Colin Allen

Seven chimpanzees in twenty-seven experiments run over the course of five years at his University of Louisiana laboratory in New Iberia, Louisiana, are at the heart of Daniel Povinelli’s case that chimpanzee thinking about the physical world is not at all like that of humans. Chimps, according to Povinelli and his coauthors James Reaux, Laura Theall, and Steve Giambrone, are phenomenally quick at learning to associate visible features of tools with specific uses of those tools, but they appear to lack cognitive access to forces and other invisible causal features of those tools. Povinelli’s chimps appar- ently rely on a trial-and-error strategy to learn whether a particular tool is suitable for a particular task, and and having mastered one task they appear unable to generalize to other tasks on the basis of tool properties that are not directly visible. Thus, for instance, Povinelli’s research subjects did not immediately recognize that a tool that had been demonstrated to be non- rigid would be unsuitable for dragging a piece of food towards them. When presented with a choice between a rigid, T-shaped “rake” that they had used many times previously and a rake with non-rigid arms, Povinelli and Reaux found, over the course of eight trials, that their chimps chose the non-rigid rake as frequently as they chose the rigid one (experiment 9, chapter 7).

Wittgenstein famously ended his Tractatus Logico-Philosophicus (Wittgenstein 1922) by writing: "Whereof one cannot speak, one must pass over in silence." (Wovon man nicht sprechen kann, darüber muss man schweigen.) In that earliest work, Wittgenstein gives no clue about whether this aphorism applied to animal minds, or whether he would have included philosophical discussions about animal minds as among those displaying "the most fundamental confusions (of which the whole of philosophy is full)" (1922, TLP 3.324), but given his later writings on language and thought, it seems a plausible hypothesis. Years later he wrote in the Philosophical Investigations (1968, p. 223) another aphoristic statement: "If a lion could speak, we would not understand him." (Wenn der Löwe sprechen könnte, wir könnten ihn nicht verstehen.) Decades of philosophical discussion about what Wittgenstein meant by these remarks illustrate another point: when philosophers speak, we do not fully understand them.

Discussions of the functions of biological traits generally take the notion of a trait for granted. Defining this notion is a non-trivial problem. Different approaches to function place different constraints on adequate accounts of the notion of a trait. Accounts of function based on engineering-style analyses allow trait boundaries to be a matter of human interest. Accounts of function based on natural selection have typically been taken to require trait boundaries that are objectively real. After canvassing problems raised by each approach, I conclude with some facts that satisfactory notions of trait must respect.

In the last decade it has become en vogue for cognitive comparative psychologists to study animal behavior in an ‘integrated’ fashion to account for both the ‘innate’ and the ‘acquired’. We will argue that these studies, instead of really integrating the concepts of ‘nature’ and ‘nurture’, rather cement this old dichotomy. They combine empty nativist interpretation of behavior systems with blatantly environmentalist explanations of learning. We identify the main culprit as the failure to take development seriously. While in some areas of biology interest in the relationship between behavior and development has surged through topics such as extragenetic inheritance, niche construction, and phenotypic plasticity, this has gone almost completely unnoticed in the study of animal behavior in comparative psychology, and is frequently ignored in ethology too. The main aims of this paper are to clarify the relationship between the concepts of learning, experience, and development, and to investigate whether and how all three concepts can be usefully deployed in the study of animal behavior. This will require the full integration of the psychological study of behavior into biology, and of the idea of learning into a wider concept of experience. We lay out how, in a systems view of development, learning may just appear as one among many processes in which experience influences behavior. This new synthesis should help to overcome the age-old dualism between innate and acquired. It thereby opens up the possibility of developing scientifically more fruitful distinctions.

The Indiana Philosophy Ontology (InPhO) project is presented as one of the first social-semantic web endeavors which aims to bootstrap feedback from users unskilled in ontology design into a precise representation of a specific domain. Our approach combines statistical text processing methods with expert feedback and logic programming approaches to create a dynamic semantic representation of the discipline of philosophy. We describe the basic principles and initial experimental results of our system.

Our goal in this paper is to provide enough of an account of the origins of cognitive ethology and the controversy surrounding it to help ethicists to gauge for themselves how to balance skepticism and credulity about animal minds when communicating with scientists. We believe that ethicists’ arguments would benefit from better understanding of the historical roots of ongoing controversies. It is not appropriate to treat some widely reported results in animal cognition as if their interpretations are a matter of scientific consensus. It is especially important to understand why loose references to “cognitive ethology” by philosophers can signal ignorance of the field to scientists who are more deeply immersed in the relevant literature. Understanding the variety of approaches to cognitive phenomena in animals is essential if such capacities are to form the foundation of scientifically-informed ethical reasoning about animals.

