Michael Anderson

At the turn of the 21st century, Susan Leigh Anderson and Michael Anderson conceived and introduced the Machine Ethics research program, that aimed to highlight the requirements under which autonomous artificial intelligence systems could demonstrate ethical behavior guided by moral values, and at the same time to show that these values, as well as ethics in general, can be representable and computable. Today, the interaction between humans and AI entities is already part of our everyday lives; in the near future it is expected to play a key role in scientific research, medical practice, public administration, education and other fields of civic life. In view of this, the debate over the ethical behavior of machines is more crucial than ever and the search for answers, directions and regulations is imperative at an academic, institutional as well as at a technical level. Our discussion with the two inspirers and originators of Machine Ethics highlights the epistemological, metaphysical and ethical questions arising by this project, as well as the realistic and pragmatic demands that dominate artificial intelligence and robotics research programs. Most of all, however, it sheds light upon the contribution of Susan and Michael Anderson regarding the introduction and undertaking of a main objective related to the creation of ethical autonomous agents, that will not be based on the “imperfect” patterns of human behavior, or on preloaded hierarchical laws and human-centric values.

Many commentators on Clark’s writings on predictive processing have wondered how well the predictive processing model actually fits with embodied and extended cognition. The former seems to imply that cognition is secluded from the environment, while the latter implies that cognition is in and of the environment. This chapter argues that a reconciliation with embodied and extended cognition is possible but requires that predictive processing proponents reject environmental seclusion. To do so means adopting ecological information in place of the Shannon information most typically invoked by proponents of predictive processing, and giving many of the other semantic-sounding terms they use (e.g., “prediction,” “model,” “representation”) deflationary understandings.

To accept that cognition is embodied is to question many of the beliefs traditionally held by cognitive scientists. One key question regards the localization of cognitive faculties. Here we argue that for cognition to be embodied and sometimes embedded, means that the cognitive faculty cannot be localized in a brain area alone. We review recent research on neural reuse, the 1/f structure of human activity, tool use, group cognition, and social coordination dynamics that we believe demonstrates how the boundary between the different areas of the brain, the brain and body, and the body and environment is not only blurred but indeterminate. In turn, we propose that cognition is supported by a nested structure of task-specific synergies, which are softly assembled from a variety of neural, bodily, and environmental components (including other individuals), and exhibit interaction dominant dynamics.

In this essay we respond to some criticisms of the guidance theory of representation offered by Tom Roberts. We argue that although Roberts’ criticisms miss their mark, he raises the important issue of the relationship between affordances and the action-oriented representations proposed by the guidance theory. Affordances play a prominent role in the anti-representationalist accounts offered by theorists of embodied cognition and ecological psychology, and the guidance theory is motivated in part by a desire to respond to the critiques of representationalism offered in such accounts, without giving up entirely on the idea that representations are an important part of the cognitive economy of many animals. Thus, explorations of whether and how such accounts can in fact be related and reconciled potentially offer to shed some light on this ongoing controversy. Although the current essay hardly settles the larger debate, it does suggest that there may be more possibility for agreement than is often supposed.

“The physics of representation” aims to define the word “representation” as used in the neurosciences, argue that such representations as described in neuroscience are related to and usefully illuminated by the representations generated by modern neural networks, and establish that these entities are “representations in good standing”. We suggest that Poldrack succeeds in, exposes some tensions between the broad use of the term in neuroscience and the narrower class of entities that he identifies in the end, and between the meaning of “representation” in neuroscience and in psychology in, and fails in. This results in some hard choices: give up on the broad scope of the term in neuroscience or continue to embrace the broad, psychologically inflected sense of the term, and deny the entities generated by neural nets are representations in the relevant sense.

Cognitive scientists and neuroscientists typically understand the brain as a complex communication/information-processing system. A limitation of this framework is that it requires cognitive systems to have prior knowledge about their environment to successfully perform some of their basic functions, such as perceiving. It is unclear how the source of such knowledge can be explained from within this framework. Drawing on Dennett (1981), we refer to this as the loans of intelligence problem. Recent advances in machine learning have resulted in the development of a family of algorithms, including the class known as autoencoders, that seem to provide a way for the information-processing framework to avoid this problem: cognitive systems do not require loans of intelligence, but instead acquire the knowledge necessary for perception through a process of unsupervised learning. This paper argues that although autoencoders do avoid the loans of intelligence problem, how they do so should not be understood from within the information-processing framework. Instead, their success should be interpreted as a proof of concept of how neural networks can attune to Gibsonian information. We thus propose that autoencoders belong to a class of algorithms for modeling the brain that have recently been dubbed direct fit algorithms.

Within the ecological and enactive approaches in cognitive science, a tension exists in how the process of skill learning is understood. Skill learning can be understood in a narrow sense, as a process of bodily change over time, or in an extended sense, as a change in the structure of the animal–environment system. We propose to resolve this tension by rejecting the first understanding in favor of the second. We thus defend an extended approach to skill learning. An extended understanding of skill learning views bodily changes as being embedded in a larger process of interaction between the organism and specific structures in the environment. Such an extended approach is committed to the claims that (1) the appropriate unit of analysis for understanding skill learning is not the body but the activity and (2) learning consists in the establishment and adaptive organization of enabling constraints on that activity. We focus on two example cases: maintaining upright posture and walking. In both cases, environmental structures play a constitutive role in the activity throughout learning, but the specific environmental structures that are involved in the activity change over time. At an early stage, the child makes use of an environmental “support”—for example, holding onto furniture to maintain upright posture. Later, once further constraints have been established, the child is able to let go of the furniture and remain upright. We argue that adopting an extended understanding of skill learning offers a promising strategy for unifying ecological and enactive approaches and can also potentially ground a radically embodied approach to higher cognition.

