PurposeThe purpose of this paper is to explore the possibility and desirability of artificial intelligence by considering western literature on AI and Buddhist doctrine.Design/methodology/approachThe paper argues that these issues can best be considered examined from a variety of philosophical and religious viewpoints and that resolution of those issues depends on which point of view the questions are addressed from. There are a number of philosophical questions involving AI usually considered by philosophers: what is the definition of AI, what is a (...) status of an AI as compared with human intelligence, is there a legitimate purpose for creating AI; if so, what is that purpose? Buddhism is a religion that is deeply philosophical and, perhaps to the surprise of western readers, has a lot to say about the nature of human mind and human intelligence. Although Buddhism does not talk explicitly about AI, the richness of its philosophical views concerning human nature and the nature of the physical world sheds considerable light on the philosophical questions stated above.FindingsThe paper explains how Buddhist teaching would answer the four questions above.Originality/valueThe paper is the first to clarify the Buddhist position on AI, and perhaps represents the first attempt to explore the relationships between any major religion and the AI agenda. (shrink)

This paper develops an empirically motivated theory of visual consciousness. It begins by outlining neuropsychological support for Jackendoff's (1987) hypothesis that visual consciousness involves mental representations at an intermediate level of processing. It then supplements that hypothesis with the further requirement that attention, which can come under the direction of high level representations, is also necessary for consciousness. The resulting theory is shown to have a number of philosophical consequences. If correct, higher-order thought accounts, the multiple drafts account, and the (...) widely held belief that sensation precedes perception will all be found wanting. The theory will also be used to illustrate and defend a methodology that fills the gulf between functionalists who ignore the brain and neural reductionists who repudiate functionalism. (shrink)

John Searle claims that consciousness is ontologically subjective, since conscious mental phenomena only exist as long as they are experienced. Therefore, mental phenomena are essentially conscious, insofar as their mental character depends on their connection with consciousness. However, to align the acceptance of unconscious mental phenomena with his Cartesian view of consciousness, Searle defends adispositional account of the unconscious. The problem is that some cases of unconscious mental causation require that certain decisive mental properties exist in an occurrent way, and (...) not merely as dispositions. By accepting unconscious mental causation, Searle commits himself to a mental existence that isindependent from consciousness. Such unconscious existence implies that certain mental phenomena are ontologically objective, and not subjective as he claims, because they exist without being experienced.Keywords: Ontological subjectivity, unconscious, disposition, mental causation, objectivity. (shrink)

When experimental philosophers carry out studies on thought experiments, some participants are excluded based on certain exclusion criteria, mirroring standard social science vignette methodology. This involves excluding people that do not pay attention or who miscomprehend the scenario presented in thought experiments. However, experimental philosophy studies sometimes exclude an alarmingly high number of participants. We argue that this threatens the external and internal validity of the conclusions being drawn and we show how a simple visualization of thought experiments can reduce (...) exclusion rates significantly. Furthermore, we argue that focus should not merely be on how many are excluded, but also why they are excluded, and we highlight the role of comprehension questions in this regard. Philosophical thought experiments often rely on the acceptance of certain key premises that may be regarded contestable, and asking comprehension questions involving such key assumptions could be problematic as that may result in some participants being inadvertently excluded from the study, potentially creating a selection bias. (shrink)

Can computer systems ever be considered moral agents? This paper considers two factors that are explored in the recent philosophical literature. First, there are the important domains in which computers are allowed to act, made possible by their greater functional capacities. Second, there is the claim that these functional capacities appear to embody relevant human abilities, such as autonomy and responsibility. I argue that neither the first (Domain-Function) factor nor the second (Simulacrum) factor gets at the central issue in the (...) case for computer moral agency: whether they can have the kinds of intentional states that cause their decisions and actions. I give an account that builds on traditional action theory and allows us to conceive of computers as genuine moral agents in virtue of their own causally efficacious intentional states. These states can cause harm or benefit to moral patients, but do not depend on computer consciousness or intelligence. (shrink)

