Machine Mentality, Misc

Latest Sermon from the Church of Fundamentalist Naturalism by Pastor Hofstadter. Like his much more famous (or infamous for its relentless philosophical errors) work Godel, Escher, Bach, it has a superficial plausibility but if one understands that this is rampant scientism which mixes real scientific issues with philosophical ones (i.e., the only real issues are what language games we ought to play) then almost all its interest disappears. I provide a framework for analysis based in evolutionary psychology and the work (...) of Wittgenstein (since updated in my more recent writings). -/- Those wishing a comprehensive up to date framework for human behavior from the modern two systems view may consult my book ‘The Logical Structure of Philosophy, Psychology, Mind and Language in Ludwig Wittgenstein and John Searle’ 2nd ed (2019). Those interested in more of my writings may see ‘Talking Monkeys--Philosophy, Psychology, Science, Religion and Politics on a Doomed Planet--Articles and Reviews 2006-2019 3rd ed (2019), The Logical Structure of Human Behavior (2019), and Suicidal Utopian Delusions in the 21st Century 4th ed (2019). (shrink)

Just as humans can draw conclusions responsibly or irresponsibly, so too can computers. Machine learning systems that have been trained on data sets that include irresponsible judgments are likely to yield irresponsible predictions as outputs. In this paper I focus on a particular kind of inference a computer system might make: identification of the intentions with which a person acted on the basis of photographic evidence. Such inferences are liable to be morally objectionable, because of a way in which they (...) are presumptuous. After elaborating this moral concern, I explore the possibility that carefully procuring the training data for image recognition systems could ensure that the systems avoid the problem. The lesson of this paper extends beyond just the particular case of image recognition systems and the challenge of responsibly identifying a person’s intentions. Reflection on this particular case demonstrates the importance (as well as the difficulty) of evaluating machine learning systems and their training data from the standpoint of moral considerations that are not encompassed by ordinary assessments of predictive accuracy. (shrink)

We study whether robots can satisfy the conditions for agents fit to be held responsible in a normative sense, with a focus on autonomy and self-control. An analogy between robots and human groups enables us to modify arguments concerning collective responsibility for studying questions of robot responsibility. On the basis of Alfred R. Mele’s history-sensitive account of autonomy and responsibility it can be argued that even if robots were to have all the capacities usually required of moral agency, their history (...) as products of engineering would undermine their autonomy and thus responsibility. (shrink)

While the recent special issue of JCS on machine consciousness (Volume 14, Issue 7) was in preparation, a collection of papers on the same topic, entitled Artificial Consciousness and edited by Antonio Chella and Riccardo Manzotti, was published. 1 The editors of the JCS special issue, Ron Chrisley, Robert Clowes and Steve Torrance, thought it would be a timely and productive move to have authors of papers in their collection review the papers in the Chella and Manzotti book, and include (...) these reviews in the special issue of the journal. Eight of the JCS authors (plus Uziel Awret) volunteered to review one or more of the fifteen papers in Artificial Consciousness; these individual reviews were then collected together with a minimal amount of editing to produce a seamless chapter-by-chapter review of the entire book. Because the number and length of contributions to the JCS issue was greater than expected, the collective review of Artificial Con- sciousness had to be omitted, but here at last it is. Each paper’s review is written by a single author, so any comments made may not reflect the opinions of all nine of the joint authors! (shrink)

The view that phenomenally conscious robots are on the horizon often rests on a certain philosophical view about consciousness, one we call “nomological behaviorism.” The view entails that, as a matter of nomological necessity, if a robot had exactly the same patterns of dispositions to peripheral behavior as a phenomenally conscious being, then the robot would be phenomenally conscious; indeed it would have all and only the states of phenomenal consciousness that the phenomenally conscious being in question has. We experimentally (...) investigate whether the folk think that certain (hypothetical) robots made of silicon and steel would have the same conscious states as certain familiar biological beings with the same patterns of dispositions to peripheral behavior as the robots. Our findings provide evidence that the folk largely reject the view that silicon-based robots would have the sensations that they, the folk, attribute to the biological beings in question. (shrink)

I detta dokument ger jag mina teorier, idéer och förklaringar till hur jag tror att medvetandet fungerar, vad det är och varför vi har det. Enligt mig är alla levande varelser bara biologiska maskiner, skulpterade av evolutionen för att bli så anpassad som möjligt till den miljö som de befinner sig i. Allt fungerar på ett speciellt sätt, det går att förklaras och förstås, det finns ingen magi, och medvetandet är inget undantag, det finns där av en anledning.

