News

As Lewin (1943) already noted, “there is nothing as practical as a good theory”. However, how do we determine which theories are good and which are bad? It is hard to improve theory quality without a tool to assess it in practice. In psychology, most subfields are characterized by weak theories ...

Recent research in cognitive neuroscience has uncovered so-called neural manifolds that play a central role in explanations of behavior. Revealed through the use of a range of dimensionality reduction techniques, these manifolds are entities in low-dimensional spaces contained in high-dimensional ne...

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 a...

The technology of Machine Learning (ML), arguably, is one of the most significant general purpose technologies of our age. The appealing promise of machine learning is that it can take a given large corpus of “raw” data packaged up into a “dataset”, learn and discover various patterns, and d...

The precautionary principle is often put forward as potentially useful guide to avoiding catastrophe under conditions of uncertainty. But finding an adequate formulation of the principle runs into a problem when needed precautionary measures also have potentially catastrophic consequences – the im...

I argue that realism requires a stance, but that the realist should maintain that their stance is the only rationally permissible one. The basic motivation for maintaining that only a realist stance is rationally permissible is that being more open-minded induces a kind of pragmatic incoherence on t...

Philosophical accounts of biological mechanisms have only recently attended to the crucial role free energy plays in enabling the operation of mechanisms and have not addressed how scientists discover the role of free energy in the operation of biological mechanisms. To do so, I examine research on ...

It has been argued that climate modeling can be partially characterized as exhibiting ontic competitive pluralism (i.e., that models compete for truth in some sense). I argue that (1) because climate models are all of the same model-type, they are not ontic competitors; instead (2) they compete in t...

Scientific consensus plays a crucial role in public life. In the face of increasing science denialism, scientists are under pressure to present themselves as a united front to combat misinformation and conspiracy theories. However, the drive for consensus also has negative epistemic consequences, su...

Recently the topic of values in science has been extremely important in the philosophy of science. Initially, the debates were over whether and what sorts of values are present in the sciences. For example, are they epistemic or non-epistemic? However, if one grants non-epistemic values find their w...

Philosophical concern with epistemological challenges presented by opacity in deep neural networks does not align with the recent boom in optimism for AI in science and recent scientific breakthroughs driven by AI methods. I argue that the disconnect between philosophical pessimism and scientific op...

Parts of the politically conservative block in the United States have a long history of “science denialism”. As a means to explore the nature of the New Demarcation Problem (Holman and Wilholt, 2022) and its relation to the original Popperian demarcation problem this paper considers an example o...

“According to [Bayesian] models” says a recent textbook in cognitive neuroscience, “the human mind behaves like a capable data scientist”. Do they? That is to say, do such models show we are rational? I argue that Bayesian models of cognition, perhaps surprisingly, do not and indeed cannot, ...

Inequality measurements are widely used by scientists and policy makers. Social scientists use them to analyze the global distribution of income and trends over time. In policymaking, inequality measurements contribute to inform redistributive policies at national level, and to set the agenda for in...

Several philosophers have argued that “constraints” constrain (and thereby explain) by virtue of being modally stronger than ordinary laws of nature. In this way, a constraint applies to all possible systems in a broader (i.e., more inclusive) sense of “possible” than the sense in play when ...

A problem that is common to many sciences is that of having to deal with a multiplicity of statistical inferences. For instance, in GWAS (Genome Wide Association Studies), an experiment might consider 20 diseases and 100,000 genes, and conduct statistical tests of the 20x100,000=2,000,000 null hypot...

Eliminativism about levels is an over-reaction to a real problem that demands instead principled pluralism. Levels eliminativism is motivated in part by the recognition of systematic failures of entailment between seemingly related but distinct ways of talking about levels. Levels pluralism, in cont...

When philosophers investigate molecular concepts to determine whether particular accounts of molecules are satisfactory, they face a methodological challenge: they must make assumptions regarding the role(s) such concepts are intended to play. I suggest recognizing a distinction between explanatory ...

One way machine learning (ML) modeling is different from more traditional modeling methods is that they are data-driven, instead of what Knüsel and Baumberger (2020) call process driven. Moreover, ML models suffer from a higher degree of model opacity compared to more traditional modeling methods. ...