John Symons

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.

Intuition serves a variety of roles in contemporary philosophy. This paper provides a historical discussion of the revival of intuition in the 1970s, untangling some of the ways that intuition has been used and offering some suggestions concerning its proper place in philosophical investigation. Contrary to some interpretations of the results of experimental philosophy, it is argued that generalized skepticism with respect to intuition is unwarranted. Intuition can continue to play an important role as part of a methodologically conservative stance towards philosophical investigation. I argue that methodological conservatism should be sharply distinguished from the process of evaluating individual propositions. Nevertheless, intuition is not always a reliable guide to truth and experimental philosophy can serve a vital ameliorative role in determining the scope and limits of our intuitive competence with respect to various areas of inquiry.

Epistemic logic begins with the recognition that our everyday talk about knowing and believing has some systematic features that we can track and re‡ect upon. Epistemic logicians have studied and extended these glints of systematic structure in fascinating and important ways since the early 1960s. However, for one reason or another, mainstream epistemologists have shown little interest. It is striking to contrast the marginal role of epistemic logic in contemporary epistemology with the centrality of modal logic for metaphysicians. This article is intended to help in correcting this oversight by presenting some important developments in epistemic logic and suggesting ways to understand their applicability to traditional epistemological problems. Obviously, by itself, tweaking the formal apparatus of epistemic logic does not solve traditional epistemological problems. Epistemic logic can help us to navigate through problems in a systematic fashion by unpacking the logic of the problematic concepts, it can also lead us to recognize problems that we had not anticipated. This is basically analogous to the role that modal logic has played in contemporary metaphysics.

Computational modeling plays an increasingly important explanatory role in cases where we investigate systems or problems that exceed our native epistemic capacities. One clear case where technological enhancement is indispensable involves the study of complex systems.1 However, even in contexts where the number of parameters and interactions that define a problem is small, simple systems sometimes exhibit non-linear features which computational models can illustrate and track. In recent decades, computational models have been proposed as a way to assist us in understanding emergent phenomena.

Skeptics argue that the acquisition of knowledge is impossible given the standing possibility of error. We present the limiting convergence strategy for responding to skepticism and discuss the relationship between conceivable error and an agent’s knowledge in the limit. We argue that the skeptic must demonstrate that agents are operating with a bad method or are in an epistemically cursed world. Such demonstration involves a significant step beyond conceivability and commits the skeptic to potentially convergent inquiry.

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.

_The Routledge Companion to Philosophy of Psychology, Second Edition_ is an invaluable guide and major reference source to the major topics, problems, concepts and debates in philosophy of psychology and is the first companion of its kind. A team of renowned international contributors provide forty-nine chapters organised into six clear parts: Historical background to Philosophy of Psychology Psychological Explanation Cognition and Representation The biological basis of psychology Perceptual Experience Personhood. _The Companion_ covers key topics such as the origins of experimental psychology; folk psychology; behaviorism and functionalism; philosophy, psychology and neuroscience; the language of thought, modularity, nativism and representational theories of mind; consciousness and the senses; dreams emotion and temporality; personal identity and the philosophy of psychopathology. For the_ second edition_ many of the current chapters have been updated, and seven new chapters added on important new topics such predictive processing, comparative cognition, learning, and group cognition, as well as a new introductory chapter by the editors on the demarcation between philosophy and psychology. Essential reading for all students of philosophy of mind, science and psychology, _The Routledge Companion to Philosophy of Psychology _will also be of interest to anyone studying psychology and its related disciplines.

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

This paper argues that the difference between contemporary software intensive scientific practice and more traditional non-software intensive varieties results from the characteristically high conditionality of software. We explain why the path complexity of programs with high conditionality imposes limits on standard error correction techniques and why this matters. While it is possible, in general, to characterize the error distribution in inquiry that does not involve high conditionality, we cannot characterize the error distribution in inquiry that depends on software. Software intensive science presents distinctive error and uncertainty modalities that pose new challenges for the epistemology of science

An asymmetry between the demands at the computational and algorithmic levels of description furnishes the illusion that the abstract profile at the computational level can be multiply realized, and that something is actually being shared at the algorithmic one. A disembodied rendering of the situation lays the stress upon the different ways in which an algorithm can be implemented. However, from an embodied approach, things look rather different. The relevant pairing, I shall argue, is not between implementation and algorithm, but rather between algorithm and computation. The autonomy of psychology is a result of the failure to appreciate this point.

In this paper, we argue for the centrality of prediction in the use of computational models in science. We focus on the consequences of the irreversibility of computational models and on the conditional or ceteris paribus, nature of the kinds of their predictions. By irreversibility, we mean the fact that computational models can generally arrive at the same state via many possible sequences of previous states. Thus, while in the natural world, it is generally assumed that physical states have a unique history, representations of those states in a computational model will usually be compatible with more than one possible history in the model. We describe some of the challenges involved in prediction and retrodiction in computational models while arguing that prediction is an essential feature of non-arbitrary decision making. Furthermore, we contend that the non-predictive virtues of computational models are dependent to a significant degree on the predictive success of the models in question.

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.

Rather than taking the ontological fundamentality of an ideal microphysics as a starting point, this article sketches an approach to the problem of levels that swaps assumptions about ontology for assumptions about inquiry. These assumptions can be implemented formally via computational modeling techniques that will be described below. It is argued that these models offer a way to save some of our prominent commonsense intuitions concerning levels. This strategy offers a way of exploring the individuation of higher level properties in a systematic and formally constrained manner. †To contact the author, please write to: Department of Philosophy, Worrell Hall 306, 500 University Avenue, University of Texas, El Paso, TX 79968; e‐mail: [email protected].

This volume gathers together essays from some of Hintikka’s colleagues and former students exploring his influence on their work and pursuing some of the insights that we have found in his work. This book includes a comprehensive overview of Hintikka’s philosophy by Dan Kolak and John Symons and an annotated bibliography of Hintikka’s work. Table of Contents: Foreword; Daniel Kolak and John Symons. Hintikka on Epistemological Axiomatizations; Vincent F. Hendricks. Hintikka on the Problem with the Problem of Transworld Identity; Troy Catterson. What is Epistemic Discourse About? Radu J. Bogdan. Interrogative Logic and the Economic Theory of Information; Raymond Dacey. A Metalogical Critique of Wittgensteinian ‘Phenomenology’; William Boos. Theoretical Commensurability By Correspondence Relations: When Empirical Success Implies Theoretical Reference; Gerhard Schurz. What is Abduction?: An Assessment of Jaakko Hintikka's Conception; James H. Fetzer. The dialogic of just being different: Hintikka's new approach to the notion of episteme and its impact on 'second generation' dialogics; Shahid Rahman. Probabilistic Features in Logic Games; Johan F. A. K. van Benthem. On Some Logical Properties of ‘Is True’; Jan Wolenski. The Results are in: The Scope and Import of Hintikka's Philosophy; Daniel Kolak and John Symons. Annotated Bibliography of Jaakko Hintikka. Index.

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.