Subjectivité artificielle: -/- •pléonasme, s'il est exact que la subjectivité humaine ne peut être qu'artificielle, cf infra subjiciel© -/- •terme proposé par l'auteur de l'A.L.S.© (Jean-Jacques Pinto) pour faire pendant à celui d'Intelligence artificielle -/- Subjiciel© : terme forgé (et déposé comme marque à l'I.N.P.I. en 1984) par l'auteur de l'A.L.S. : Jacques Pinto) : -/- 1. programmesubjectif "naturel", mais il se pourrait bien que la subjectivité humaine ne puisse être qu'artificielle : il n'y a pas de "nature humaine", seulement (...) une "condition humaine". Les subjiciels sont au service de l'identification subjective comme les cogniciels sont au service de l'identification cognitive -/- 2. logiciel de subjectivité artificielle écrit par des humains pour simuler la subjectivité humaine "naturelle", et en particulier les subjilectes ou lectes subjectifs. À ce propos, signalons que dès 1983, inspiré par le titre du livre de William Skyvington, "Machina sapiens. Essai sur l'intelligence artificielle". Seuil, 1976, nous avons proposé l'expression Machina subjectiva pour désigner l'ensemble des projets tendant à construire cette subjectivité artificielle. (shrink)

Much has been written about the possibility of human trust in robots. In this article we consider a more specific relationship: that of a human follower’s obedience to a social robot who leads through the exercise of referent power and what Weber described as ‘charismatic authority.’ By studying robotic design efforts and literary depictions of robots, we suggest that human beings are striving to create charismatic robot leaders that will either (1) inspire us through their display of superior morality; (2) (...) enthrall us through their possession of superhuman knowledge; or (3) seduce us with their romantic allure. Rejecting a contractarian-individualist approach which presumes that human beings will be able to consciously ‘choose’ particular robot leaders, we build on the phenomenological-social approach to trust in robots to argue that charismatic robot leaders will emerge naturally from our world’s social fabric, without any rational decision on our part. Finally, we argue that the stability of these leader-follower relations will hinge on a fundamental, unresolved question of robotic intelligence: is it possible for synthetic intelligences to exist that are morally, intellectually, and emotionally sophisticated enough to exercise charismatic authority over human beings—but not so sophisticated that they lose the desire to do so? (shrink)

Computers can mimic human intelligence, sometimes quite impressively. This has led some to claim that, a.) computers can actually acquire intelligence, and/or, b.) the human mind may be thought of as a very sophisticated computer. In this paper I argue that neither of these inferences are sound. The human mind and computers, I argue, operate on radically different principles.

With their “bottom-up” approach, Holk Cruse and Malte Schilling present a highly intriguing perspective on those mental phenomena that have fascinated humankind since ancient times. Among them are those aspects of our inner lives that are at the same time most salient and yet most elusive: we are conscious beings with complex emotions, thinking and acting in pursuit of various goals. Starting with, from a biological point of view, very basic abilities, such as the ability to move and navigate in (...) an unpredictable environment, Cruse & Schilling have developed, step-by-step, a robotic system with the ability to plan future actions and, to a limited extent, to verbally report on its own internal states. The authors then offer a compelling argument that their system exhibits aspects of various higher-level mental phenomena such as emotion, attention, intention, volition, and even consciousness. The scientific investigation of the mind is faced with intricate problems at a very fundamental, methodological level. Not only is there a good deal of conceptual vagueness and uncertainty as to what the explananda precisely are, but it is also unclear what the best strategy might be for addressing the phenomena of interest. Cruse & Schilling’s bio-robotic “bottom-up” approach is designed to provide answers to such questions. In this commentary, I begin, in the first section, by presenting the main ideas behind this approach as I understand them. In the second section, I turn to an examination of its scope and limits. Specifically, I will suggest a set of constraints on good explanations based on the bottom-up approach. What criteria do such explanations have to meet in order to be of real scientific value? I maintain that there are essentially three such criteria: biological plausibility, adequate matching criteria, and transparency. Finally, in the third section, I offer directions for future research, as Cruse & Schilling’s bottom-up approach is well suited to provide new insights in the domain of social cognition and to explain its relation to phenomena such as language, emotion, and self. (shrink)

I critically examine some provocative arguments that John Searle presents in his book The Rediscovery of Mind to support the claim that the syntactic states of a classical computational system are "observer relative" or "mind dependent" or otherwise less than fully and objectively real. I begin by explaining how this claim differs from Searle's earlier and more well-known claim that the physical states of a machine, including the syntactic states, are insufficient to determine its semantics. In contrast, his more recent (...) claim concerns the syntax, in particular, whether a machine actually has symbols to underlie its semantics. I then present and respond to a number of arguments that Searle offers to support this claim, including whether machine symbols are observer relative because the assignment of syntax is arbitrary, or linked to universal realizability, or linked to the sub-personal interpretive acts of a homunculus, or linked to a person's consciousness. I conclude that a realist about the computational model need not be troubled by such arguments. Their key premises need further support. (shrink)