The development of autonomous, robotic weaponry is progressing rapidly. Many observers agree that banning the initiation of lethal activity by autonomous weapons is a worthy goal. Some disagree with this goal, on the grounds that robots may equal and exceed the ethical conduct of human soldiers on the battlefield. Those who seek arms-control agreements limiting the use of military robots face practical difficulties. One such difficulty concerns defining the notion of an autonomous action by a robot. Another challenge concerns how to verify and monitor the capabilities of rapidly changing technologies. In this article we describe concepts from our previous work about autonomy and ethics for robots and apply them to military robots and robot arms control. We conclude with a proposal for a first step toward limiting the deployment of autonomous weapons capable of initiating lethal force

The application of digital humanities techniques to philosophy is changing the way scholars approach the discipline. This paper seeks to open a discussion about the difficulties, methods, opportunities, and dangers of creating and utilizing a formal representation of the discipline of philosophy. We review our current project, the Indiana Philosophy Ontology (InPhO) project, which uses a combination of automated methods and expert feedback to create a dynamic computational ontology for the discipline of philosophy. We argue that our distributed, expert-based approach to modeling the discipline carries substantial practical and philosophical benefits over alternatives. We also discuss challenges facing our project (and any other similar project) as well as the future directions for digital philosophy afforded by formal modeling.

In this paper, we approach the idea of group cognition from the perspective of the “extended mind” thesis, as a special case of the more general claim that systems larger than the individual human, but containing that human, are capable of cognition (Clark, 2008; Clark & Chalmers, 1998). Instead of deliberating about “the mark of the cognitive” (Adams & Aizawa, 2008), our discussion of group cognition is tied to particular cognitive capacities. We review recent studies of group problem-solving and group memory which reveal that specific cognitive capacities that are commonly ascribed to individuals are also aptly ascribed at the level of groups. These case studies show how dense interactions among people within a group lead to both similarity-inducing and differentiating dynamics that affect the group's ability to solve problems. This supports our claim that groups have organization-dependent cognitive capacities that go beyond the simple aggregation of the cognitive capacities of individuals. Group cognition is thus an emergent phenomenon in the sense of Wimsatt (1986). We further argue that anybody who rejects our strategy for showing that cognitive properties can be instantiated at multiple levels in the organizational hierarchy on a priori grounds is a “demergentist,” and thus incurs the burden of proof for explaining why cognitive properties are “stuck” at a certain level of organizational structure. Finally, we show that our analysis of group cognition escapes the “coupling-constitution” charge that has been leveled against the extended mind thesis (Adams & Aizawa, 2008).

The demise of behaviorism has made ethologists more willing to ascribe mental states to animals. However, a methodology that can avoid the charge of excessive anthropomorphism is needed. We describe a series of experiments that could help determine whether the behavior of nonhuman animals towards dead conspecifics is concept mediated. These experiments form the basis of a general point. The behavior of some animals is clearly guided by complex mental processes. The techniques developed by comparative psychologists and behavioral ecologists are able to provide us with the tools to critically evaluate hypotheses concerning the continuity between human minds and animal minds.

A principal goal of the discipline of artificial morality is to design artificial agents to act as if they are moral agents. Intermediate goals of artificial morality are directed at building into AI systems sensitivity to the values, ethics, and legality of activities. The development of an effective foundation for the field of artificial morality involves exploring the technological and philosophical issues involved in making computers into explicit moral reasoners. The goal of this paper is to discuss strategies for implementing artificial morality and the differing criteria for success that are appropriate to different strategies.

Few areas of scientific investigation have spawned more alternative approaches than animal behavior: comparative psychology, ethology, behavioral ecology, sociobiology, behavioral endocrinology, behavioral neuroscience, neuroethology, behavioral genetics, cognitive ethology, developmental psychobiology---the list goes on. Add in the behavioral sciences focused on the human animal, and you can continue the list with ethnography, biological anthropology, political science, sociology, psychology (cognitive, social, developmental, evolutionary, etc.), and even that dismal science, economics. Clearly, no reasonable-length chapter can do justice to such a varied collection. We have opted therefore to focus on three of these subdisciplines and to provide a somewhat historical tour of them, mentioning along the way the philosophical points that are of particular interest to us, but allowing the development of these points to be limited only by the imaginations of our readers. For readers seeking a more-traditional historical survey, see Dewsbury (1984a, b) and Burghardt (1985a). Our chosen brief is to write about comparative psychology, ethology, and cognitive ethology, although other approaches, especially neuroscience, will be mentioned where appropriate. These sciences are philosophically significant because they are enmeshed in ancient philosophical questions about the nature of mind and purposeful action and about the differences between humans and other animals. These sciences are also clustered because of their attention to mechanistic explanations of individual animal behavior as opposed to attempting to capture regularities at a population level, such as the game-theoretic strategic models popular among behavioral ecologists.

Daniel Dennett and Stephen Stich have independently, but similarly, argued that the contents of mental states cannot be specified precisely enough for the purposes of scientific prediction and explanation. Dennett takes this to support his view that the proper role for mentalistic terms in science is heuristic. Stich takes it to support his view that cognitive science should be done without reference to mental content at all. I defend a realist understanding of mental content against these attacks by Dennett and Stich. I argue that they both mistake the difficulty of making content ascriptions precise for the impossibility of doing so.