Christian List

Suppose a committee, expert panel or other group is making judgements on some issues, where these may be not just yes/no questions, such as whether a defendant is guilty, but also variables with many possible values, such as macroeconomic or meteorological variables or travel directions. Furthermore, there may be interconnections between different issues, as in the case of economic or climate variables. How can the group arrive at ‘intelligent’ collective judgements, based on the group members’ individual judgements? We investigate three challenges raised by this judgement-aggregation problem. First, reasonable methods of aggregation (such as defining the collective judgement for each issue as the average or median judgement) can produce inconsistent collective judgements. Second, many methods of aggregation are manipulable by strategic voting. Finally, not all methods of aggregation are conducive to tracking the truth on the issues in question. We prove new impossibility or possibility theorems on all three challenges, identifying what it takes to produce collective judgements in a consistent, non-manipulable and truth-tracking manner and thereby to achieve collective intelligence through aggregation. Overall, the median method, though imperfect, performs reasonably well. We also note the relevance of our analysis for non-human group decisions. This article is part of the theme issue ‘The evolution of collective intelligence’.

We present a seven-pronged no-go result for quantum mechanics: a “heptalemma”. It shows that seven initially plausible theses about physical reality are jointly inconsistent with the predictions of quantum mechanics, while any six are jointly consistent. We must then decide which theses to retain and which to give up. Since different interpretations of quantum mechanics entail different responses to the heptalemma, we get a novel taxonomy of such interpretations. Beyond the application to quantum mechanics, the heptalemma offers a general diagnostic criterion for determining whether a given scientific domain should count as classical or not, and if not, how it departs from classicality.

While there has been much discussion of whether AI systems could function as moral agents or acquire sentience, there has been very little discussion of whether AI systems could have free will. I sketch a framework for thinking about this question, inspired by Daniel Dennett’s work. I argue that, to determine whether an AI system has free will, we should not look for some mysterious property, expect its underlying algorithms to be indeterministic, or ask whether the system is unpredictable. Rather, we should simply ask whether we have good explanatory reasons to view the system as an intentional agent, with the capacity for choice between alternative possibilities and control over the resulting actions. If the answer is “yes”, then the system counts as having free will in a pragmatic and diagnostically useful sense.

In this paper, I argue that no theory of consciousness can simultaneously respect four initially plausible metaphysical claims—namely ‘first-person realism’, ‘non-solipsism’, ‘non-fragmentation’, and ‘one world’—but that any three of the four claims are mutually consistent. So, theories of consciousness face a ‘quadrilemma’. Since it will be hard to achieve a consensus on which of the four claims to retain and which to give up, we arrive at a landscape of competing theories, all of which have pros and cons. I will briefly indicate which kinds of theories correspond to the four horns of the quadrilemma.

Judgment-aggregation theory has always focused on the attainment of rational collective judgments. But so far, rationality has been understood in static terms: as coherence of judgments at a given time, defined as consistency, completeness, and/or deductive closure. This paper asks whether collective judgments can be dynamically rational, so that they change rationally in response to new information. Formally, a judgment aggregation rule is dynamically rational with respect to a given revision operator if, whenever all individuals revise their judgments in light of some information (a learnt proposition), then the new aggregate judgments are the old ones revised in light of this information, i.e., aggregation and revision commute. We prove an impossibility theorem: if the propositions on the agenda are non-trivially connected, no judgment aggregation rule with standard properties is dynamically rational with respect to any revision operator satisfying some basic conditions. Our theorem is the dynamic-rationality counterpart of some well-known impossibility theorems for static rationality. We also explore how dynamic rationality might be achieved by relaxing some of the conditions on the aggregation rule and/or the revision operator. Notably, premise-based aggregation rules are dynamically rational with respect to so-called premise-based revision operators.

Real human agents, even when they are rational by everyday standards, sometimes assign different credences to objectively equivalent statements, such as ‘Orwell is a writer’ and ‘E.A. Blair is a writer’, or credences less than 1 to necessarily true statements, such as not-yet-proven theorems of arithmetic. Anna Mahtani calls this the phenomenon of ‘opacity’. Opaque credences seem probabilistically incoherent, which goes against a key modelling assumption of probability theory. I sketch a modelling strategy for capturing opaque credence assignments without abandoning probabilistic coherence. I draw on ideas from judgement-aggregation theory, where we face similar challenges of defining the ‘objects of judgement’.

Michael S. Moore defends the ideas of free will and responsibility, especially in relation to criminal law, against several challenges from neuroscience. I agree with Moore that morality and the law presuppose a commonsense understanding of humans as rational agents, who make choices and act for reasons, and that to defend moral and legal responsibility, we must show that this commonsense understanding remains viable. Unlike Moore, however, I do not think that classical compatibilism, which is based on a conditional understanding of the ability to do otherwise, provides a sufficiently robust account of free will, even when it is amended as Moore suggests. I argue that free will and responsibility can be defended more robustly by observing that, at the level of agency, there can be alternative possibilities and mental causation in a stronger sense than recognized by classical compatibilism, even if physical determinism is true. Moore’s arguments could thus be strengthened by embracing this compatibilist libertarian position. At the same time, I note that, although the idea of responsibility is robustly defensible, there are independent reasons for rejecting a retributivist approach to punishment.

The aim of this exploratory paper is to review an under-appreciated parallel between group agency and artificial intelligence. As both phenomena involve non-human goal-directed agents that can make a difference to the social world, they raise some similar moral and regulatory challenges, which require us to rethink some of our anthropocentric moral assumptions. Are humans always responsible for those entities’ actions, or could the entities bear responsibility themselves? Could the entities engage in normative reasoning? Could they even have rights and a moral status? I will tentatively defend the (increasingly widely held) view that, under certain conditions, artificial intelligent systems, like corporate entities, might qualify as responsible moral agents and as holders of limited rights and legal personhood. I will further suggest that regulators should permit the use of autonomous artificial systems in high-stakes settings only if they are engineered to function as moral (not just intentional) agents and/or there is some liability-transfer arrangement in place. I will finally raise the possibility that if artificial systems ever became phenomenally conscious, there might be a case for extending a stronger moral status to them, but argue that, as of now, this remains very hypothetical.