Ask most any cognitive scientist working today if a digital computational system could develop aesthetic sensibility and you will likely receive the optimistic reply that this remains an open empirical question. However, I attempt to show, while drawing upon the later Wittgenstein, that the correct answer is in fact available. And it is a negative a priori. It would seem, for example, that recent computational successes in textual attribution, most notably those of Donald Foster (famed finder of Ted Kazinski a.k.a. (...) “the Unibomber”) speak favorably of the digital model's capacity to overcome the “aspect blindness” handicap in this domain. I argue however that such results are only achievable when rigid input‐to‐output parameters are given, and that this element is precisely what is absent in standard examples of aesthetic judgment. I thus conclude that while the connectionist model anticipated by Turing may provide the best approach for the AI project, its capacity for meeting its own sufficiency requirements is necessarily crippled by its inability to share in what can be generally referred to as the collective engagements of human solidarity. (shrink)

Functionalism of robot pain claims that what is definitive of robot pain is functional role, defined as the causal relations pain has to noxious stimuli, behavior and other subjective states. Here, I propose that the only way to theorize role-functionalism of robot pain is in terms of type-identity theory. I argue that what makes a state pain for a neuro-robot at a time is the functional role it has in the robot at the time, and this state is type identical (...) to a specific circuit state. Support from an experimental study shows that if the neural network that controls a robot includes a specific 'emotion circuit', physical damage to the robot will cause the disposition to avoid movement, thereby enhancing fitness, compared to robots without the circuit. Thus, pain for a robot at a time is type identical to a specific circuit state. (shrink)

In 1949, the Department of Philosophy at the University of Manchester organized a symposium “Mind and Machine” with Michael Polanyi, the mathematicians Alan Turing and Max Newman, the neurologists Geoff rey Jeff erson and J. Z. Young, and others as participants. Th is event is known among Turing scholars, because it laid the seed for Turing’s famous paper on “Computing Machinery and Intelligence”, but it is scarcely documented. Here, the transcript of this event, together with Polanyi’s original statement and his (...) notes taken at a lecture by Jeff erson, are edited and commented for the fi rst time. Th e originals are in the Regenstein Library of the University of Chicago. Th e introduction highlights elements of the debate that included neurophysiology, mathematics, the mind-body-machine problem, and consciousness and shows that Turing’s approach, as documented here, does not lend itself to reductionism. (shrink)

In this reply to James H. Fetzer’s “Minds and Machines: Limits to Simulations of Thought and Action”, I argue that computationalism should not be the view that (human) cognition is computation, but that it should be the view that cognition (simpliciter) is computable. It follows that computationalism can be true even if (human) cognition is not the result of computations in the brain. I also argue that, if semiotic systems are systems that interpret signs, then both humans and computers are (...) semiotic systems. Finally, I suggest that minds can be considered as virtual machines implemented in certain semiotic systems, primarily the brain, but also AI computers. In doing so, I take issue with Fetzer’s arguments to the contrary. (shrink)

Detractors of Searle’s Chinese Room Argument have arrived at a virtual consensus that the mental properties of the Man performing the computations stipulated by the argument are irrelevant to whether computational cognitive science is true. This paper challenges this virtual consensus to argue for the first of the two main theses of the persons reply, namely, that the mental properties of the Man are what matter. It does this by challenging many of the arguments and conceptions put forth by the (...) systems and logical replies to the Chinese Room, either reducing them to absurdity or showing how they lead, on the contrary, to conclusions the persons reply endorses. The paper bases its position on the Chinese Room Argument on additional philosophical considerations, the foundations of the theory of computation, and theoretical and experimental psychology. The paper purports to show how all these dimensions tend to support the proposed thesis of the persons reply. (shrink)

This paper is a follow-up of the first part of the persons reply to the Chinese Room Argument. The first part claims that the mental properties of the person appearing in that argument are what matter to whether computational cognitive science is true. This paper tries to discern what those mental properties are by applying a series of hypothetical psychological and strengthened Turing tests to the person, and argues that the results support the thesis that the Man performing the computations (...) characteristic of understanding Chinese actually understands Chinese. The supposition that the Man does not understand Chinese has gone virtually unquestioned in this foundational debate. The persons reply acknowledges the intuitive power behind that supposition, but knows that brute intuitions are not epistemically sacrosanct. Like many intuitions humans have had, and later deposed, this intuition does not withstand experimental scrutiny. The second part of the persons reply consequently holds that computational cognitive science is confirmed by the Chinese Room thought experiment. (shrink)

