Jonathan Birch

Most of the contributions to Cooperation and Its Evolution grapple with the distinctive challenges presented by the project of explaining human sociality. Many of these puzzles have a ‘chicken and egg’ character: our virtually unparalleled capacity for large-scale cooperation is the product of psychological, behavioural, and demographic changes in our recent evolutionary history, and these changes are linked by complex patterns of reciprocal dependence. There is much we do not yet understand about the timing of these changes, and about the order in which different aspects of human social psychology (co-)evolved. In this review essay, I discuss four such puzzles the volume raises. These concern punishment and norm-psychology, moral judgement and the moral emotions, hierarchy and top-down coercion, and property rights and legal systems.

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.

I consider some hitherto unexplored examples of teleological language in the sciences. In explicating these examples, I aim to show (a) that such language is not the sole preserve of the biological sciences, and (b) that not all such talk is reducible to the ascription of functions. In chemistry and biochemistry, scientists explaining molecular rearrangements and protein folding talk informally of molecules rearranging “in order to” maximize stability. Evolutionary biologists, meanwhile, often speak of traits evolving “in order to” optimize some fitness-relevant variable. I argue that in all three contexts such locutions are best interpreted as shorthands for more detailed explanations which, were we to spell them out in full, would show that the relevant process would robustly converge towards the same end-point despite variation in initial conditions. This suggests that, in biology, such talk presupposes a substantial form of adaptationism. The upshot is that such shorthands may be more applicable in the physical sciences than the biological.

An influential argument due to Elliott Sober, subsequently strengthened by Denis Walsh and Joel Pust, moves from plausible premises to the bold conclusion that natural selection cannot explain the traits of individual organisms. If the argument were sound, the explanatory scope of selection would depend, surprisingly, on metaphysical considerations concerning origin essentialism. I show that the Sober-Walsh-Pust argument rests on a flawed counterfactual criterion for explanatory relevance. I further show that a more defensible criterion for explanatory relevance recently proposed by Michael Strevens lends support to the view that natural selection can be relevant to the explanation of individual traits.

How can we investigate non-human experiences scientifically? Given substantial differences in sensory abilities and the private nature of consciousness, this remains an open question. In this review, we propose a way to gain empirical traction on one key feature of experience: its temporal structure, or 'timescape'. Perceptual contents follow systematic temporal principles-synchronisation, revision, and persistence-and are sampled across attentional windows and vary in stability. These principles can be explored through temporal illusions and experimental paradigms. We conceptualise an animal's timescape in terms of five key windows, all of which are experimentally testable, and analyse evidence across animal species to highlight varying timescapes. Together, these ideas lay the foundations for a research programme comparing the temporal Umwelts of non-human animals.

Inclusive fitness theory was not originally designed to explain the major transitions in evolution, but there is a growing consensus that it has the resources to do so. My aim in this paper is to highlight, in a constructive spirit, the puzzles and challenges that remain. I first consider the distinctive aspects of the cooperative interactions we see within the most complex social groups in nature: multicellular organisms and eusocial insect colonies. I then focus on one aspect in particular: the extreme redundancy these societies exhibit. I argue that extreme redundancy poses a distinctive explanatory puzzle for inclusive fitness theory, and I offer a potential solution which casts coercion as the key enabler. I suggest that the general moral to draw from the case is one of guarded optimism: while inclusive fitness is a powerful tool for understanding evolutionary transitions, it must be integrated within a broader framework that recognizes the distinctive problems such transitions present and the distinctive mechanisms by which these problems may be overcome.

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.

The three commentaries on “Ethics for a large sentient world” raise several problems for a Gandhian approach to animal ethics. In my responses, I defend my position that granting robust rights to individual insects is untenable, pushing us to look harder at alternative options. I explain how Gandhi’s commitment to nonviolence allows him to avoid the unwelcome implications his principles might otherwise have. I consider his nuanced position on the interplay between general principles and embedded responses to particular situations. I explain why he should not be read as an antinatalist. That said, his framework undeniably presents an austere ascetic ideal that calls on us to rethink the meaning of “progress”. The framework condemns many aspects of modern industrialized economies, not just their treatment of non-human animals.

