This paper describes one style of functional analysis commonly used in the neurosciences called task-bound functional analysis. The concept of function invoked by this style of analysis is distinctive in virtue of the dependence relations it bears to transient environmental properties. It is argued that task-bound functional analysis cannot explain the presence of structural properties in nervous systems. An alternative concept of neural function is introduced that draws on the theoretical neuroscience literature, and an argument is given to show that (...) this alternative concept of may help to overcome the explanatory limitations of task-bound functional analysis. (shrink)

From Bacteria To Bach and Back is an ambitious book that attempts to integrate a theory about the evolution of the human mind with another theory about the evolution of human culture. It is advertised as a defense of memes, but conceptualizes memes more liberally than has been done before. It is also advertised as a defense of the proposal that natural selection operates on culture, but conceptualizes natural selection as a process in which nearly all interesting parameters are free (...) to vary. This liberal conception of key concepts creates space for philosophical innovation, but occasionally makes the empirical content of the theory difficult to pin down. Nevertheless, the book is full of scientific insight, wit, and humor. It will undoubtedly become a cause of both controversy and inspiration for those interested in naturalistic theories of human culture. (shrink)

In this article, network science is discussed from a methodological perspective, and two central theses are defended. The first is that network science exploits the very properties that make a system complex. Rather than using idealization techniques to strip those properties away, as is standard practice in other areas of science, network science brings them to the fore, and uses them to furnish new forms of explanation. The second thesis is that network representations are particularly helpful in explaining the properties (...) of non-decomposable systems. Where part-whole decomposition is not possible, network science provides a much-needed alternative method of compressing information about the behavior of complex systems, and does so without succumbing to problems associated with combinatorial explosion. The article concludes with a comparison between the uses of network representation analyzed in the main discussion, and an entirely distinct use of network representation that has recently been discussed in connection with mechanistic modeling. (shrink)

A fascinating research program in neurophysiology attempts to quantify the amount of information transmitted by single neurons. The claims that emerge from this research raise new philosophical questions about the nature of information. What kind of information is being quantified? Do the resulting quantities describe empirical magnitudes like those found elsewhere in the natural sciences? In this article, it is argued that neural information quantities have a relativisitic character that makes them distinct from the kinds of information typically discussed in (...) the philosophical literature. It is also argued that despite this relativistic character, there are cases in which neural information quantities can be viewed as robustly objective empirical properties. (shrink)

Neural systems process information. This platitude contains an interesting ambiguity between multiple senses of the term “information.” According to a popular thought, the ambiguity is best resolved by reserving semantic concepts of information for the explication of neural activity at a high level of organization, and quantitative concepts of information for the explication of neural activity at a low level of organization. This article articulates the justification behind this view, and concludes that it is an oversimplification. An analysis of the (...) meaning of claims about Shannon information rates in the spiking activity of neurons is then developed. On the basis of that analysis, it is shown that quantitative conceptions of information are more intertwined with semantic concepts than they seem to be, and, partially for that reason, are also more philosophically interesting. (shrink)

Neural systems process information. This platitude contains an interesting ambiguity between multiple senses of the term “information.” According to a popular thought, the ambiguity is best resolved by reserving semantic concepts of information for the explication of neural activity at a high level of organization, and quantitative concepts of information for the explication of neural activity at a low level of organization. This article articulates the justification behind this view, and concludes that it is an oversimplification. An analysis of the (...) meaning of claims about Shannon information rates in the spiking activity of neurons is then developed. On the basis of that analysis, it is shown that quantitative conceptions of information are more intertwined with semantic concepts than they seem to be, and, partially for that reason, are also more philosophically interesting. (shrink)

Will brain imaging technology soon enable neuroscientists to read minds? We cannot answer this question without some understanding of the state of the art in neuroimaging. But neither can we answer this question without some understanding of the concept invoked by the term "mind reading." This article is an attempt to develop such understanding. Our analysis proceeds in two stages. In the first stage, we provide a categorical explication of mind reading. The categorical explication articulates empirical conditions that must be (...) satisfied if mind reading is to be achieved. In the second stage, we develop a metric for judging the proficiency of mind reading experiments. The conception of mind reading that emerges helps to reconcile folk psychological judgments about what mind reading must involve with the constraints imposed by empirical strategies for achieving it. (shrink)

Heyes suggests that selective social learning comes in two varieties. One is common, domain general, and associative. The other is rare, domain specific, and metacognitive. We argue that this binary distinction cannot quite do the work she assigns it and sketch a framework in which additional strategies for selective social learning might be accommodated.

Will brain imaging technology soon enable neuroscientists to read minds? We cannot answer this question without some understanding of the state of the art in neuroimaging. But neither can we answer this question without some understanding of the concept invoked by the term “mind reading.” This article is an attempt to develop such understanding. Our analysis proceeds in two stages. In the first stage, we provide a categorical explication of mind reading. The categorical explication articulates empirical conditions that must be (...) satisfied if mind reading is to be achieved. In the second stage, we develop a metric for judging the proficiency of mind reading experiments. The conception of mind reading that emerges helps to reconcile folk psychological judgments about what mind reading must involve with the constraints imposed by empirical strategies for achieving it. (shrink)

Position papers on artificial intelligence (AI) ethics are often framed as attempts to work out technical and regulatory strategies for attaining what is commonly called trustworthy AI. In such papers, the technical and regulatory strategies are frequently analyzed in detail, but the concept of trustworthy AI is not. As a result, it remains unclear. This paper lays out a variety of possible interpretations of the concept and concludes that none of them is appropriate. The central problem is that, by framing (...) the ethics of AI in terms of trustworthiness, we reinforce unjustified anthropocentric assumptions that stand in the way of clear analysis. Furthermore, even if we insist on a purely epistemic interpretation of the concept, according to which trustworthiness just means measurable reliability, it turns out that the analysis will, nevertheless, suffer from a subtle form of anthropocentrism. The paper goes on to develop the concept of strange error, which serves both to sharpen the initial diagnosis of the inadequacy of trustworthy AI and to articulate the novel epistemological situation created by the use of AI. The paper concludes with a discussion of how strange error puts pressure on standard practices of assessing moral culpability, particularly in the context of medicine. (shrink)

Charles A. Baylis; VII—Foundations For a Presentative Theory of Perception and Sensation, Proceedings of the Aristotelian Society, Volume 66, Issue 1, 1 June 19.

This book is a clear, engaging, and ambitious introduction to the philosophy of John Dewey. First, a comment about the subtitle: while I recognize that it reflects the book’s inclusion in a series of “beginner’s guides,” the subtitle (“a beginner’s guide”) is unfortunate. The book is much more than that, and, as such, it is more valuable than the subtitle suggests. It is clearly of help to people new to Dewey, and yet it is also a significant resource for those (...) returning to Dewey in a variety of capacities. For example, this reviewer has found Hildebrand’s book helpful for thinking about pedagogical strategies for teaching Dewey in a recent seminar class (on James and Dewey), and I expect many other teachers will .. (shrink)

Charles A. Baylis; VII—Foundations For a Presentative Theory of Perception and Sensation, Proceedings of the Aristotelian Society, Volume 66, Issue 1, 1 June 19.

Here are the chief riches of more than 3,000 years of Indian philosophical thought-the ancient Vedas, the Upanisads, the epics, the treatises of the heterodox and orthodox systems, the commentaries of the scholastic period, and the contemporary writings. Introductions and interpretive commentaries are provided.