We explicate representational content by addressing how representations that ex- plain intelligent behavior might be acquired through processes of Darwinian evo- lution. We present the results of computer simulations of evolved neural network controllers and discuss the similarity of the simulations to real-world examples of neural network control of animal behavior. We argue that focusing on the simplest cases of evolved intelligent behavior, in both simulated and real organisms, reveals that evolved representations must carry information about the creature’s environ- ments (...) and further can do so only if their neural states are appropriately isomor- phic to environmental states. Further, these informational and isomorphism rela- tions are what are tracked by content attributions in folk-psychological and cognitive scientific explanations of these intelligent behaviors. (shrink)

It is possible to survey humankind and be proud, even to smile, for we accomplish great things. Art and science are two notable worthy human accomplishments. Consonant with art and science are some of the ways we treat each other. Sacrifice and heroism are two admirable human qualities that pervade human interaction. But, as everyone knows, all this goodness is more than balanced by human depravity. Moral corruption infests our being. Why?

In mid-May of 2001, I attended a fascinating workshop at Cold Spring Harbor Labs. The conference was held at the lab's Banbury Center, an elegant mansion and its beautiful surrounding estate, located on Banbury Lane, in the outskirts of Lloyd Harbor, overlooking the north shore of Long Island in New York. The estate was formerly owned by Charles Sammis Robertson. In 1976, Robertson donated his estate, and an endowment for its upkeep, to the Lab. The donation included the Robertson's mansion, (...) now called Robertson House, and a large, seven-car garage that would become the actual conference center. The Center was opened on Sunday, June 14, 1977, by Francis Crick who gave a talk entitled "How Scientists Work." For us, Banbury was an idyllic location with great food where we could talk about the most difficult problem in all o f science: what is the nature and cause of consciousness? (shrink)

Good sciences have good metaphors. Indeed, good sciences are good because they have good metaphors. AI could use more good metaphors. In this editorial, I would like to propose a new metaphor to help us understand intelligence. Of course, whether the metaphor is any good or not depends on whether it actually does help us. (What I am going to propose is not something opposed to computationalism -- the hypothesis that cognition is computation. Noncomputational metaphors are in vogue these days, (...) and to date they have all been equally plausible and equally successful. And, just to be explicit, I do not mean “IQ” by “intelligence.” I am using “intelligence” in the way AI uses it: as a semi-techical term referring to a general property of all intelligent systems, animal (including humans), or machine, alike.). (shrink)

Under the Superstition Mountains in central Arizona toil those who would rob humankind o f its humanity. These gray, soulless monsters methodically tear away at our meaning, our subjectivity, our essence as transcendent beings. With each advance, they steal our freedom and dignity. Who are these denizens of darkness, these usurpers of all that is good and holy? None other than humanity’s arch-foe: The Cognitive Scientists -- AI researchers, fallen philosophers, psychologists, and other benighted lovers of computers. Unless they are (...) stopped, humanity -- you and I -- will soon be nothing but numbers and algorithms locked away on magnetic tape. (shrink)

Over three decades ago, in a brief but provocative essay, Paul Ziff argued for the thesis that robots cannot have feelings because they are "mechanisms, not organisms, not living creatures. There could be a broken-down robot but not a dead one. Only living creatures can literally have feelings."[i] Since machines are not living things they cannot have feelings.

This report consists of three papers: “Why Isn’t My Pocket Calculator a Thinking Thing?”, by Larry Hauser; “Because Mere Calculating Isn’t Thinking” (comments on Hauser’s paper), by William J. Rapaport; and “The Sense of ‘Thinking’,” Hauser’s reply. They were originally presented at the Colloquium on Philosophy of Mind at the American Philosophical Association Central Division meeting in Chicago, 27 April 1991. Hauser argues that his pocket calculator (Cal) has certain arithmetical abilities: it seems Cal calculates. That calculating is thinking seems (...) equally untendentious. Yet these two claims together provide premises for a seemingly valid syllogism whose conclusion—Cal thinks—most would deny. He considers several ways to avoid this conclusion, and finds them mostly wanting. Either we ourselves can’t be said to think or calculate if our calculation-like performances are judged by the standards proposed to rule out Cal; or the standards—e.g., autonomy and self-consciousness—make it impossible to verify whether anything or anyone (save oneself) meets them. While appeals to the intentionality of thought or the unity of minds provide more credible lines of resistance, available accounts of intentionality and mental unity are insufficiently clear and warranted to provide very substantial arguments against Cal’s title to be called a thinking thing. Indeed, considerations favoring granting that title are more formidable than generally appreciated. Rapaport’s comments suggest that on a strong view of thinking, mere calculating is not thinking (and pocket calculators don’t think), but on a weak, but unexciting, sense of thinking, pocket calculators do think. He closes with some observations on the implications of this conclusion. (shrink)