Annalen der Philosophie

Libertarians claim that human behaviour is undetermined and cannot be predicted from knowledge of past history even in principle since it is based on the random movements of quantum mechanics. Determinists on the other hand deny thatmacroscopic phenomena can be activated bysub-microscopic events, and assert that if human action is unpredictable in the way claimed by libertarians, it must be aimless and irrational. This is not true of some types of random behaviour described in this paper. Random behaviour may make one unpredictable to opponents and may therefore be rational. Similarly, playing a game with a mixed strategy may have an unpredictable outcome in every single play, but the strategy is rational, in that it is meant to maximize the expected value of an objective, be it private or social. As to whether the outcome of such behaviour is genuinely unpredictable as in quantum mechanics, or predictable by a hypothetical outside observer knowing all natural laws, it is argued that it makes no difference in practice, as long as it is not humanly predictable. Thus we have a new version of libertarianism which is compatible with determinism.

The question regarding how to characterize aesthetics has been revived with the publication of Bence Nanay’s Aesthetics as Philosophy of Perception. This paper takes seriously Dustin Stokes’ criticisms of Nanay’s book regarding Nanay’s inability to distinguish between ordinary expert visual tasks (e.g., sorting for sock color or ornithology) and aesthetic experience. Using empirical research on gist perception and its reliance on low-level features in visual experience, I develop a theory that distinguishes expert visual tasks and aesthetic experiences by differentiating two different kinds of distributed attention over properties. I argue that expert visual tasks are instances of property attribution in a mode of conscious attention, while aesthetics is a kind of distributed attention that significantly relies on the reiteration of gist-like lowlevel features. Gist, often referred to in visual science as “preattentive” mode, gives us a model to understand the perceptual processes that are specific to aesthetics. This comports with our common-sense definition of aesthetics as both distinguishable from ordinary expert visual tasks and an experience that makes prominent sensory aspects of visual experience.

The philosophical debate around the impact of machine learning in science is often framed in terms of a choice between AI and classical methods as mutually exclusive alternatives involving difficult epistemological trade-offs. A common worry regarding machine learning methods specifically is that they lead to opaque models that make predictions but do not lead to explanation or understanding. Focusing on the field of molecular biology, I argue that in practice machine learning is often used with explanatory aims. More specifically, I argue that machine learning can be tightly integrated with other, more traditional, research methods and in a clear sense can contribute to insight into the causal processes underlying phenomena of interest to biologists. One could even say that machine learning is not the end of theory in important areas of biology, as has been argued, but rather a new beginning. I support these claims with a detailed discussion of a case study involving gene regulation by microRNAs.

Perceptual experience is often said to be transparent; that is, when we have a perceptual experience we seem to be aware of properties of the objects around us, and never seem to be aware of properties of the experience itself. This is a (purported) introspective fact. It is also often said that we can infer a metaphysical fact from this introspective fact, e.g. a fact about the nature of perceptual experience. A transparency theory fills in the details for these two facts, and bridges the gap between them. We have three aims: to scrutinize Michael Tye’s transparency theory (Noûs 36(1):137–151, 2002; Consciousness revisited: materialism without phenomenal concepts, MIT Press, Cambridge, 2009; Philos Stud 170(1):39–57, 2014a), introduce a new transparency theory, and advance a meta-theoretical hypothesis about the interest, and import, of transparency theories.

A frequentist confidence interval can be constructed by inverting a hypothesis test, such that the interval contains only parameter values that would not have been rejected by the test. We show how a similar definition can be employed to construct a Bayesian support interval. Consistent with Carnap’s theory of corroboration, the support interval contains only parameter values that receive at least some minimum amount of support from the data. The support interval is not subject to Lindley’s paradox and provides an evidence-based perspective on inference that differs from the belief-based perspective that forms the basis of the standard Bayesian credible interval.

In this paper, a survey is made of some of the contributionsto the interpretation of Hartle and Hawking's theory of thewave function of the universe and its beginning. It is arguedthat there are considerable difficulties with the interpretationof the theory, but that there is at least one interpretationhitherto not found in the literature which survives existingphilosophical objections.