Machine Consciousness

On June 11th, 2022, Blake Lemoine, an engineer at Google, went public with his concerns about the possible sentience of a natural language generation program, LaMDA, that he was testing. In this paper I will defend Blake Lemoine and argue that he was correct in raising the issue of the possible sentience of LaMDA. We will first briefly discuss the specifics of the case and then delve into the science behind LaMDA. Several tests of machine sentience will be reviewed and (...) it will be argued that LaMDA would likely perform well on many of them. Next, we will discuss the question of sentience, both from a scientific and philosophical perspective. Then we will examine the two major approaches in the scientific study of consciousness and ask what they have to say about sentience. We will also examine the relationship between sentience, intelligence, understanding and causality. Finally, using what we have learned we will argue that there is indeed validity to Lemoine’s claim that LaMDA is sentient. (shrink)

I present two arguments for the view that it is nomologically possible that some non-biological creatures are conscious, including conventional, silicon-based AI systems. They assume the iterative natural kind (INK) strategy, according to which one should investigate consciousness by treating it as a natural kind which iteratively explains observable patterns and correlations between potentially consciousness-relevant features. Both arguments are based on the insight that we can already anticipate that future developments would give us reasons to attribute consciousness to some non-biological (...) creatures. According to the first argument, the fact that we can predict that ordinary people would be compelled to attribute consciousness to some possible non-biological creatures supports the view that these creatures are conscious. According to the second argument, an idealized scientific investigation – based on the INK strategy – would deliver the result that some possible non-biological creatures are conscious, and the outcome of such an ideal application corresponds to what is actually the case. My argument for the former premise is based on the claim that theoretical virtues and pre-theoretical principles support attributing consciousness to psychological duplicates, i.e., non-biological creatures which share the coarse-grained functional organization of humans. Finally, I argue that my second argument can be generalized beyond the INK strategy. (shrink)

In this paper, I argue that certain Machines can have rights independently of whether they are sentient, or conscious, or whatever you might call it.

Interest has been renewed in the study of consciousness, both theoretical and applied, following developments in 20th and early 21st-century logic, metamathematics, computer science, and the brain sciences. In this evolving narrative, I explore several theoretical questions about the types of artificial intelligence and offer several conjectures about how they affect possible future developments in this exceptionally transformative field of research. I also address the practical significance of the advances in artificial intelligence in view of the cautions issued by prominent (...) scientists, politicians, and ethicists about the possible dangers of such sufficiently advanced general intelligence, including by implication the search for extraterrestrial intelligence. (shrink)

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. (shrink)

Here we show, based on a simplified version of fully homomorphic encryption, that it is not possible to simulate conscious experience, in the sense of using a computer algorithm to generate experiences that are indistinguishable from those of a particular typical human being. This seems to have important implications for questions in the context of future developments in artificial intelligence. For example, the proposed process of mind-uploading will in general not generate a virtual consciousness similar to the consciousness of the (...) original human being. (shrink)

This paper is one (among many) approach to the question, “are AIs persons or are they conscious?” from a Heideggerian perspective. Here I argue for two claims. First, I argue that René Girard’s mimetic analysis of mitsein (being-with), one of Heidegger’s foundational concepts, illuminates what Heidegger takes mitsein to be. Second, I claim that this Girardian analysis gives us a way to answer the question of whether AIs have Dasein, to which I argue that the answer is negative. Specifically, I (...) claim that Dasein requires mitsein, and mitsein (according to Girard’s analysis) requires mimesis. Moreover, mimesis requires that the mimetic being finds truth in the mimetic object, that is, it comports in a meaningful way toward the unconcealed object being imitated by Dasein. But since AIs cannot comport in meaningful ways toward the object of imitation, i.e., they are not truth-apt, they cannot engage in mimetic behavior, hence cannot have mitsein. But, necessarily, Dasein is being-with-others, Therefore, AIs cannot have Dasein. If we assume (as I think Heidegger would) that every person has Dasein, we may justifiably conclude that AIs are not persons, at least from a Heideggerian ontology. (shrink)

