This essay explains how to use the calculus of consent framework to think more rigorously about self-governance, and applies this framework to the issue of evaluating federal regulatory agencies. Robust political economy is the idea that institutions should be designed to work well even under weak assumptions about decision-makers’ knowledge and benevolence. I show how the calculus of consent can be used to analyze both incentives and knowledge problems. The calculus is simultaneously a theory of self-governance and a tool for (...) robust political economy analysis. Applying this framework to the case of public administration leads to the conclusion that private goods (such as medicine) tend to be over-regulated, public goods tend to be under-regulated (such as enabling too much pollution), and regulatory agencies tend to be over-centralized (and should in most cases either be replaced with certification markets or moved to state level). (shrink)

Journal of Political Philosophy, EarlyView.

This essay argues that prediction markets, as one approach for aggregating dispersed private information, may not only be praised for their epistemic accuracy. They also feature characteristics that are morally desirable from the point of view of epistemic justice. Notably, they are a promising approach when we are trying to address testimonial injustice. The impersonality of market transactions effectively tackles the issue of identity prejudice, which underlies many forms of testimonial injustice. This is not to say that prediction markets do (...) not pose challenges for epistemic justice of their own like the risk of excluding knowers based on ability to pay. Or, in light of identity prejudice’s systematicity, the risk of discouraging some knowers because of differences in education or social background that lead to a certain unease when faced with prediction markets. The essay discusses these challenges, concedes limitations but also offers countermeasures to certain worries – e.g. hosting prediction markets on a play-money basis. Throughout, the essay addresses the question of the potential scope of using prediction markets for epistemic purposes, notably by means of the practical example of a prediction market for monetary policy. (shrink)

‘Epistemic’ arguments for conservatism typically claim that given the limits of human reason, we are better off accepting some particular social practice or institution rather than trying to consciously improve it. I critically examine and defend here one such argument, claiming that there are some domains of social life in which, given the limits of our knowledge and the complexity of the social world, we ought to defer to those institutions that have robustly endured in a wide variety of circumstances (...) in the past while not being correlated with intolerable outcomes. These are domains of social life in which our ignorance of optimal institutions is radical, and there is uncertainty about the costs of error. This is an argument for the preservation of particular institutions, not particular policies or outcomes, and it specifically identifies these with the institutions that John Rawls called ‘the basic structure of society.’ The argument further implies that to the extent that there is any reason to change these institutions, changes should be calculated as far as possible to increase their ‘epistemic power.’. (shrink)

This paper offers a comparison of three different kinds of collective attitudes: aggregate, common, and corporate attitudes. They differ not only in their relationship to individual attitudes—e.g., whether they are “reducible” to individual attitudes—but also in the roles they play in relation to the collectives to which they are ascribed. The failure to distinguish them can lead to confusion, in informal talk as well as in the social sciences. So, the paper’s message is an appeal for disambiguation.

Decision-making typically requires judgments about causal relations: we need to know the causal effects of our actions and the causal relevance of various environmental factors. We investigate how several individuals' causal judgments can be aggregated into collective causal judgments. First, we consider the aggregation of causal judgments via the aggregation of probabilistic judgments, and identify the limitations of this approach. We then explore the possibility of aggregating causal judgments independently of probabilistic ones. Formally, we introduce the problem of causal-network aggregation. (...) Finally, we revisit the aggregation of probabilistic judgments when this is constrained by prior aggregation of qualitative causal judgments. (shrink)

Many researchers have argued that humanity will create artificial general intelligence (AGI) within the next twenty to one hundred years. It has been suggested that AGI may inflict serious damage to human well-being on a global scale ('catastrophic risk'). After summarizing the arguments for why AGI may pose such a risk, we review the fieldʼs proposed responses to AGI risk. We consider societal proposals, proposals for external constraints on AGI behaviors and proposals for creating AGIs that are safe due to (...) their internal design. (shrink)