University of Michigan, Ann Arbor
Department of Philosophy
PhD, 2013
Canterbury, Kent, United Kingdom of Great Britain and Northern Ireland
Areas of Specialization
Epistemology
Philosophy of Probability
  •  1019
    Comparative Probabilities
    In Richard Pettigrew & Jonathan Weisberg (eds.), The Open Handbook of Formal Epistemology, Philpapers Foundation. pp. 267-348. 2019.
  •  650
    The Art of Learning
    Oxford Studies in Epistemology 7. forthcoming.
    Confirmational holism is at odds with Jeffrey conditioning --- the orthodox Bayesian policy for accommodating uncertain learning experiences. Two of the great insights of holist epistemology are that (i) the effects of experience ought to be mediated by one's background beliefs, and (ii) the support provided by one's learning experience can and often is undercut by subsequent learning. Jeffrey conditioning fails to vindicate either of these insights. My aim is to describe and defend a new updati…Read more
  •  537
    Moss (2018) argues that rational agents are best thought of not as having degrees of belief in various propositions but as having beliefs in probabilistic contents, or probabilistic beliefs. Probabilistic contents are sets of probability functions. Probabilistic belief states, in turn, are modeled by sets of probabilistic contents, or sets of sets of probability functions. We argue that this Mossean framework is of considerable interest quite independently of its role in Moss’ account of probabi…Read more
  •  397
    Epistemic Conservativity and Imprecise Credence
    Philosophy and Phenomenological Research. forthcoming.
    Unspecific evidence calls for imprecise credence. My aim is to vindicate this thought. First, I will pin down what it is that makes one's imprecise credences more or less epistemically valuable. Then I will use this account of epistemic value to delineate a class of reasonable epistemic scoring rules for imprecise credences. Finally, I will show that if we plump for one of these scoring rules as our measure of epistemic value or utility, then a popular family of decision rules recommends impreci…Read more
  •  260
    Probabilistic Knowledge and Cognitive Ability
    Philosophical Review 125 (4): 509-587. 2016.
    Sarah Moss argues that degrees of belief, or credences, can amount to knowledge in much the way that full beliefs can. This essay explores a new kind of objective Bayesianism designed to take us some way toward securing such knowledge-constituting credences, or "probabilistic knowledge." Whatever else it takes for an agent's credences to amount to knowledge, their success, or accuracy, must be the product of _cognitive ability_ or _skill_. The brand of Bayesianism developed here helps ensure thi…Read more
  •  251
    According to accuracy-first epistemology, accuracy is the fundamental epistemic good. Epistemic norms — Probabilism, Conditionalization, the Principal Principle, etc. — have their binding force in virtue of helping to secure this good. To make this idea precise, accuracy-firsters invoke Epistemic Decision Theory (EpDT) to determine which epistemic policies are the best means toward the end of accuracy. Hilary Greaves and others have recently challenged the tenability of this programme. Their arg…Read more
  •  242
    Degrees of incoherence, Dutch bookability & guidance value
    Philosophical Studies 180 (2): 395-428. 2022.
    Why is it good to be less, rather than more incoherent? Julia Staffel, in her excellent book “Unsettled Thoughts,” answers this question by showing that if your credences are incoherent, then there is some way of nudging them toward coherence that is guaranteed to make them more accurate and reduce the extent to which they are Dutch-bookable. This seems to show that such a nudge toward coherence makes them better fit to play their key epistemic and practical roles: representing the world and gui…Read more
  •  212
    IP Scoring Rules: Foundations and Applications
    Proceedings of Machine Learning Research 103 256-264. 2019.
  •  178
    We investigate epistemic independence for choice functions in a multivariate setting. This work is a continuation of earlier work of one of the authors [23], and our results build on the characterization of choice functions in terms of sets of binary preferences recently established by De Bock and De Cooman [7]. We obtain the independent natural extension in this framework. Given the generality of choice functions, our expression for the independent natural extension is the most general one we …Read more
  •  165
  •  126
    Independent natural extension for choice functions
    International Journal of Approximate Reasoning 390-413. 2023.
    We introduce an independence notion for choice functions, which we call ‘epistemic independence’ following the work by De Cooman et al. [17] for lower previsions, and study it in a multivariate setting. This work is a continuation of earlier work of one of the authors [29], and our results build on the characterization of choice functions in terms of sets of binary preferences recently established by De Bock and De Cooman [11]. We obtain the many-to-one independent natural extension in this fram…Read more
  •  118
    The twin pillars of Levi’s epistemology are his infallibilism and his corrigibilism. According to infallibilism, any agent is committed to being absolutely certain about anything she fully believes. From her own perspective, there is no serious possibility that any proposition she believes is false. She takes her own beliefs to be infallible, in this sense. But this need not make her dogmatic, on Levi’s view. According to his corrigibilism, an agent might come to have good reason to change her b…Read more
  •  38
    If chances are propensities, what reason do we have to expect them to be probabilities? I will offer a new answer to this question. It comes in two parts. First, I will defend an accuracy-centred account of what it is for a causal system to have precise propensities in the first place. Second, I will prove that, given some pretty weak assumptions about the nature of comparative causal dispositions, and some fairly standard assumptions about reasonable measures of inaccuracy, propensities must be…Read more
  •  7
    New Foundations for Imprecise Bayesianism
    Dissertation, University of Michigan. 2013.
    My dissertation examines two kinds of statistical tools for taking prior information into account, and investigates what reasons we have for using one or the other in different sorts of inference and decision problems. Chapter 1 describes a new objective Bayesian method for constructing `precise priors'. Precise prior probability distributions are statistical tools for taking account of your `prior evidence' in an inference or decision problem. `Prior evidence' is the wooly hodgepodge of informa…Read more