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Donal Khosrowi
Universität Hannover
  1. Three Ways in Which Pandemic Models May Perform a Pandemic.Philippe Van Basshuysen, Lucie White, Donal Khosrowi & Mathias Frisch - 2021 - Erasmus Journal for Philosophy and Economics 14 (1):110-127.
    Models not only represent but may also influence their targets in important ways. While models’ abilities to influence outcomes has been studied in the context of economic models, often under the label ‘performativity’, we argue that this phenomenon also pertains to epidemiological models, such as those used for forecasting the trajectory of the Covid-19 pandemic. After identifying three ways in which a model by the Covid-19 Response Team at Imperial College London may have influenced scientific advice, policy, and individual responses, (...)
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  2. Extrapolation of causal effects – hopes, assumptions, and the extrapolator’s circle.Donal Khosrowi - 2019 - Journal of Economic Methodology 26 (1):45-58.
    I consider recent strategies proposed by econometricians for extrapolating causal effects from experimental to target populations. I argue that these strategies fall prey to the extrapolator’s circle: they require so much knowledge about the target population that the causal effects to be extrapolated can be identified from information about the target alone. I then consider comparative process tracing as a potential remedy. Although specifically designed to evade the extrapolator’s circle, I argue that CPT is unlikely to facilitate extrapolation in typical (...)
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    Getting Serious about Shared Features.Donal Khosrowi - 2020 - British Journal for the Philosophy of Science 71 (2):523-546.
    In Simulation and Similarity, Michael Weisberg offers a similarity-based account of the model–world relation, which is the relation in virtue of which successful models are successful. Weisberg’s main idea is that models are similar to targets in virtue of sharing features. An important concern about Weisberg’s account is that it remains silent on what it means for models and targets to share features, and consequently on how feature-sharing contributes to models’ epistemic success. I consider three potential ways of concretizing the (...)
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  4.  62
    Decentring the discoverer: how AI helps us rethink scientific discovery.Elinor Clark & Donal Khosrowi - 2022 - Synthese 200 (6):1-26.
    This paper investigates how intuitions about scientific discovery using artificial intelligence can be used to improve our understanding of scientific discovery more generally. Traditional accounts of discovery have been agent-centred: they place emphasis on identifying a specific agent who is responsible for conducting all, or at least the important part, of a discovery process. We argue that these accounts experience difficulties capturing scientific discovery involving AI and that similar issues arise for human discovery. We propose an alternative, collective-centred view as (...)
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  5. Evidence-Based Policy: The Tension Between the Epistemic and the Normative.Donal Khosrowi & Julian Reiss - 2019 - Critical Review: A Journal of Politics and Society 31 (2):179-197.
    Acceding to the demand that public policy should be based on “the best available evidence” can come at significant moral cost. Important policy questions cannot be addressed using “the best available evidence” as defined by the evidence-based policy paradigm; the paradigm can change the meaning of questions so that they can be addressed using the preferred kind of evidence; and important evidence that does not meet the standard defined by the paradigm can get ignored. We illustrate these problems in three (...)
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  6.  76
    Trade-offs between Epistemic and Moral Values in Evidence-Based Policy.Donal Khosrowi - 2016 - Economics and Philosophy (1):49-78.
    Proponents of evidence-based policy (EBP) call for public policy to be informed by high-quality evidence from randomized controlled trials. This methodological preference aims to promote several epistemic values, e.g. rigor, unbiasedness, precision, and the ability to obtain causal conclusions. I argue that there is a trade-off between these epistemic values and several non-epistemic, moral and political values. This is because the evidence afforded by preferred EBP methods is differentially useful for pursuing different moral and political values. I expand on how (...)
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    Managing Performative Models.Donal Khosrowi - 2023 - Philosophy of the Social Sciences 53 (5):371-395.
    Scientific models can be performative: they can causally affect the phenomena they are intended to represent. The existing literature offers two responses. The appraisal view emphasizes that performativity can sometimes be a good-making model attribute, e.g., when predictions steer the public’s behavior in desirable ways. The mitigation view seeks to endogenize agents’ behavioral response to model-issued forecasts to get rid of performativity instead. This paper argues that neither approach is fully compelling: the appraisal view encounters severe concerns about moral values (...)
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  8.  88
    Evidence-Based Policy.Donal Khosrowi - 2021 - In Julian Reiss & Conrad Heilmann (eds.), Routledge Handbook of Philosophy of Economics. New York: 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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  9. Diffusing the Creator: Attributing Credit for Generative AI Outputs.Donal Khosrowi, Finola Finn & Elinor Clark - 2023 - Aies '23: Proceedings of the 2023 Aaai/Acm Conference on Ai, Ethics, and Society.
    The recent wave of generative AI (GAI) systems like Stable Diffusion that can produce images from human prompts raises controversial issues about creatorship, originality, creativity and copyright. This paper focuses on creatorship: who creates and should be credited with the outputs made with the help of GAI? Existing views on creatorship are mixed: some insist that GAI systems are mere tools, and human prompters are creators proper; others are more open to acknowledging more significant roles for GAI, but most conceive (...)
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  10.  23
    When Experiments Need Models.Donal Khosrowi - 2021 - Philosophy of the Social Sciences 51 (4):400-424.
    This paper argues that an important type of experiment-target inference, extrapolating causal effects, requires models to be successful. Focusing on extrapolation in Evidence-Based Policy, it is ar...
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  11.  44
    What’s (successful) extrapolation?Donal Khosrowi - 2021 - Journal of Economic Methodology 29 (2):140-152.
    Extrapolating causal effects is becoming an increasingly important kind of inference in Evidence-Based Policy, development economics, and microeconometrics more generally. While several strategies have been proposed to aid with extrapolation, the existing methodological literature has left our understanding of what extrapolation consists of and what constitutes successful extrapolation underdeveloped. This paper addresses this lack in understanding by offering a novel account of successful extrapolation. Building on existing contributions pertaining to the challenges involved in extrapolation, this more nuanced and comprehensive account (...)
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    Extrapolating from experiments, confidently.Donal Khosrowi - 2023 - European Journal for Philosophy of Science 13 (2):1-28.
    Extrapolating causal effects from experiments to novel populations is a common practice in evidence-based-policy, development economics and other social science areas. Drawing on experimental evidence of policy effectiveness, analysts aim to predict the effects of policies in new populations, which might differ importantly from experimental populations. Existing approaches made progress in articulating the sorts of similarities one needs to assume to enable such inferences. It is also recognized, however, that many of these assumptions will remain surrounded by significant uncertainty in (...)
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