Positions that link rights to sentience face an insect challenge: insects are plausibly sentient, yet recognizing individual insects as rights-bearers would problematize public health, veterinary and agricultural benefits obtained by harming them. The most obvious responses seem inadequate. Indian animal ethics, which has always taken the idea of insect sentience seriously, is a promising place to look for further options. Of particular relevance is the idea of ahimsa (nonviolence, noninjury), but ahimsa in its ancient form has metaphysical commitments that secular animal ethics should not accept. More promising still is the progressive ahimsaism developed by Gandhi in the 1920s, on which duties of non-maleficence can be overridden by duties of care, provided the duty of care is adopted, interpreted and exercised in accordance with the guiding ideal of ahimsa. This article provides an exposition and analysis of the view and relates it to the insect challenge.

Some patients, following brain injury, do not outwardly respond to spoken commands, yet show patterns of brain activity that indicate responsiveness. This is ‘cognitive-motor dissociation’ (CMD). Recent research has used machine learning to diagnose CMD from electroencephalogram recordings. These techniques have high false discovery rates, raising a serious problem of inductive risk. It is no solution to communicate the false discovery rates directly to the patient’s family, because this information may confuse, alarm and mislead. Instead, we need a procedure for generating case-specific probabilistic assessments that can be communicated clearly. This article constructs a possible procedure with three key elements: (1) A shift from categorical ‘responding or not’ assessments to degrees of evidence; (2) The use of patient-centred priors to convert degrees of evidence to probabilistic assessments; and (3) The use of standardised probability yardsticks to convey those assessments as clearly as possible.

نواجه تحدّيين عاجلين فيما يتعلّق بالوعي والذكاء الاصطناعي. يتمثّل التحدّي الأول في أنّ ملايين المستخدمين سيُسيئون قريبًا إسناد وعيٍ شبيهٍ بالوعي البشري إلى أصدقاء الذكاء الاصطناعي وشركائهم ومساعديهم، استنادًا إلى المحاكاة ولعب الأدوار، ولا نعرف كيف يمكن منع ذلك. أمّا التحدّي الثاني فهو أنّ أشكالًا غريبةً وعميقةً للغاية من الوعي قد تتحقق فعلًا في الذكاء الاصطناعي، لكن فهمنا النظري للوعي لا يزال غير ناضج بما يكفي لتقديم إجابات واثقة، سواء بالإيجاب أو بالنفي. والموقف الوسطي بشأن وعي الذكاء الاصطناعي هو أنّ علينا أخذ هذين التحدّيَين على محمل الجد. ويتفاعل التحدّيان بطرق تجعل الأمر صعبًا؛ فالإجراءات الرامية إلى معالجة التحدّي الأول قد تُضعف محاولات معالجة التحدّي الثاني عبر تصوير فكرة الوعي الاصطناعي على أنّها مستحيلة أو غير مرجّحة بطبيعتها. وفي المقابل، قد تؤدي محاولات معالجة التحدّي الثاني إلى ارتفاع مستويات إسناد الوعي الخاطئ لدى المستخدمين العاديين. ويحاول هذا "البيان" صياغة استراتيجيات متسقة متبادلة للتعامل مع كلا التحدّيين.

Nick Bostrom’s ‘Simulation Argument’ purports to show that, unless we are confident that advanced ‘posthuman’ civilizations are either extremely rare or extremely rarely interested in running simulations of their own ancestors, we should assign significant credence to the hypothesis that we are simulated. I argue that Bostrom does not succeed in grounding this constraint on credence. I first show that the Simulation Argument requires a curious form of selective scepticism, for it presupposes that we possess good evidence for claims about the physical limits of computation and yet lack good evidence for claims about our own physical constitution. I then show that two ways of modifying the argument so as to remove the need for this presupposition fail to preserve the original conclusion. Finally, I argue that, while there are unusual circumstances in which Bostrom’s selective scepticism might be reasonable, we do not currently find ourselves in such circumstances. There is no good reason to uphold the selective scepticism the Simulation Argument presupposes. There is thus no good reason to believe its conclusion.