To summarize, in order for rational agents to be able to engage in the sophisticated kinds of reasoning exemplified by human beings, they must be able to introspect much of their cognition. The problem of other minds and the problem of knowing the mental states of others will arise automatically for any rational agent that is able to introspect its own cognition. The most that a rational agent can reasonably believe about other rational agents is that they have rational architectures (...) similar to its own, and that they have thoughts related to their rational architectures in certain ways. This leads to Rational Functionalism as an account of what it is to be a cognizer having mental states. That in turn entails that a computer can be a person in precisely the same sense as my next door neighbor if it can appropriately mimic my rational architecture. There is nothing I could know about my neighbor that I could not believe with equal justification about the computer. Rational Functionalism also makes it reasonable to define the narrow content of a thought to be its overall place in the agent's rational architecture, that is, its conceptual role. This is, however, avery narrow notion of content. For practical purposes, we are not interested in knowing the narrow contents of other people's thoughts. We are only interested in rather general properties of those narrow contents. This is what is expressed by the use ofthat-clauses in public language. (shrink)

The truly philosophical issue in machine conscioiusness is whether machines can have 'hard consciounsess'. Criteria for hard consciousness are higher than for phenomenal consciousness, since the latter incorporates first-person functional consciousness.

Roughly speaking, computationalism says that cognition is computation, or that cognitive phenomena are explained by the agent‘s computations. The cognitive processes and behavior of agents are the explanandum. The computations performed by the agents‘ cognitive systems are the proposed explanans. Since the cognitive systems of biological organisms are their nervous 1 systems (plus or minus a bit), we may say that according to computationalism, the cognitive processes and behavior of organisms are explained by neural computations. Some people might prefer to (...) say that cognitive systems are ―realized‖ by nervous systems, and thus that—according to computationalism—cognitive computations are ―realized‖ by neural processes. In this paper, nothing hinges on the nature of the relation between cognitive systems and nervous systems, or between computations and neural processes. For present purposes, if a neural process realizes a computation, then that neural process is a computation. Thus, I will couch much of my discussion in terms of nervous systems and neural computation.1 Before proceeding, we should dispense with a possible red herring. Contrary to a common assumption, computationalism does not stand in opposition to connectionism. Connectionism, in the most general and common sense of the term, is the claim that cognitive phenomena are explained (at some level and at least in part) by the processes of neural networks. This is a truism, supported by most neuroscientific evidence. Everybody ought to be a connectionist in this general sense. The relevant question is, are neural processes computations? More precisely, are the neural processes to be found in the nervous systems of organisms computations? Computationalists say ―yes‖, anti-computationalists say ―no‖. This paper investigates whether any of the arguments on offer against computationalism have a chance at knocking it off.2 Ever since Warren McCulloch and Walter Pitts (1943) first proposed it, computationalism has been subjected to a wide range of objections.. (shrink)

Defending or attacking either functionalism or computationalism requires clarity on what they amount to and what evidence counts for or against them. My goal here is not to evaluate their plausibility. My goal is to formulate them and their relationship clearly enough that we can determine which type of evidence is relevant to them. I aim to dispel some sources of confusion that surround functionalism and computationalism, recruit recent philosophical work on mechanisms and computation to shed light on them, and (...) clarify how functionalism and computationalism may or may not legitimately come together. (shrink)

