Jonathan Birch

In debates about animal sentience, the precautionary principle is often invoked. The idea is that when the evidence of sentience is inconclusive, we should “give the animal the benefit of the doubt” or “err on the side of caution” in formulating animal protection legislation. Yet there remains confusion as to whether it is appropriate to apply the precautionary principle in this context, and, if so, what “applying the precautionary principle” means in practice regarding the burden of proof for animal sentience. Here I construct a version of the precautionary principle tailored to the question of animal sentience together with a practical framework for implementing it. I explain and defend the key features of this framework, argue that it is well-aligned current practice in animal welfare science, and consider and reject a number of influential counterarguments to the use of precautionary reasoning in this area.

Various results show the ‘formal equivalence’ of kin and group selectionist methodologies, but this does not preclude there being a real and useful distinction between kin and group selection processes. I distinguish individual and population-centred approaches to drawing such a distinction, and I proceed to develop the latter. On the account I advance, the differences between kin and group selection are differences of degree in the structural properties of populations. A spatial metaphor (‘K-G space’) provides a useful framework for thinking about these differences: kin and group selection may be conceptualized as large, overlapping regions of K-G space. I then consider some implications of the account, defend it from possible objections, and further argue that the structural features characteristic of both kin and group selection may recur at multiple levels of biological organization.

The notion that natural selection is a process of fitness maximization gets a bad press in population genetics, yet in other areas of biology the view that organisms behave as if attempting to maximize their fitness remains widespread. Here I critically appraise the prospects for reconciliation. I first distinguish four varieties of fitness maximization. I then examine two recent developments that may appear to vindicate at least one of these varieties. The first is the ‘new’ interpretation of Fisher’s fundamental theorem of natural selection, on which the theorem is exactly true for any evolving population that satisfies some minimal assumptions. The second is the Formal Darwinism project, which forges links between gene frequency change and optimal strategy choice. In both cases, I argue that the results fail to establish a biologically significant maximization principle. I conclude that it may be a mistake to look for universal maximization principles justified by theory alone. A more promising approach may be to find maximization principles that apply conditionally and to show that the conditions were satisfied in the evolution of particular traits.

In an incendiary 2010 Nature article, M. A. Nowak, C. E. Tarnita and E. O. Wilson present a savage critique of the best known and most widely used framework for the study of social evolution, W. D. Hamilton’s theory of kin selection. Over a hundred biologists have since rallied to the theory’s defence, but Nowak et al. maintain that their arguments ‘stand unrefuted’. Here I consider the most contentious claim Nowak et al. defend: that Hamilton’s rule, the core explanatory principle of kin selection theory, ‘almost never holds’. I first distinguish two versions of Hamilton’s rule in contemporary theory: a special version (HRS) that requires restrictive assumptions, and a general version (HRG) that does not. I then show that Nowak et al. are most charitably construed as arguing that HRS almost never holds, while HRG buys its generality at the expense of explanatory power. While their arguments against HRS are fairly uncontroversial, their arguments against HRG are more contentious, yet these have been largely overlooked in the ensuing furore. I consider the arguments for and against the explanatory value of HRG, with a view to assessing what exactly is at stake in the debate. I suggest that the debate hinges on issues concerning the causal interpretability of regression coefficients, and concerning the explanatory function Hamilton’s rule is intended to serve.

Cooperation is rife in the microbial world, yet our best current theories of the evolution of cooperation were developed with multicellular animals in mind. Hamilton’s theory of inclusive fitness is an important case in point: applying the theory in a microbial setting is far from straightforward, as social evolution in microbes has a number of distinctive features that the theory was never intended to capture. In this article, I focus on the conceptual challenges posed by the project of extending Hamilton’s theory to accommodate the effects of gene mobility. I begin by outlining the basics of the theory of inclusive fitness, emphasizing the role that the concept of relatedness is intended to play. I then provide a brief history of this concept, showing how, over the past fifty years, it has departed from the intuitive notion of genealogical kinship to encompass a range of generalized measures of genetic similarity. I proceed to argue that gene mobility forces a further revision of the concept. The reason in short is that, when the genes implicated in producing social behaviour are mobile, we cannot talk of an organism’s genotype simpliciter; we can talk only of an organism’s genotype at a particular stage in its life cycle. We must therefore ask: with respect to which stage(s) in the life cycle should relatedness be evaluated? For instance: is it genetic similarity at the time of social interaction that matters to the evolution of social behaviour, or is it genetic similarity at the time of reproduction? I argue that, strictly speaking, it is neither of these: what really matters to the evolution of social behaviour is diachronic genetic similarity between the producers of fitness benefits at the time they produce them and the recipients of those benefits at the end of their life-cycle. I close by discussing the implications of this result. The main payoff is that it makes room for a possible new mechanism for the evolution of altruism in microbes that does not require correlated interaction among bearers of the genes for altruism. The importance of this mechanism in nature remains an open empirical question.

We face two urgent challenges concerning consciousness and AI. Challenge One is that millions of users will soon misattribute human-like consciousness to AI friends, partners, and assistants on the basis of mimicry and role-play, and we don’t know how to prevent this. Challenge Two is that profoundly alien forms of consciousness might genuinely be achieved in AI, but our theoretical understanding of consciousness is too immature to provide confident answers one way or the other. Centrism about AI consciousness is the position that we must take both challenges seriously. The two challenges interact in ways that make this difficult. Steps to address Challenge One might undermine attempts to address Challenge Two by portraying the idea of conscious AI as impossible or inherently unlikely. Conversely, attempts to address Challenge Two might lead to higher levels of misattribution from ordinary users. This “manifesto” attempts to construct mutually consistent strategies for addressing both challenges.

