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  1. Evidence-Based Policy.Donal Khosrowi - 2022 - In Conrad Heilmann & Julian Reiss (eds.), Routledge Handbook of Philosophy of Economics. Routledge. pp. 370-381.
    Public policymakers and institutional decision-makers routinely face questions about whether interventions “work”: does universal basic income improve people’s welfare and stimulate entrepreneurial activity? Do gated alleyways reduce burglaries or merely shift the crime burden to neighbouring communities? What is the most cost-effective way to improve students’ reading abilities? These are empirical questions that seem best answered by looking at the world, rather than trusting speculations about what will be effective. Evidence-based policy (EBP) is a movement that concretizes this intuition. It (...)
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  • Choosing and refusing: doxastic voluntarism and folk psychology.John Turri, David Rose & Wesley Buckwalter - 2018 - Philosophical Studies 175 (10):2507-2537.
    A standard view in contemporary philosophy is that belief is involuntary, either as a matter of conceptual necessity or as a contingent fact of human psychology. We present seven experiments on patterns in ordinary folk-psychological judgments about belief. The results provide strong evidence that voluntary belief is conceptually possible and, granted minimal charitable assumptions about folk-psychological competence, provide some evidence that voluntary belief is psychologically possible. We also consider two hypotheses in an attempt to understand why many philosophers have been (...)
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  • Knowledge and the norm of assertion: a simple test.John Turri - 2015 - Synthese 192 (2):385-392.
    An impressive case has been built for the hypothesis that knowledge is the norm of assertion, otherwise known as the knowledge account of assertion. According to the knowledge account, you should assert something only if you know that it’s true. A wealth of observational data supports the knowledge account, and some recent empirical results lend further, indirect support. But the knowledge account has not yet been tested directly. This paper fills that gap by reporting the results of such a test. (...)
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  • Probabilistic causation.Christopher Hitchcock - 2008 - Stanford Encyclopedia of Philosophy.
    “Probabilistic Causation” designates a group of theories that aim to characterize the relationship between cause and effect using the tools of probability theory. The central idea behind these theories is that causes change the probabilities of their effects. This article traces developments in probabilistic causation, including recent developments in causal modeling. A variety of issues within, and objections to, probabilistic theories of causation will also be discussed.
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  • Ethics framework for predictive clinical AI model updating.Michal Pruski - 2023 - Ethics and Information Technology 25 (3):1-10.
    There is an ethical dilemma present when considering updating predictive clinical artificial intelligence (AI) models, which should be part of the departmental quality improvement process. One needs to consider whether withdrawing the AI model is necessary to obtain the relevant information from a naive patient population or whether to use causal inference techniques to obtain this information. Withdrawing an AI model from patient care might pose challenges if the AI model is considered standard of care, while use of causal inference (...)
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  • Analysing causality: The opposite of counterfactual is factual.Jim Bogen - 2002 - International Studies in the Philosophy of Science 18 (1):3 – 26.
    Using Jim Woodward's Counterfactual Dependency account as an example, I argue that causal claims about indeterministic systems cannot be satisfactorily analysed as including counterfactual conditionals among their truth conditions because the counterfactuals such accounts must appeal to need not have truth values. Where this happens, counterfactual analyses transform true causal claims into expressions which are not true.
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  • Are there algorithms that discover causal structure?David Freedman & Paul Humphreys - 1999 - Synthese 121 (1-2):29-54.
    There have been many efforts to infer causation from association byusing statistical models. Algorithms for automating this processare a more recent innovation. In Humphreys and Freedman[(1996) British Journal for the Philosophy of Science 47, 113–123] we showed that one such approach, by Spirtes et al., was fatally flawed. Here we put our arguments in a broader context and reply to Korb and Wallace [(1997) British Journal for thePhilosophy of Science 48, 543–553] and to Spirtes et al.[(1997) British Journal for the (...)
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