We begin by distinguishing computationalism from a number of other theses that are sometimes conflated with it. We also distinguish between several important kinds of computation: computation in a generic sense, digital computation, and analog computation. Then, we defend a weak version of computationalism—neural processes are computations in the generic sense. After that, we reject on empirical grounds the common assimilation of neural computation to either analog or digital computation, concluding that neural computation is sui generis. Analog computation requires continuous (...) signals; digital computation requires strings of digits. But current neuroscientific evidence indicates that typical neural signals, such as spike trains, are graded like continuous signals but are constituted by discrete functional elements (spikes); thus, typical neural signals are neither continuous signals nor strings of digits. It follows that neural computation is sui generis. Finally, we highlight three important consequences of a proper understanding of neural computation for the theory of cognition. First, understanding neural computation requires a specially designed mathematical theory (or theories) rather than the mathematical theories of analog or digital computation. Second, several popular views about neural computation turn out to be incorrect. Third, computational theories of cognition that rely on non-neural notions of computation ought to be replaced or reinterpreted in terms of neural computation. (shrink)

Some philosophers have conflated functionalism and computationalism. I reconstruct how this came about and uncover two assumptions that made the conflation possible. They are the assumptions that (i) psychological functional analyses are computational descriptions and (ii) everything may be described as performing computations. I argue that, if we want to improve our understanding of both the metaphysics of mental states and the functional relations between them, we should reject these assumptions.

Some philosophers have conflated functionalism and computationalism. I reconstruct how this came about and uncover two assumptions that made the conflation possible. They are the assumptions that (i) psychological functional analyses are computational descriptions and (ii) everything may be described as performing computations. I argue that, if we want to improve our understanding of both the metaphysics of mental states and the functional relations between them, we should reject these assumptions. # 2004 Elsevier Ltd. All rights reserved.

The received view is that computational states are individuated at least in part by their semantic properties. I offer an alternative, according to which computational states are individuated by their functional properties. Functional properties are specified by a mechanistic explanation without appealing to any semantic properties. The primary purpose of this paper is to formulate the alternative view of computational individuation, point out that it supports a robust notion of computational explanation, and defend it on the grounds of how computational (...) states are individuated within computability theory and computer science. A secondary purpose is to show that existing arguments for the semantic view are defective. (shrink)

Computationalism has been the mainstream view of cognition for decades. There are periodic reports of its demise, but they are greatly exaggerated. This essay surveys some recent literature on computationalism. It concludes that computationalism is a family of theories about the mechanisms of cognition. The main relevant evidence for testing it comes from neuroscience, though psychology and AI are relevant too. Computationalism comes in many versions, which continue to guide competing research programs in philosophy of mind as well as psychology (...) and neuroscience. Although our understanding of computationalism has deepened in recent years, much work in this area remains to be done. (shrink)

This paper offers an account of what it is for a physical system to be a computing mechanism—a system that performs computations. A computing mechanism is a mechanism whose function is to generate output strings from input strings and (possibly) internal states, in accordance with a general rule that applies to all relevant strings and depends on the input strings and (possibly) internal states for its application. This account is motivated by reasons endogenous to the philosophy of computing, namely, doing (...) justice to the practices of computer scientists and computability theorists. It is also an application of recent literature on mechanisms, because it assimilates computational explanation to mechanistic explanation. The account can be used to individuate computing mechanisms and the functions they compute and to taxonomize computing mechanisms based on their computing power. (shrink)

According to pancomputationalism, everything is a computing system. In this paper, I distinguish between different varieties of pancomputationalism. I find that although some varieties are more plausible than others, only the strongest variety is relevant to the philosophy of mind, but only the most trivial varieties are true. As a side effect of this exercise, I offer a clarified distinction between computational modelling and computational explanation.<br><br>.

