanatory centrality of role functions within ecology.

Piccinini’s usability constraint states that physical processes must have “physically constructible manifestation[s]” to be included in epistemically useful models of physical computation. But to determine what physical processes can be implemented in physical systems (as parts of computations), we must already know what physical processes can be implemented in physical systems (as parts of processes for constructing computing systems). We need additional assumptions about what qualifies as a building process. Piccinini implicitly assumes a classical computational understanding of executable processes, but this is an assumption imposed on physical theories and may artificially limit our picture of epistemically useful physical computation.

The cosmological constant problem stems from treating quantum field theory and general relativity as an effective field theory (EFT). We argue that the problem is a reduction ad absurdum and that one should reject the assumption that general relativity can generically be treated as an EFT. This marks a failure of naturalness and provides an internal signal that EFT methods do not apply in all spacetime domains. We then take an external view, showing that the assumptions for using EFTs are violated in general relativistic domains where Λ is relevant. We highlight some ways forward that do not depend on naturalness.

Experiences of racial discrimination can seem to be caused by one’s race, a combination of social identities, or non-social features. In other words, racial discrimination can be intersectional or attributionally ambiguous. This poses challenges for current understandings and measurement tools of racial discrimination in public health research, such as the explanation of racial health disparities. Different kinds of discriminatory experiences plausibly produce different psychological effects that mediate their negative health impacts. Thus, multiple characterizations and measurements of racial discrimination are needed. As a result, I argue that racial discrimination should be a polysemous concept (with multiple meanings).

Participatory modeling in sustainability science allows scientists to take stakeholders’ interests, knowledge, and values into account when designing a model-based solution to a sustainability problem, by incorporating stakeholders in the model-building process. This improves the chance of generating socially robust knowledge and consensus on solutions. Part of what helps in this regard is that scientists, through involving stakeholders, limit their own values from influencing the outcome, thus achieving some level of value-neutrality. We argue that while it might achieve this to some extent, it comes at a cost to the reliability of the outcomes, which is ethically problematic.