In this report, we argue that there is a realistic possibility that some AI systems will be conscious and/or robustly agentic in the near future. That means that the prospect of AI welfare and moral patienthood — of AI systems with their own interests and moral significance — is no longer an issue only for sci-fi or the distant future. It is an issue for the near future, and AI companies and other actors have a responsibility to start taking it seriously. We also recommend three early steps that AI companies and other actors can take: They can (1) acknowledge that AI welfare is an important and difficult issue (and ensure that language model outputs do the same), (2) start assessing AI systems for evidence of consciousness and robust agency, and (3) prepare policies and procedures for treating AI systems with an appropriate level of moral concern. To be clear, our argument in this report is not that AI systems definitely are — or will be — conscious, robustly agentic, or otherwise morally significant. Instead, our argument is that there is substantial uncertainty about these possibilities, and so we need to improve our understanding of AI welfare and our ability to make wise decisions about this issue. Otherwise there is a significant risk that we will mishandle decisions about AI welfare, mistakenly harming AI systems that matter morally and/or mistakenly caring for AI systems that do not.

Martha Nussbaum’s Justice for Animals calls upon humanity to secure for all sentient beings the central capabilities they need to flourish. This essay review critically examines the ethical and scientific foundations of Nussbaum’s position. On the ethical side, we explore the tension between a robust defence of animal rights and political liberalism, which requires tolerance of a range of reasonable views. On the scientific side, we reflect on how our uncertainty regarding the distribution of sentience in the natural world leaves us uncertain about how many claimants of justice there are and about the relative strength of their claims. We bring out some further problems with Nussbaum’s views on animal killing and pest control. We also reflect on how animal welfare science might be done differently if guided by Nussbaum’s framework.

The Evolution of the Sensitive Soul is a landmark attempt to make progress on the problem of animal consciousness. Ginsburg and Jablonka propose a general cognitive marker of the presence of consciousness: Unlimited Associative Learning. They use this marker to defend a generous view about the distribution of consciousness in the natural world, on which a capacity for conscious experience is common to all vertebrates, many arthropods and some cephalopod molluscs. They use this inferred distribution to defend a view about the evolution of consciousness, on which it has evolved at least three times, first evolved at around the time of the Cambrian explosion (just over 500 million years ago), and was in fact the driving force behind that explosion. In this essay review, I reflect critically on the book’s central idea: the proposal that Unlimited Associative Learning provides a general marker of consciousness.

Andrew Bourke’s Principles of Social Evolution identifies three stages that characterize an evolutionary transition in individuality and deploys inclusive fitness theory to explain each stage. The third stage, social group transformation, has hitherto received relatively little attention from inclusive fitness theorists. In this review, I first discuss Bourke’s “virtual dominance” hypothesis for the evolution of the germ line. I then contrast Bourke’s inclusive fitness approach to the major transitions with the multi-level approach developed by Richard Michod, Samir Okasha and others. I suggest that, rather than choosing between these approaches, we should exploit the strengths of both. Finally, I stress the need for a firmer conceptual grasp of the nature of social group transformation.

Octopuses, squid, and cuttlefish are remarkable creatures, famed for their intelligence. They are invertebrates—animals without a backbone—and are much more distant from us in evolutionary terms than our fellow mammals, far more distant even than birds, reptiles, and fishes. The last common ancestor of humans and octopuses lived over 560 million years ago. These animals have evolved intelligence by a different path, and their ways of perceiving and interacting with the world are very different from our own. This resource aims to take you inside the minds of octopuses, squid, cuttlefish, and their lesser-known relatives, the nautiluses, using the latest scientific evidence to present an accurate, up-to-date picture of what we know about their capabilities.

Motivational trade-off behaviours, where an organism behaves as if flexibly weighing up an opportunity for reward against a risk of injury, are often regarded as evidence that the organism has valenced experiences like pain. This type of evidence has been influential in shifting opinion regarding crabs and insects. Critics note that (i) the precise links between trade-offs and consciousness are not fully known; (ii) simple trade-offs are evinced by the nematode worm Caenorhabditis elegans, mediated by a mechanism plausibly too simple to support conscious experience; (iii) pain can sometimes interfere with rather than support making trade-offs rationally. However, rather than undermining trade-off evidence in general, such cases show that the nature of the trade-off, and its underlying neural substrate, matter. We investigate precisely how.

This paper attempts to reconcile critics and defenders of inclusive fitness by constructing a synthesis that does justice to the insights of both. I argue that criticisms of the regression-based version of Hamilton’s rule, although they undermine its use for predictive purposes, do not undermine its use as an organizing framework for social evolution research. I argue that the assumptions underlying the concept of inclusive fitness, conceived as a causal property of an individual organism, are unlikely to be exactly true in real populations, but they are approximately true given a specific type of weak selection that Hamilton took, on independent grounds, to be responsible for the cumulative assembly of complex adaptation. Finally, I reflect on the uses and limitations of “design thinking” in social evolution research. The debate about the foundations of inclusive fitness theory that has followed in the wake of Nowak, Tarnita and Wilson’s (1) critique has been remarkably polarizing. After several rounds of rebuttals and replies, there is still little evidence of any serious reconciliation between the theory’s critics (2-10) and its defenders (11-24). It doesn’t have to be this way. I believe that, on the main points of disagreement, it is possible to find a way forward that does justice to the insights of both camps. My aim in this paper is to find that way forward.

The sense of fairness is a central aspect of human moral psychology. Intuitions about fairness lead to many widespread moral beliefs, such as the belief that the punishment should fit the crime or the belief that one deserves a fair share of what one has earned. In The Origins of Fairness, Nicolas Baumard sets out to shed light on the evolutionary origin of these intuitions. He argues that the human sense of fairness is innate and universal, and he offers an account of its evolution that highlights the role of bargaining in early human “cooperation markets.”