to appear in Ergo
It is often suggested that when opinions differ among individuals in a group, the opinions should be aggregated to form a compromise. This paper compares two approaches to aggregating opinions, linear pooling and what I call opinion agglomeration. In evaluating both strategies, I propose a pragmatic criterion, No Regrets, entailing that an aggregation strategy should prevent groups from buying and selling bets on events at prices regretted by their members. I show that only opinion agglomeration is able to satisfy the demand. I then proceed to give normative and empirical arguments in support of the pragmatic criterion for opinion aggregation, and that ultimately favor opinion agglomeration.
to appear in The British Journal for Philosophy of Science. (with Matteo Colombo & Stephan Hartmann)
Some naturalistic philosophers of mind subscribing to the predictive processing theory of mind have adopted a realist attitude towards the results of Bayesian cognitive science. In this paper, we argue that this realist attitude is unwarranted. The Bayesian research program in cognitive science does not possess special epistemic virtues over alternative approaches for explaining mental phenomena involving uncertainty. In particular, the Bayesian approach is not simpler, more unifying, or more rational than alternatives. It is also contentious that the Bayesian approach is overall better supported by the empirical evidence. So, to develop philosophical theories of mind on the basis of a realist interpretation of results from Bayesian cognitive science is unwarranted. Naturalistic philosophers of mind should instead adopt an anti-realist attitude towards these results and remain agnostic as to whether Bayesian models are true. For continuing on with an exclusive focus and praise of Bayes within debates about the predictive processing theory will impede progress in philosophical understanding of scientific practice in computational cognitive science as well as of the architecture of the mind.
Noûs 52, no. 2 (2018): 260-278. (with Gregory Wheeler)
Two compelling principles, the Reasonable Range Principle and the Preservation of Irrelevant Evidence Principle, are necessary conditions that any response to peer disagreements ought to abide by. The Reasonable Range Principle maintains that a resolution to a peer disagreement should not fall outside the range of views expressed by the peers in their dispute, whereas the Preservation of Irrelevant Evidence (PIE) Principle maintains that a resolution strategy should be able to preserve unanimous judgments of evidential irrelevance among the peers. No standard Bayesian resolution strategy satisfies the PIE Principle, however, and we give a loss aversion argument in support of PIE and against Bayes. The theory of imprecise probability allows one to satisfy both principles, and we introduce the notion of a set-based credal judgment to frame and address a range of subtle issues that arise in peer disagreements.
The Reasoner 9, no. 9 (2015): 76-77.
In this note, I show that AGM belief contraction is appropriate for modeling an epistemically modest response to a disagreement with an epistemic peer.
The Precautionary Principle and Expert Disagreement
Martin Peterson has argued that in conforming to the so-called Precautionary Principle in case of expert disagreement, decision makers should follow the ecumenical principle: all expert views should be considered, not just those that are the most prominent or influential. In carefully defining the ecumenical principle, Peterson characterizes the doxastic commitments of decision makers qualitatively and deliberately precludes probabilistic judgments, as he claims that probabilities may provide decision makers with information that is more precise than warranted. In this note, I argue, contra Peterson, that there is a feasible probabilistic interpretation of the doxastic commitments of decision makers under the ecumenical principle in which conflicting expert judgments are combined if probabilities are construed more broadly as set-based, imprecise probabilities, e.g., 45-80% probability that X. Besides avoiding the concern of probabilities overstating the evidence, the probabilistic account of the EP proposed avoids an opposite problem Peterson’s account is highly susceptible to, namely, understating the evidence, thus making it more plausible than his purely qualitative account.
Normative Uncertainty Meets Social Choice Theory
William MacAskill (2016) cleverly combines elements of social choice theory and expected value theory in forming a proposal for decision making under normative uncertainty that he calls the Borda Rule. However, the decision criterion is challenged by incomplete orderings of the options available to a decision maker. In this paper, I show that MacAskill’s robustified extension of the Borda Rule is an unsatisfying solution to the problem and propose amending it with a Borda scoring rule for partially ordered ballots. Besides avoiding the struggles MacAskill’s robust version faces, I demonstrate that the amended rule better accommodates group decision making under normative uncertainty—a matter that has yet to receive serious attention.