Rapid advances in artificial intelligence (AI) have led users to believe that systems such as large language models (LLMs) have mental states, including the capacity for ‘experience’ (e.g., emotions and consciousness). These folk-psychological attributions often diverge from expert opinion and are distinct from attributions of ‘intelligence’ (e.g., reasoning, planning), and yet may affect trust in AI systems. While past work provides some support for a link between anthropomorphism and trust, the impact of attributions of consciousness and other aspects of mentality on user trust remains unclear. We explored this in a preregistered experiment (N = 410) in which participants rated the capacity of an LLM to exhibit consciousness and a variety of other mental states. They then completed a decision-making task where they could revise their choices based on the advice of an LLM. Bayesian analyses revealed strong evidence against a positive correlation between attributions of consciousness and advice-taking; indeed, a dimension of mental states related to experience showed a negative relationship with advice-taking, while attributions of intelligence were strongly correlated with advice acceptance. These findings highlight how users’ attitudes and behaviours are shaped by sophisticated intuitions about the capacities of LLMs—with different aspects of mental state attribution predicting people’s trust in these systems.

I contrast my picture of the relationship between the science and policy of animal sentience with that of Marian Stamp Dawkins, who thinks “the science of animal sentience and the politics of animal welfare should be kept separate” because they involve irreconcilably different standards of evidence. On my alternative picture, (i) the science of animal sentience, like any other empirical science, delivers evidence but not certainty; (ii) this evidence allows us to make better practical decisions, both within and outside science and (iii) the quality standards we apply to the evidence should be high in all contexts, including the formulation of public policy.

Definitions of animal welfare often invoke consciousness or sentience. Marian Stamp Dawkins has argued that to define animal welfare this way is a mistake. In Dawkins’s alternative view, an animal with good welfare is one that is healthy and “has what it wants.” The dispute highlights a source of strain on the concept of animal welfare: consciousness-involving definitions are better able to capture the normative significance of welfare, whereas consciousness-free definitions facilitate the validation of welfare indicators. I reflect on how the field should respond to this strain, ultimately recommending against splitting the concept and in favor of consciousness-involving definitions.

I briefly present and motivate a 'skill hypothesis' regarding the evolution of human normative cognition. On this hypothesis, the capacity to internally represent action-guiding norms evolved as a solution to the distinctive problems of standardizing, learning and teaching complex motor skills and craft skills, especially skills related to toolmaking. We have an evolved cognitive architecture for internalizing norms of technique, which was then co-opted for a rich array of social functions. There was a gradual expansion of the normative domain, with ritual playing an important role in bridging the gap between concrete, enacted norms and general, abstract norms, such as kinship norms. I conclude by stating nine predictions arising from the skill hypothesis.

This is a response to the nine commentaries on our target article “Unlimited Associative Learning: A primer and some predictions”. Our responses are organized by theme rather than by author. We present a minimal functional architecture for Unlimited Associative Learning (UAL) that aims to tie to together the list of capacities presented in the target article. We explain why we discount higher-order thought (HOT) theories of consciousness. We respond to the criticism that we have overplayed the importance of learning and underplayed the importance of spatial modelling. We decline the invitation to add a negative marker to our proposed positive marker so as to rule out consciousness in plants, but we nonetheless maintain that there is no positive evidence of consciousness in plants. We close by discussing how UAL relates to development and to its material substrate.

Kantian ethics has struggled terribly with the challenge of incorporating non-human animals as beings to which we can owe obligations. Christine Korsgaard’s Fellow Creatures is a bold, substantial attempt to meet that challenge. It is a significant book. In this essay, I won’t attempt a chapter-by-chapter summary. I will set the scene for the book’s core argument (which comes rather late, in Chapter 8), offer a reconstruction of that argument, and reflect on its strengths and limitations. I’ll also briefly compare the view at which Korsgaard arrives to that of Tom Regan in The Case for Animal Rights (1983).

Simona Ginsburg and Eva Jablonka: The Evolution of the Sensitive Soul: Learning and the Origins of Consciousness. MIT Press, Cambridge, MA, 2019, 646pp, ISBN: 9780262039307 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.

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.

Hamilton's theory of kin selection is the best-known framework for understanding the evolution of social behavior but has long been a source of controversy in evolutionary biology. A recent critique of the theory by Nowak, Tarnita, and Wilson sparked a new round of debate, which shows no signs of abating. In this overview, we highlight a number of conceptual issues that lie at the heart of the current debate. We begin by emphasizing that there are various alternative formulations of Hamilton's rule, including a general version, which is always true; an approximate version, which assumes weak selection; and a special version, which demands other restrictive assumptions. We then examine the relationship between the neighbor-modulated fitness and inclusive fitness approaches to kin selection. Finally, we consider the often-strained relationship between the theories of kin and multilevel selection.