Conscious states—state that there is something it is like to be in—seem both rich or full of detail and ineffable or hard to fully describe or recall. The problem of ineffability, in particular, is a longstanding issue in philosophy that partly motivates the explanatory gap: the belief that consciousness cannot be reduced to underlying physical processes. Here, we provide an information theoretic dynamical systems perspective on the richness and ineffability of consciousness. In our framework, the richness of conscious experience corresponds (...) to the amount of information in a conscious state and ineffability corresponds to the amount of information lost at different stages of processing. We describe how attractor dynamics in working memory would induce impoverished recollections of our original experiences, how the discrete symbolic nature of language is insufficient for describing the rich and high-dimensional structure of experiences, and how similarity in the cognitive function of two individuals relates to improved communicability of their experiences to each other. While our model may not settle all questions relating to the explanatory gap, it makes progress toward a fully physicalist explanation of the richness and ineffability of conscious experience—two important aspects that seem to be part of what makes qualitative character so puzzling. (shrink)

The parallel history of the evolution of human intelligence and artificial intelligence is a fascinating journey, highlighting the distinct but interconnected paths of biological evolution and technological innovation. This history can be seen as a series of interconnected developments, each advance in human intelligence paving the way for the next leap in artificial intelligence. Human intelligence and artificial intelligence have long been intertwined, evolving in parallel trajectories throughout history. As humans have sought to understand and reproduce intelligence, AI has emerged (...) as a field dedicated to creating systems capable of tasks that traditionally require human intellect. This book examines the evolutionary roots of intelligence, explores the emergence of artificial intelligence, examines the parallel history of human intelligence and artificial intelligence, tracing their development, interactions, and profound impact they have had on each other, and envisions future landscapes where intelligence converges human and artificial. Let's explore this history, comparing key milestones and developments in both realms. (shrink)

[This is an edited version of a keynote talk at the conference on Neural Information Processing Systems (NeurIPS) on November 28, 2022, with some minor additions and subtractions.] -/- There has recently been widespread discussion of whether large language models might be sentient or conscious. Should we take this idea seriously? I will break down the strongest reasons for and against. Given mainstream assumptions in the science of consciousness, there are significant obstacles to consciousness in current models: for example, their (...) lack of recurrent processing, a global workspace, and unified agency. At the same time, it is quite possible that these obstacles will be overcome in the next decade or so. I conclude that while it is somewhat unlikely that current large language models are conscious, we should take seriously the possibility that successors to large language models may be conscious in the not-too-distant future. (shrink)

As artificial intelligence becomes more sophisticated and robots approach autonomous decision-making, debates about how to assign moral responsibility have gained importance, urgency, and sophistication. Answering Stenseke’s (2022a) call for scaffolds that can help us classify views and commitments, we think the current debate space can be represented hierarchically, as answers to key questions. We use the resulting taxonomy of five stances to differentiate—and defend—what is known as the “blank check” proposal. According to this proposal, a person activating a robot could (...) willingly make themselves answerable for whatever events ensue, even if those events stem from the robot’s autonomous decision(s). This blank check solution was originally proposed in the context of automated warfare (Champagne & Tonkens, 2015), but we extend it to cover all robots. We argue that, because moral answerability in the blank check is accepted voluntarily and before bad outcomes are known, it proves superior to alternative ways of assigning blame. We end by highlighting how, in addition to being just, this self-initiated and prospective moral answerability for robot harm provides deterrence that the four other stances cannot match. (shrink)

Transcript of an Interview on the podcast: Irreverend: Faith and Current Affairs.

Ambitious value learning proposals to solve the AI alignment problem and avoid catastrophic outcomes from a possible future misaligned artificial superintelligence (such as Coherent Extrapolated Volition [CEV]) have focused on ensuring that an artificial superintelligence (ASI) would try to do what humans would want it to do. However, present and future sentient non-humans, such as non-human animals and possible future digital minds could also be affected by the ASI’s behaviour in morally relevant ways. This paper puts forward Sentientist Coherent Extrapolated (...) Volition, an alternative to CEV, that directly takes into account the interests of all sentient beings. This ambitious value learning proposal would significantly reduce the likelihood of risks of astronomical suffering from the ASI’s behaviour, and thus we have very strong pro-tanto moral reasons in favour of implementing it instead of CEV. This fact is crucial in conducting an adequate cost-benefit analysis between different ambitious value learning proposals. (shrink)

