12 found
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  1. Transparency in Algorithmic and Human Decision-Making: Is There a Double Standard?John Zerilli, Alistair Knott, James Maclaurin & Colin Gavaghan - 2019 - Philosophy and Technology 32 (4):661-683.
    We are sceptical of concerns over the opacity of algorithmic decision tools. While transparency and explainability are certainly important desiderata in algorithmic governance, we worry that automated decision-making is being held to an unrealistically high standard, possibly owing to an unrealistically high estimate of the degree of transparency attainable from human decision-makers. In this paper, we review evidence demonstrating that much human decision-making is fraught with transparency problems, show in what respects AI fares little worse or better and argue that (...)
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  2.  40
    A Citizen's Guide to Artificial Intelligence.James Maclaurin, John Danaher, John Zerilli, Colin Gavaghan, Alistair Knott, Joy Liddicoat & Merel Noorman - 2021 - Cambridge, MA, USA: MIT Press.
    A concise but informative overview of AI ethics and policy. -/- Artificial intelligence, or AI for short, has generated a staggering amount of hype in the past several years. Is it the game-changer it's been cracked up to be? If so, how is it changing the game? How is it likely to affect us as customers, tenants, aspiring homeowners, students, educators, patients, clients, prison inmates, members of ethnic and sexual minorities, and voters in liberal democracies? Authored by experts in fields (...)
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  3.  29
    Multiple Realization and the Commensurability of Taxonomies.John Zerilli - 2019 - Synthese 196 (8):3337-3353.
    The past two decades have witnessed a revival of interest in multiple realization and multiply realized kinds. Bechtel and Mundale’s :175–207, 1999) illuminating discussion of the subject must no doubt be credited with having generated much of this renewed interest. Among other virtues, their paper expresses what seems to be an important insight about multiple realization: that unless we keep a consistent grain across realized and realizing kinds, claims alleging the multiple realization of psychological kinds are vulnerable to refutation. In (...)
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  4.  20
    Algorithmic Decision-Making and the Control Problem.John Zerilli, Alistair Knott, James Maclaurin & Colin Gavaghan - 2019 - Minds and Machines 29 (4):555-578.
    The danger of human operators devolving responsibility to machines and failing to detect cases where they fail has been recognised for many years by industrial psychologists and engineers studying the human operators of complex machines. We call it “the control problem”, understood as the tendency of the human within a human–machine control loop to become complacent, over-reliant or unduly diffident when faced with the outputs of a reliable autonomous system. While the control problem has been investigated for some time, up (...)
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  5.  16
    Government Use of Artificial Intelligence in New Zealand.Colin Gavighan, Ali Knott, James Maclaurin, John Zerilli & Joy Liddicoat - 2019 - The New Zealand Law Foundation.
    Final Report on Phase 1 of the New Zealand Law Foundation’s Artificial Intelligence and Law in New Zealand Project.
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  6.  17
    Algorithmic Decision-Making and the Control Problem.John Zerilli, Alistair Knott, James Maclaurin & Colin Gavaghan - 2019 - Minds and Machines 29 (4):555-578.
    The danger of human operators devolving responsibility to machines and failing to detect cases where they fail has been recognised for many years by industrial psychologists and engineers studying the human operators of complex machines. We call it “the control problem”, understood as the tendency of the human within a human–machine control loop to become complacent, over-reliant or unduly diffident when faced with the outputs of a reliable autonomous system. While the control problem has been investigated for some time, up (...)
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  7.  31
    Against the “System” Module.John Zerilli - 2017 - Philosophical Psychology 30 (3):231-246.
    Modularity is a fundamental doctrine in the cognitive sciences. It holds a preeminent position in cognitive psychology and generative linguistics, as well as a long history in neurophysiology, with roots going all the way back to the early nineteenth century. But a mature field of neuroscience is a comparatively recent phenomenon and has challenged orthodox conceptions of the modular mind. One way of accommodating modularity within the new framework suggested by these developments is to go for increasingly soft versions of (...)
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  8.  30
    Multiple Realization and the Commensurability of Taxonomies.John Zerilli - 2016 - Synthese:1-17.
    The past two decades have witnessed a revival of interest in multiple realization and multiply realized kinds. Bechtel and Mundale’s :175–207, 1999) illuminating discussion of the subject must no doubt be credited with having generated much of this renewed interest. Among other virtues, their paper expresses what seems to be an important insight about multiple realization: that unless we keep a consistent grain across realized and realizing kinds, claims alleging the multiple realization of psychological kinds are vulnerable to refutation. In (...)
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  9.  38
    Neural Reuse and the Modularity of Mind: Where to Next for Modularity?John Zerilli - 2019 - Biological Theory 14 (1):1-20.
    The leading hypothesis concerning the “reuse” or “recycling” of neural circuits builds on the assumption that evolution might prefer the redeployment of established circuits over the development of new ones. What conception of cognitive architecture can survive the evidence for this hypothesis? In particular, what sorts of “modules” are compatible with this evidence? I argue that the only likely candidates will, in effect, be the columns which Vernon Mountcastle originally hypothesized some 60 years ago, and which form part of the (...)
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  10.  14
    Explaining Machine Learning Decisions.John Zerilli - 2022 - Philosophy of Science 89 (1):1-19.
    The operations of deep networks are widely acknowledged to be inscrutable. The growing field of Explainable AI has emerged in direct response to this problem. However, owing to the nature of the opacity in question, XAI has been forced to prioritise interpretability at the expense of completeness, and even realism, so that its explanations are frequently interpretable without being underpinned by more comprehensive explanations faithful to the way a network computes its predictions. While this has been taken to be a (...)
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  11.  17
    Neural Redundancy and Its Relation to Neural Reuse.John Zerilli - 2019 - Philosophy of Science 86 (5):1191-1201.
    Evidence of the pervasiveness of neural reuse in the human brain has forced a revision of the standard conception of modularity in the cognitive sciences. One persistent line of argument against such revision, however, cites the evidence of cognitive dissociations. While this article takes the dissociations seriously, it contends that the traditional modular account is not the best explanation. The key to the puzzle is neural redundancy. The article offers both a philosophical analysis of the relation between reuse and redundancy (...)
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  12.  17
    A Minimalist Framework for Comparative Psychology: T. Suddendorf The Gap: The Science of What Separates Us From the Animals. Basic Books, New York, 358 Pp.John Zerilli - 2014 - Biology and Philosophy 29 (6):897-904.
    Suddendorf explores “the gap” between humans and other animals, with a particular emphasis on our great ape relatives. Both for nonscientists and those scientists or philosophers whose work is not centrally preoccupied with such questions, the book provides a tidy compendium of experimental results organized around a number of precisely defined areas of competence. He takes language, mental time travel, theory of mind, intelligence, culture and morality to be definitive of human cognitive prowess and judiciously evaluates the comparative evidence he (...)
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