This article provides the first detailed modern examination of Julia Wedgwood’s interventions in the Victorian debate about the origin of language. Wedgwood wanted to understand language, consistently with Darwin’s theory of evolution, as having evolved gradually out of other forms of animal behaviour. She focused specifically on imitative behaviours, siding with the imitative or “bow-wow” theory of language which her father Hensleigh Wedgwood also championed. She opposed the conceptualist or “ding-dong” theory of Max Müller, on which language is the “Rubicon” (...) that radically separates humans from animals. I argue that Julia Wedgwood was right to emphasise that the human capacity for language is continuous with animal behaviours, though she was wrong to reduce this continuity to a single behaviour, imitation. Nevertheless, her language essays remain significant as an early attempt to forge a Darwinian account of language, and they illuminate the fact that women were able to take part in Victorian philosophical debates, including on an abstract topic such as philosophy of language. The essays also provide entry into Wedgwood’s thought and work more broadly, which are unjustly neglected and deserve to be recovered. (shrink)

This is a critique of Timothy Hsiao’s ‘A Moral Defense of Trophy Hunting.’ I argue that Hsiao’s arguments on pain, consciousness, behavior, cruelty, and necessity all fail. More importantly, I argue against his broader conclusion that non-human animals ‘do not have any inherent moral significance.’ My conclusion is that Hsiao’s moral defense of trophy hunting fails.

Midwest Studies In Philosophy, Volume 44, Issue 1, Page 38-47, December 2019.

I draw on neurobiological evidence to defend the rationalist thesis that moral judgments are essentially dependent on reasoning, not emotions (conceived as distinct from inference). The neuroscience reveals that moral cognition arises from domain-general capacities in the brain for inferring, in particular, the consequences of an agent’s action, the agent’s intent, and the rules or norms relevant to the context. Although these capacities entangle inference and affect, blurring the reason/emotion dichotomy doesn’t preferentially support sentimentalism. The argument requires careful consideration of (...) the empirical evidence (from neuroimaging to psychopathology) and philosophical analysis of the commitments of rationalism versus sentimentalism in ethics. (shrink)

In domains as disparate as playing Go and predicting the structure of proteins, artificial intelligence (AI) technologies have begun to perform at levels beyond which any humans can achieve. Does this fact represent something lamentable? Does superhuman AI performance somehow undermine the value of human achievements in these areas? Go grandmaster Lee Sedol suggested as much when he announced his retirement from professional Go, blaming the advances of Go-playing programs like AlphaGo for sapping his will to play the game at (...) a high level. In this paper, I attempt to make sense of Sedol’s lament. I consider a number of ways that the existence of superhuman-performing AI technologies could undermine the value of human achievements. I argue there is very little in the nature of the technology itself that warrants such despair. (Compare: does the existence of a fighter jet undermine the value of being the fastest human sprinter?) But I also argue there are several more localized domains where these technologies threaten to displace human beings from being able to achieve valuable things at all. This is a particular worry for those in unequal societies, I argue, given the difficulty of many achievements and the corresponding amount of resources needed to achieve great things. (shrink)

It has been hypothesized that postperformance memory gaps occur in highly skilled individuals because experts generally perform their skills without conscious attention. In contrast, we hypothesize that such memory gaps may occur when performers focus so intently on their unfolding actions that their ongoing attention interferes with long-term memory formation of what was previously attended to, or when performers are highly focused on aspects of their bodily skills that are not readily put into words. In neither case, we argue, does (...) performance proceed automatically yet both situations, we suggest, may lead to an inability to recollect performance. (shrink)

The received view of implicit bias holds that it is associative and unreflective. Recently, the received view has been challenged. Some argue that implicit bias is not predicated on “any” associative process, but it is unreflective. These arguments rely, in part, on debiasing experiments. They proceed as follows. If implicit bias is associative and unreflective, then certain experimental manipulations cannot change implicitly biased behavior. However, these manipulations can change such behavior. So, implicit bias is not associative and unreflective. This paper (...) finds philosophical and empirical problems with that argument. When the problems are solved, the conclusion is not quite right: implicit bias is not necessarily unreflective, but it seems to be associative. Further, the paper shows that even if legitimate non-associative interventions on implicit bias exist, then both the received view and its recent contender would be false. In their stead would be interactionism or minimalism about implicit bias. (shrink)

The last 5 years have seen a series of remarkable achievements in deep-neural-network-based artificial intelligence research, and some modellers have argued that their performance compares favourably to human cognition. Critics, however, have argued that processing in deep neural networks is unlike human cognition for four reasons: they are (i) data-hungry, (ii) brittle, and (iii) inscrutable black boxes that merely (iv) reward-hack rather than learn real solutions to problems. This article rebuts these criticisms by exposing comparative bias within them, in the (...) process extracting some more general lessons that may also be useful for future debates. (shrink)

A theoretical pillars of vision science in the information-processing tradition is that perception involves unconscious inference. The classic support for this claim is that, since retinal inputs underdetermine their distal causes, visual perception must be the conclusion of a process that starts with premises representing both the sensory input and previous knowledge about the visible world. Focus on this “argument from underdetermination” gives the impression that, if it fails, there is little reason to think that visual processing involves unconscious inference. (...) Here an alternative means of support for this pillar is proposed, based on another foundational challenge for the visual system: recognizing invariant properties of objects in the environment even though anything we encounter is never seen exactly the same way twice. Explaining how the visual system solves this invariance problem requires positing visual processes that exhibit many commonalities with inductive inference. Thus, this novel “argument from invariance” reveals one way in which visual processing clearly involves unconscious inference. (shrink)