Externalism and exploitability

Das, Nilanjan

doi:10.1111/phpr.12742

Cited by 6 publications

(2 citation statements)

References 54 publications

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“…6 Proponents of evidential externalism want to reject the partitionality assumption. They argue that in cases in which it is not transparent to the agent what their evidence is, the partitionality assumption fails, which means that a crucial premise in the Dutch strategy argument is unavailable (Das, 2020;Gallow, 2019a). The problem also applies to the expected accuracy argument for conditionalization, as Schoenfield (2017) shows, as well as the accuracy dominance arguments by Briggs and Pettigrew (2020) and Nielsen (2021).…”

Section: The Dutch Strategy Argument For Conditionalization and Its Limitationsmentioning

confidence: 99%

Updating incoherent credences ‐ Extending the Dutch strategy argument for conditionalization

Bona

Staffel

2021

Philos Phenomenol Research

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In this paper, we ask: how should an agent who has incoherent credences update when they learn new evidence? The standard Bayesian answer for coherent agents is that they should conditionalize; however, this updating rule is not defined for incoherent starting credences. We show how one of the main arguments for conditionalization, the Dutch strategy argument, can be extended to devise a target property for updating plans that can apply to them regardless of whether the agent starts out with coherent or incoherent credences. The main idea behind this extension is that the agent should avoid updating plans that increase the possible sure loss from Dutch strategies. This happens to be equivalent to avoiding updating plans that increase incoherence according to a distance-based incoherence measure.

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Section: The Dutch Strategy Argument For Conditionalization and Its Limitationsmentioning

confidence: 99%

Updating incoherent credences ‐ Extending the Dutch strategy argument for conditionalization

Bona

Staffel

2021

Philos Phenomenol Research

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“…I am assuming that, in cases of this sort, when the agent distributes credences over a finite possibility space, the credence functions in the agent's posterior representor are required by epistemic rationality to assign non-zero credences to the possibilities compatible with the agent's evidence.36 For recent discussions of this point, seeGallow (2019) andDas (2022).…”

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confidence: 99%

Credal imprecision and the value of evidence

Das

2022

Nous

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This paper is about a tension between two theses. The first is Value of Evidence: roughly, the thesis that it is always rational for an agent to gather and use cost-free evidence for making decisions. The second is Rationality of Imprecision: the thesis that an agent can be rationally required to adopt doxastic states that are imprecise, i.e., not representable by a single credence function. While others have noticed this tension, I offer a new diagnosis of it. I show that it arises when an agent with an imprecise doxastic state engages in an unreflective inquiry, an inquiry where they revise their beliefs using an updating rule that doesn't satisfy a weak reflection principle. In such an unreflective inquiry, certain synchronic norms of instrumental rationality can make it instrumentally irrational for an agent to gather and use cost-free evidence. I then go on to propose a diachronic norm of instrumental rationality that preserves Value of Evidence in unreflective inquiries. This, I suggest, may help us reconcile this thesis with Rationality of Imprecision.Consider this argument. The success of our actions depends on the way the world is. We can only find out how the world is by gathering more evidence and revising our beliefs in light of it. So, if a piece of evidence is available for gathering and use, it always makes sense to gather that evidence and use it for making decisions.This argument-though plausible at first glance-is subject to two challenges. First, if the expected costs of gathering and using the available evidence outweigh the expected benefits of This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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Approximate rationality and ideal rationality

Zhang

2024

AJPH

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According to approximate Bayesianism, Bayesian norms are ideal norms worthy of approximation for non-ideal agents. This paper discusses one potential challenge for approximate Bayesianism: in non-transparent learning situations—situations where the agent does not learn what they have or have not learnt—it is unclear that the Bayesian norms are worth satisfying, let alone approximating. I discuss two replies to this challenge and find neither satisfactory. I suggest that what transpires is a general tension between approximate Bayesianism and the possibility of “non-ideal” epistemic situations.

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Externalism and exploitability

Cited by 6 publications

References 54 publications

Updating incoherent credences ‐ Extending the Dutch strategy argument for conditionalization

Updating incoherent credences ‐ Extending the Dutch strategy argument for conditionalization

Credal imprecision and the value of evidence

Approximate rationality and ideal rationality

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