Each of our theories of mental representation provides some insight into how the mind works. However, these insights often seem incompatible, as the debates between symbolic, dynamical, emergentist, sub-symbolic, and grounded approaches to cognition attest. Mental representations—whatever they are—must share many features with each of our theories of representation, and yet there are few hypotheses about how a synthesis could be possible. Here, I develop a theory of the underpinnings of symbolic cognition that shows how sub-symbolic dynamics may give rise (...) to higher-level cognitive representations of structures, systems of knowledge, and algorithmic processes. This theory implements a version of conceptual role semantics by positing an internal universal representation language in which learners may create mental models to capture dynamics they observe in the world. The theory formalizes one account of how truly novel conceptual content may arise, allowing us to explain how even elementary logical and computational operations may be learned from a more primitive basis. I provide an implementation that learns to represent a variety of structures, including logic, number, kinship trees, regular languages, context-free languages, domains of theories like magnetism, dominance hierarchies, list structures, quantification, and computational primitives like repetition, reversal, and recursion. This account is based on simple discrete dynamical processes that could be implemented in a variety of different physical or biological systems. In particular, I describe how the required dynamics can be directly implemented in a connectionist framework. The resulting theory provides an “assembly language” for cognition, where high-level theories of symbolic computation can be implemented in simple dynamics that themselves could be encoded in biologically plausible systems. (shrink)

We argue that the causal account offered by analytic functionalism provides the best account of the folk psychological theory of mind, and that people ordinarily define mental states relative to the causal roles these states occupy in relation to environmental impingements, external behaviors, and other mental states. We present new empirical evidence, as well as review several key studies on mental state ascription to diverse types of entities such as robots, cyborgs, corporations and God, and explain how this evidence supports (...) a functional account. We also respond to two challenges to this view based on the embodiment hypothesis, or the claim that physical realizers matter over and above functional role, and qualia. In both cases we conclude that research to date best supports a functional account of ordinary mental state concepts. (shrink)

I argue that the physiological, phenomenal and conceptual constitute a trichotomous hierarchy of emergent categories. I claim that each category employs a distinctive type of interactive mechanism that facilitates a meaningful kind of environmental discourse. I advocate, therefore, that each have a causal relation with the environment but that their specific class of mechanism qualifies distinctively the meaningfulness of that interaction and subsequent responses. Consequently, I argue that the causal chain of physical interaction feeds distinctive value-laden constructions that are ontologically (...) distinct for each category. Within the limitations of the interactive mechanisms of each category, increasingly sophisticated forms tend to evolve. The increase in sophistication in each category inevitably leads to the emergence of the novel mechanism particular to the next in the hierarchy. In essence, there is an emergent hierarchy of evolving categories delineated by the nature of their mechanism of environmental engagement. I argue that biochemical mechanisms have a tendency to evolve meaningfully, specifically in a way that is both qualitatively relevant and responsive to environmental particulars. I explain that these mechanisms set in play an organisational imperative that leads to the emergence of the capacity to evaluate and prioritise qualitative biochemical assimilations which, inevitably, generates a subjectively individuated experience phenomenon. I then relate this to the novel characteristics of the human perspective. (shrink)

The term ‘information’ is used extensively in biology, cognitive science and the philosophy of consciousness in relation to the concepts of ‘meaning’ and ‘causation’. While ‘information’ is a term that serves a useful purpose in specific disciplines, there is much to the concept that is problematic. Part 1 is a critique of the stance that information is an independently existing entity. On this view, and in biological contexts, systems transmit, acquire, assimilate, decode and manipulate it, and in so doing, generate (...) meaning. I provide a detailed proposal in Part 2 that supports the claim that it is the dynamic form of a system that qualifies the informational nature of meaningful interactive engagement, that is, that information is dependent on dynamic form rather than that it exists independently. In Part 3, I reflect on the importance of the distinction between the independent and dependent stances by looking specifically at the implications for how we might better interpret causation and emergence. (shrink)

