John Symons

Ethically significant consequences of artificially intelligent artifacts will stem from their effects on existing social relations. Artifacts will serve in a variety of socially important roles—as personal companions, in the service of elderly and infirm people, in commercial, educational, and other socially sensitive contexts. The inevitable disruptions that these technologies will cause to social norms, institutions, and communities warrant careful consideration. As we begin to assess these effects, reflection on degrees and kinds of social agency will be required to make properly informed decisions concerning the deployment of artificially intelligent artifacts in important settings. The social agency of these systems is unlike a human social agency, and this paper provides a methodological framework that is more suited for inquiry into artificial social agents than conventional philosophical treatments of the concept of agency. Separate aspects and dimensions of agency can be studied without assuming that agency must always look like adult human agency. This revised approach to the agency of artifacts is conducive to progress in the topics studied by AI ethics.

This paper introduces the _Global Philosophy_ symposium on Giuseppe Primiero’s book _On the Foundations of Computing_ (2020). The collection gathers commentaries and responses of the author with the aim of engaging with some open questions in the philosophy of computer science. Firstly, this paper introduces the central themes addressed in Primiero’s book; secondly, it highlights some of the main critiques from commentators in order to, finally, pinpoint some conceptual challenges indicating future directions for the philosophy of computer science.

Procedural justifications of democracy emphasize inclusiveness and respect and by doing so come into conflict with instrumental justifications that depend on voters’ competence. This conflict raises questions about jury theorems and makes their standing in democratic theory contested. We show that a type of no-regret learning called meta-induction can help to satisfy the competence assumption without excluding voters or diverse opinion leaders on an a priori basis. Meta-induction assigns weights to opinion leaders based on their past predictive performance to determine the level of their inclusion in recommendations for voters. The weighting minimizes the difference between the performance of meta-induction and the best opinion leader in hindsight. The difference represents the regret of meta-induction whose minimization ensures that the recommendations are optimal in supporting voters’ competence. Meta-induction has optimal truth-tracking properties that support voters’ competence even if it is targeted by mis/disinformation and should be considered a tool for supporting democracy in hyper-plurality.

This paper argues that open-mindedness is a corrective virtue. It serves as a corrective to the epistemic vice of confirmation bias. Specifically, open-mindedness is the epistemically virtuous disposition to resist the negative effects of confirmation bias on our ability to reason well and to evaluate evidence and arguments. As part of the defense and presentation of our account, we explore four discussions of open-mindedness in the recent literature. All four approaches have strengths and shed light on aspects of the virtue of open-mindedness. Each mentions various symptoms of confirmation bias and some explore aspects of the corrective role of open-mindedness. However, ours is the first to explicitly identify open-mindedness as a corrective virtue to the specific epistemic vice of confirmation bias. We show how the corrective account also permits a response to the concern that open-mindedness might not actually count as a virtue.

In his “A New Program for Philosophy of Science?”, Ronald Giere expresses qualms regarding the critical and political projects I advocate for philosophy of science—that the critical project assumes an underdetermination absent from actual science, and the political project takes us outside the professional pursuit of philosophy of science. In reply I contend that the underdetermination the critical project assumes does occur in actual science, and I provide a variety of examples to support this. And I contend that the political project requires no more than what other academic fields even in science studies are already providing.

Quantum computing is of high interest because it promises to perform at least some kinds of computations much faster than classical computers. Arute et al. 2019 (informally, “the Google Quantum Team”) report the results of experiments that purport to demonstrate “quantum supremacy” – the claim that the performance of some quantum computers is better than that of classical computers on some problems. Do these results close the debate over quantum supremacy? We argue that they do not. In the following, we provide an overview of the Google Quantum Team’s experiments, then identify some open questions in the quest to demonstrate quantum supremacy.

This dissertation begins with an analysis of the recent history of the cognitive neuroscience of vision. This analysis is intended to test the basic assumptions of computational functionalism. Functionalists have argued that since psychological properties can be realized by a variety of structures, those structures are irrelevant to a proper characterization of their properties. By considering applications of functionalist methodology in cognitive science, I argue that functionalist models of mental life can be faulted for being either too minimal, or for making empirical and methodological claims that cannot be supported. In opposition to the functionalist autonomy thesis, Chapters Three and Four argue that taking neuroscientific evidence seriously can justify a revision of psychological taxonomies. ;Though the approach taken here with respect to the relationship between neuroscience and philosophy echoes some arguments presented in support of theory reductionism, it does not presuppose taking a reductionist or eliminativist stance on either ontological or methodological questions. In opposition to traditional eliminativist or reductionist suggestions, it is argued that naturalizing the philosophy of mind does not imply the complete subordination of philosophical inquiry to neuroscientific evidence. As evidence for this general claim and for the relevance of philosophical analysis to scientific inquiry, Chapters Four and Five present an analysis of uses of the notion of information in the neuroscience of vision. This analysis draws on past work in the logic of perception, relying in particular on Jaakko Hintikka's analysis of identification. Chapter Five considers the so-called two-pathways theory of visual identification in cognitive neuroscience, concluding that developments in semantical analysis can make an important difference at the level of concrete neuroscientific investigation. Specifically, the scientifically misleading claim that two kinds of visual information are necessary for the implementation of two modes of identification is corrected.

This paper challenges arguments that systematic patterns of intelligent behavior license the claim that representations must play a role in the cognitive system analogous to that played by syntactical structures in a computer program. In place of traditional computational models, I argue that research inspired by Dynamical Systems theory can support an alternative view of representations. My suggestion is that we treat linguistic and representational structures as providing complex multi-dimensional targets for the development of individual brains. This approach acknowledges the indispensability of the intentional or representational idiom in psychological explanation without locating representations in the brains of intelligent agents

Horgan’s perceptive discussion of Freudian psychology, Prozac and evolutionary biology cannot mitigate the problems that seriously weaken his book (Horgan, 1999). While he certainly manages to deflate some of the more outrageous hype surrounding the scientific and often not-so-scientific study of the mind, his criticism of the brain and behavioral sciences contains a number of flaws, some of which I will address below. My response focuses on his discussion of neuroscience. As we shall see, the three mysteries that Horgan believes cripple neuroscience are certainly not as serious as he insists.