Wlodek Rabinowicz

This talk will focus on the contrast between aggregation of individual preference rankings to a collective preference ranking and aggregation of individual value judgments to a collective value judgment. The targeted case is one in which the individual judgments that are to be aggregated and the collective judgment that results from aggregation are value rankings. This means that, formally, both in the case of preferences and in the case of value judgments, aggregation takes profiles of rankings as inputs and delivers rankings as outputs. I am going to argue that, despite of this formal similarity, the kind of procedures that work fine for aggregation of judgments turns out to be inappropriate for aggregation of preferences. The relevant procedures consist in minimization of distance from the individual inputs. Whatever measure of distance is chosen, distance-based procedures violate the strong Pareto condition. This seems alright as value judgment aggregation goes, but would not be acceptable for preference aggregation, on the most natural interpretation of the latter task. When applied to judgment aggregation, distance-based aggregation procedures might also be approached from the epistemic perspective: questions might be raised about their advantages as truth-trackers. From this perspective, what matters is not only the probability of the output being true, but also its expected verisimilitude, or, to put it differently, its expected distance from truth.

Wlodek Rabinowicz, Lund University, Sweden and  London School of Economics, The UK