Our everyday life is increasingly permeated with digital objects that carry out smart and complex functions. The latest (but certainly not final) advancement of smart digital applications – is to be identified the creation of a field, at once conceptual and material, of things denominated smart objects (henceforth SOs). This technological evolution is so pervasive that it is referred to as smartification. Smart objects have some distinctive features including in particular varying degrees of agency, autonomy and authority. There is no (...) doubt that the SO category is extremely broad, various and intrinsically fuzzy, it is evident that the phenomenon is by no means easy to define: which objects are really smart and which are not? But above all: what do we mean in semio-linguistic, and not psychological nor merely phenomenological terms, when we attribute the qualifier smart to an artifact? What is clear is that a new, or at least different (and controversial) relationship is developing between objects and subjects, or rather between human beings and objects inhabiting the spaces of social action: that is, a new system of objects, to cite Baudrillard (1968), or a new “society of objects” (see Landowski and Marrone 2002). In this paper we will focus on a type of smart physical device designed to interact with its users in the domestic sphere, assisting them in a variety of tasks – such as for example Amazon Echo, capable of connecting to Alexa, an intelligent personal assistant based on machine learning, or the more recent Google Assistant. Our semiotic-oriented – or, more precisely, potentially socio-semiotic/ethno-semiotic – analysis will deal with these issues theoretically by concentrating on the problem of identity, which is anthropologically, but also and above all philosophically, sensitive. We shall look at the impact of technological devices on the perceptive/cognitive systems of human beings, starting with a reflection on the practices of interaction, signification and interpretation that also involve digital objects with a possible impact on everyday life. (shrink)

Starting in the 1950s, computer programs for simulating cognitive processes and intelligent behaviour were the hallmark of Good Old-Fashioned Artificial Intelligence and ‘cognitivist’ cognitive science. This article examines a somewhat neglected case of simulation pursued by one of the founding fathers of simulation methodology, Herbert A. Simon. In the 1970s and 1980s, Simon had repeated contacts with Marxist countries and scientists, in the context of which he advanced the idea that cognitivism could be used as a framework for simulating dialectical (...) materialism. Simon's idea was, in particular, to represent dialectical processes through a ‘symbolic’ version of dialectical logic. This article explores the context of Simon's interaction with Marxist countries—China and the USSR—and also assesses the outcome of the simulation. The difficulty with simulating distinctive features of dialectical materialism is read in light of the underlying assumptions of cognitivism and, ultimately, in light of the attempt to tame a rival world view. (shrink)

This paper considers the impact of the AI R&D programme on human society and the individual human being on the assumption that a full realisation of the engineering objective of AI, namely, construction of human-level, domain-independent intelligent entities, is possible. Our assumption is essentially identical tothe maximum progress scenario of the Office of Technology Assessment, US Congress.Specifically, the first section introduces some of the significant issues on the relational nexus among work, education and the human-machine boundary. In particular, based on (...) a Russellian conception of rationality I briefly argue that we need to change our related conceptions of work, employment and free time, through a new human-centred education. On the human-machine boundary problem, I make a couple of tentative suggestions and put forward some crucial open questions.Section two discusses the impact of the emerging machine intelligence on human nature both as modification of its self-image, keeping human nature itself unchanged, and its potential for altering human nature itself. I briefly argue that: (i) in a certain context, the question of the supremacy or uniqueness of human intelligence loses much, if not all, of its ‘weight’; and (ii) appearance of Robot-X species would immortalise the human spirit. (shrink)

The “Slicing Problem” is a thought experiment that raises questions for substrate-neutral computational theories of consciousness, including those that specify a certain causal structure for the computation like Integrated Information Theory. The thought experiment uses water-based logic gates to construct a computer in a way that permits cleanly slicing each gate and connection in half, creating two identical computers each instantiating the same computation. The slicing can be reversed and repeated via an on/off switch, without changing the amount of matter (...) in the system. The question is what do different computational theories of consciousness believe is happening to the number and nature of individual conscious units as this switch is toggled. Under a token interpretation, there are now two discrete conscious entities; under a type interpretation, there may remain only one. Both interpretations lead to different implications depending on the adopted theoretical stance. Any route taken either allows mechanisms for “consciousness-multiplying exploits” or requires ambiguous boundaries between conscious entities, raising philosophical and ethical questions for theorists to consider. We discuss resolutions under different theories of consciousness for those unwilling to accept consciousness-multiplying exploits. In particular, we specify three features that may help promising physicalist theories to navigate such thought experiments. (shrink)