This essay introduces the massive redeployment hypothesis, an account of the functional organization of the brain that centrally features the fact that brain areas are typically employed to support numerous functions. The central contribution of the essay is to outline a middle course between strict localization on the one hand, and holism on the other, in such a way as to account for the supporting data on both sides of the argument. The massive redeployment hypothesis is supported by case studies of redeployment, and compared and contrasted with other theories of the localization of function.

Recent trends in the philosophy of mind and cognitive science can be fruitfully characterized as part of the ongoing attempt to come to grips with the very idea of homo sapiens--an intelligent, evolved, biological agent--and its signature contribution is the emergence of a philosophical anthropology which, contra Descartes and his thinking thing, instead puts doing at the center of human being. Applying this agency-oriented line of thinking to the problem of representation, this paper introduces the Guidance Theory, according to which the content and intentionality of representations can be accounted for in terms of the way they provide guidance for action. We offer a brief account of the motivation for the theory, and a formal characterization

In this paper, I summarize an emerging debate in the cognitive sciences over the right taxonomy for understanding cognition – the right theory of and vocabulary for describing the structure of the mind – and the proper role of neuroscientific evidence in specifying this taxonomy. In part because the discussion clearly entails a deep reconsideration of the supposed autonomy of psychology from neuroscience, this is a debate in which philosophers should be interested, with which they should be familiar, and to which they should contribute. Here, I outline some of the positions being advocated, and reflect on some of the possible implications of this work both for scientific and folk psychology.

Cognition is embodied when it is deeply dependent upon features of the physical body of an agent, that is, when aspects of the agent's body beyond the brain play a significant causal or physically constitutive role in cognitive processing. In general, dominant views in the philosophy of mind and cognitive science have considered the body as peripheral to understanding the nature of mind and cognition. Proponents of embodied cognitive science view this as a serious mistake. Sometimes the nature of the dependence of cognition on the body is quite unexpected, and suggests new ways of conceptualizing and exploring the mechanics of cognitive processing. Embodied cognitive science encompasses a loose-knit family of research programs in the cognitive sciences that often share a commitment to critiquing and even replacing traditional approaches to cognition and cognitive processing. Empirical research on embodied cognition has exploded in the past 10 years. As the bibliography for this article attests, the various bodies of work that will be discussed represent a serious alternative to the investigation of cognitive phenomena. Relatively recent work on the embodiment of cognition provides much food for thought for empirically-informed philosophers of mind. This is in part because of the rich range of phenomena that embodied cognitive science has studied. But it is also in part because those phenomena are often thought to challenge dominant views of the mind, such as the computational and representational theories of mind, at the heart of traditional cognitive science. And they have sometimes been taken to undermine standard positions in the philosophy of mind, such as the idea that the mind is identical to, or even realized in, the brain.

One of the most foundational and continually contested questions in the cognitive sciences is the degree to which the functional organization of the brain can be understood as modular. In its classic formulation, a module was defined as a cognitive sub-system with nine specific properties; the classic module is, among other things, domain specific, encapsulated, and implemented in dedicated neural substrates. Most of the examinations—and especially the criticisms—of the modularity thesis have focused on these properties individually, for instance by finding counterexamples in which otherwise good candidates for cognitive modules are shown to lack domain specificity or encapsulation. The current paper goes beyond the usual approach by asking what some of the broad architectural implications of the modularity thesis might be, and attempting to test for these. The evidence does not favor a modular architecture for the cortex. Moreover, the evidence suggests that best way to approach the understanding of cognition is not by analyzing and modelling different functional domains in isolation from the others, but rather by looking for points of overlap in their neural implementations, and exploiting these to guide the analysis and decomposition of the functions in question. This has significant implications for the question of how to approach the design and implementation of intelligent artifacts in general, and language-using robots in particular.

In: B. Hardy-Vallee & N. Payette, eds. Beyond the brain: embodied, situated & distributed cognition. (Cambridge: Cambridge Scholar’s Press), in press. Abstract: In this article, I do three main things: 1. First, I introduce an approach to the mind motivated primarily by evolutionary considerations. I do that by laying out four principles for the study of the mind from an evolutionary perspective, and four predictions that they suggest. This evolutionary perspective is completely compatible with, although broader than, the embodied cognition approach. 2. Then I look at one prediction in depth, the idea that the brain evolved by exaptation–reusing exiting functional units, and combining them in novel ways to generate new cognitive capacities. 3. Finally, I try to lay out some of the implications, both of the in-depth example, and of the more general approach.

The current essay introduces the guidance theory of representation, according to which the content and intentionality of representations can be accounted for in terms of the way they provide guidance for action. The guidance theory offers a way of fixing representational content that gives the causal and evolutionary history of the subject only an indirect role, and an account of representational error, based on failure of action, that does not rely on any such notions as proper functions, ideal conditions, or normal circumstances. Moreover, because the notion of error is defined in terms of failure of action, the guidance theory meets the “meta-epistemological requirement” that representational error should be potentially detectable by the representing system itself. In this essay, we offer a brief account of the biological origins of representation, a formal characterization of the guidance theory, some examples of its use, and show how the guidance theory handles some traditional problem cases for representation: the representation of fictional and abstract entities. Being both representational and actiongrounded, the guidance theory may provide some common ground between embodied and cognitivist approaches to the study of the mind

As part of the ongoing attempt to fully naturalize the concept of human being--and, more specifically, to re-center it around the notion of agency--this essay discusses an approach to defining the content of representations in terms ultimately derived from their central, evolved function of providing guidance for action. This 'guidance theory' of representation is discussed in the context of, and evaluated with respect to, two other biologically inspired theories of representation: Dan Lloyd's dialectical theory of representation and Ruth Millikan's biosemantics.