Apply rich psychological terms in AI with care

There is much to be gained from interdisciplinary efforts to tackle complex psychological notions such as ‘theory of mind’ by combining the rich history of study and debates in cognitive science and recent findings from AI research. However, careful and consistent communication is essential when comparing artificial and biological intelligence, say Henry Shevlin and Marta Halina.Leverhulme Trust, Templeton World Charity Foundatio

Current controversies in the cognitive science of short-term memory

Short-term memory is critically implicated in most human cognitive capacities and has been the object of study for more than a century, yet many questions remain unsettled and new controversies have emerged. This paper provides an overview of some current debates within the field. These include (i) the issue of how many short-term memory systems there are, (ii) whether working memory is best understood as having domain-specific resources, (iii) how information is encoded in working memory, (iv) how sensory memory and working memory are related to attention, and (v) the relationship between short-term memory and consciousness.This work was supported by the Leverhulme Centre for the Future of Intelligence, Leverhulme Trust, under Grant RC-2015-067

Rethinking creative intelligence: comparative psychology and the concept of creativity

AbstractThe concept of creativity is a central one in folk psychological explanation and has long been prominent in philosophical debates about the nature of art, genius, and the imagination. The scientific investigation of creativity in humans is also well established, and there has been increasing interest in the question of whether the concept can be rigorously applied to non-human animals. In this paper, I argue that such applications face serious challenges of both a conceptual and methodological character, reflecting deep controversies within both philosophy and psychology concerning how to define and apply the concept of creativity. After providing a brief review of some of the leading theories of creativity (Section 2) and discussing some of the strongest putative cases of creative intelligence in non-human animals (Section 3), I examine some of the more worrisome difficulties faced by attempts to use these theories to answer the question of whether animals are truly creative (Section 4). I conclude by examining how we might overcome them, and suggest that one approach worth taking seriously is to adopt what I term a Strong Rejectionist view of creativity, eschewing use of the term entirely in the scientific study of comparative cognition.</jats:p

Consciousness, Perception, and Short-Term Memory

Dissertation Abstract: Consciousness, Perception, and Short-Term Memory When we engage in almost any perceptual activity – recognizing a face, listening out for a phone-call, or simply taking in a sunset – information must be briefly stored and processed in some form of short-term memory. For philosophers attempting to develop an empirically grounded account of perception and conscious experience, it is therefore crucial to engage with scientific theories of the kinds of short-term memory mechanisms that underlie our moment-to-moment retention of information about the world. To that end, in this dissertation I review recent scientific evidence for a new form of rapid but transitory memory, dubbed Conceptual Short-Term Memory (CSTM), and show how it may constitute an important missing piece in philosophical debates about the mind. I begin in the first chapter by providing some background on past psychological work on short-term memory and the influence this work has had on the philosophy of mind. In the second chapter, I present the evidence for CSTM, and argue that it has a number of important features that make it of philosophical interest. In particular, I note that it seems to sit at the border of strictly perceptual processes and higher-level cognition, encoding incoming information quickly, effortlessly, but fleetingly in terms of basic-level concepts like ‘dog’, ‘car’, or ‘painting’. In the following chapters, I examine in more detail how CSTM might be usefully applied to three specific debates. First, I argue that CSTM may allow us to give a powerful account of categorical perception or ‘perceiving-as’, explaining how our perceptual experience comes to be infused with awareness of the categorical identities of the things we perceive. I argue that this account could shed light on questions about how cognition can affect perceptual experience. Second, I offer a new account of consciousness that I term the Workspace-Plus account, claiming that a short-term conceptual buffer such as CSTM may serve as the constitutive basis for perceptual experience independent of higher-level cognitive mechanisms. Finally, developing this suggestion, I turn to broader questions about the evolutionary function of consciousness and its place in nature. I suggest that if we identify perceptual experience with the process of perceptual categorization mediated by a conceptual buffer like CSTM, we can offer an independently appealing account of the psychological role of consciousness, and begin to make informed inferences about the presence of subjective experience in animals. I close by examining how this account can be applied to a crucial debate at the intersection of ethics and the philosophy of mind, namely the question of how we identify experiences of suffering in animals

Consciousness, Machines, and Moral Status

In light of recent breakneck pace in machine learning, questions about whether near-future artificial systems might be conscious and possess moral status are increasingly pressing. This paper argues that as matters stand these debates lack any clear criteria for resolution via the science of consciousness. Instead, insofar as they are settled at all, it is likely to be via shifts in public attitudes brought about by the increasingly close relationships between humans and AI users. Section 1 of the paper I briefly lays out the current state of the science of consciousness and its limitations insofar as these pertain to machine consciousness, and claims that there are no obvious consensus frameworks to inform public opinion on AI consciousness. Section 2 examines the rise of conversational chatbots or Social AI, and argues that in many cases, these elicit strong and sincere attributions of consciousness, mentality, and moral status from users, a trend likely to become more widespread. Section 3 presents an inconsistent triad for theories that attempt to link consciousness, behaviour, and moral status, noting that the trends in Social AI systems will likely make the inconsistency of these three premises more pressing. Finally, Section 4 presents some limited suggestions for how consciousness and AI research communities should respond to the gap between expert opinion and folk judgment

All too human? Identifying and mitigating ethical risks of Social AI

This paper presents an overview of the risks and benefits of Social AI, understood as conversational AI systems that cater to human social needs like romance, companionship, or entertainment. Section 1 of the paper provides a brief history of conversational AI systems and introduces conceptual distinctions to help distinguish varieties of Social AI and pathways to their deployment. Section 2 of the paper adds further context via a brief discussion of anthropomorphism and its relevance to assessment of human-chatbot relationships. Section 3 of the paper provides a survey of potential and in some cases demonstrated harms associated with user interactions with Social AI systems. Finally, Section 4 discusses how the benefits and harms of Social AI can best be addressed, with a primary focus on how frameworks from AI ethics can inform their development

Deep Learning Applied to Scientific Discovery: A Hot Interface with Philosophy of Science

We scrutinize publications in automated scientific discovery using deep learning, with the aim of shedding light on problems with strong connections to philosophy of science, of physics in particular. We show that core issues of philosophy of science, related, notably, to the nature of scientific theories; the nature of unification; and of causation loom large in scientific deep learning. Therefore advances in deep learning could, and ideally should, have impact on philosophy of science, and vice versa. We suggest lines of further research, and highlight the role ‘theory-driven’ AI could have in future developments of the field

Special Issue "On Defining Artificial Intelligence"—Commentaries and Author's Response

n/