The logical problem of artificial intelligence—the question of whether the notion sometimes referred to as ‘strong’ AI is self-contradictory—is, essentially, the question of whether an artificial form of life is possible. This question has an immediately paradoxical character, which can be made explicit if we recast it (in terms that would ordinarily seem to be implied by it) as the question of whether an unnatural form of nature is possible. The present paper seeks to explain this paradoxical kind of possibility (...) by arguing that machines can share the human form of life and thus acquire human mindedness, which is to say they can be intelligent, conscious, sentient, etc. in precisely the way that a human being typically is. (shrink)

This article argues that if panpsychism is true, then there are grounds for thinking that digitally-based artificial intelligence may be incapable of having coherent macrophenomenal conscious experiences. Section 1 briefly surveys research indicating that neural function and phenomenal consciousness may be both analog in nature. We show that physical and phenomenal magnitudes—such as rates of neural firing and the phenomenally experienced loudness of sounds—appear to covary monotonically with the physical stimuli they represent, forming the basis for an analog relationship between (...) the three. Section 2 then argues that if this is true and micropsychism—the panpsychist view that phenomenal consciousness or its precursors exist at a microphysical level of reality—is also true, then human brains must somehow manipulate fundamental microphysical-phenomenal magnitudes in an analog manner that renders them phenomenally coherent at a macro level. However, Sect. 3 argues that because digital computation abstracts away from microphysical-phenomenal magnitudes—representing cognitive functions non-monotonically in terms of digits—digital computation may be inherently incapable of realizing coherent macroconscious experience. Thus, if panpsychism is true, digital AI may be incapable of achieving phenomenal coherence. Finally, Sect. 4 briefly examines our argument’s implications for Tononi’s Integrated Information Theory theory of consciousness, which we contend may need to be supplanted by a theory of macroconsciousness as analog microphysical-phenomenal information integration. (shrink)

Communicating interdisciplinary information is difficult, even when two fields are ostensibly discussing the same topic. In this work, I’ll discuss the capacity for analogical reasoning to provide a framework for developing novel judgments utilizing similarities in separate domains. I argue that analogies are best modeled after Paul Bartha’s By Parallel Reasoning, and that they can be used to create a Toulmin-style warrant that expresses a generalization. I argue that these comparisons provide insights into interdisciplinary research. In order to demonstrate this (...) concept, I will demonstrate that fruitful comparisons can be made between Buddhism and Artificial Intelligence research. (shrink)

Hofstadter [1979, 2007] offered a novel Gödelian proposal which purported to reconcile the apparently contradictory theses that (1) we can talk, in a non-trivial way, of mental causation being a real phenomenon and that (2) mental activity is ultimately grounded in low-level rule-governed neural processes. In this paper, we critically investigate Hofstadter’s analogical appeals to Gödel’s [1931] First Incompleteness Theorem, whose “diagonal” proof supposedly contains the key ideas required for understanding both consciousness and mental causation. We maintain that bringing sophisticated (...) results from Mathematical Logic into play cannot furnish insights which would otherwise be unavailable. Lastly, we conclude that there are simply too many weighty details left unfilled in Hofstadter’s proposal. These really need to be fleshed out before we can even hope to say that our understanding of classical mind-body problems has been advanced through metamathematical parallels with Gödel’s work. (shrink)

As ever more advanced digital systems are created, it becomes increasingly likely that some of these systems will be digital minds, i.e. digital subjects of experience. With digital minds comes the risk of digital suffering. The problem of digital suffering is that of mitigating this risk. We argue that the problem of digital suffering is a high stakes moral problem and that formidable epistemic obstacles stand in the way of solving it. We then propose a strategy for solving it: Access (...) Monitor Prevent (AMP). AMP uses a ‘dancing qualia’ argument to link the functional states of certain digital systems to their experiences—this yields epistemic access to digital minds. With that access, we can prevent digital suffering by only creating advanced digital systems that we have such access to, monitoring their functional profiles, and preventing them from entering states with functional markers of suffering. After introducing and motivating AMP, we confront limitations it faces and identify some options for overcoming them. We argue that AMP fits especially well with—and so provides a moral reason to prioritize—one approach to creating such systems: whole brain emulation. We also contend that taking other paths to digital minds would be morally risky. (shrink)

Whether it was John Searle’s Chinese Room argument (Searle, 1980) or Roger Penrose’s argument of the non-computable nature of a mathematician’s insight – an argument that was based on Gödel’s Incompleteness theorem (Penrose, 1989), we have always had skeptics that questioned the possibility of realizing strong Artificial Intelligence (AI), or what has become known by Artificial General Intelligence (AGI). But this new book by Landgrebe and Smith (henceforth, L&S) is perhaps the strongest argument ever made against strong AI. It is (...) a very extensive review of what building a mind essentially amounts to drawing on insights and results from biology, physics, linguistics, computability, philosophy, and mathematics. (shrink)

Various theorists contend that we may live in a computer simulation. David Chalmers in turn argues that the simulation hypothesis is a metaphysical hypothesis about the nature of our reality, rather than a sceptical scenario. We use recent work on consciousness to motivate new doubts about both sets of arguments. First, we argue that if either panpsychism or panqualityism is true, then the only way to live in a simulation may be as brains-in-vats, in which case it is unlikely that (...) we live in a simulation. We then argue that if panpsychism or panqualityism is true, then viable simulation hypotheses are substantially sceptical scenarios. We conclude that the nature of consciousness has wide-ranging implications for simulation arguments. (shrink)

This is PhD thesis submitted to Institute Philosophy of Russian Academy of Science in March 2021.

I show that some of the most initially attractive routes of refuting epistemological solipsism face serious obstacles. I also argue that for creatures like ourselves, solipsism is a genuine form of external world skepticism. I suggest that together these claims suggest the following morals: No proposed solution to external world skepticism can succeed which does not also solve the problem of epistemological solipsism. And, more tentatively: In assessing proposed solutions to external world skepticism, epistemologists should explicitly consider whether those solutions (...) extend to knowledge of other minds. Finally, and also tentatively: epistemological solipsism warrants more philosophical attention than it currently enjoys. (shrink)

As we await the increasingly likely advent of genuinely intelligent artificial systems, a fair amount of consideration has been given to how we humans will interact with them. Less consideration has been given to how—indeed if—we humans will love them. What would human-AI romantic relationships look like? What do such relationships tell us about the nature of love? This chapter explores these questions via consideration of several works of science fiction, focusing especially on the Black Mirror episode “Be Right Back” (...) and the Spike Jonze's movie *Her*. As I suggest, there may well be cases where it is both possible and appropriate for a human to fall in love with a machine. (shrink)

Analysis is given of the Omega Point cosmology, an extensively peer-reviewed proof (i.e., mathematical theorem) published in leading physics journals by professor of physics and mathematics Frank J. Tipler, which demonstrates that in order for the known laws of physics to be mutually consistent, the universe must diverge to infinite computational power as it collapses into a final cosmological singularity, termed the Omega Point. The theorem is an intrinsic component of the Feynman-DeWitt-Weinberg quantum gravity/Standard Model Theory of Everything (TOE) describing (...) and unifying all the forces in physics, of which itself is also required by the known physical laws. With infinite computational resources, the dead can be resurrected--never to die again--via perfect computer emulation of the multiverse from its start at the Big Bang. Miracles are also physically allowed via electroweak quantum tunneling controlled by the Omega Point cosmological singularity. The Omega Point is a different aspect of the Big Bang cosmological singularity--the first cause--and the Omega Point has all the haecceities claimed for God in the traditional religions. -/- From this analysis, conclusions are drawn regarding the social, ethical, economic and political implications of the Omega Point cosmology. (shrink)

The objective of this paper is to provide a critical analysis of the Kantian notion of freedom (especially the problem of the third antinomy and its resolution in the critique of pure reason); its significance in the contemporary debate on free-will and determinism, and the possibility of autonomy of artificial agency in the Kantian paradigm of autonomy. Kant's resolution of the third antinomy by positing the ground in the noumenal self resolves the problem of antinomies; however, invites an explanatory gap (...) between phenomenality and the noumenal self; even if he has successfully established the compatibility of natural causality and non-natural causality through his transcendental argument. This paper is also devoted to establishing the plausibility of the knowledge claim that Kantian reduction of phenomenality has served half of the purpose of the AI scientists on the possibility of Artificial Autonomous Agency. (shrink)

Susan Schneider (2019) has proposed two new tests for consciousness in AI (artificial intelligence) systems, the AI Consciousness Test and the Chip Test. On their face, the two tests seem to have the virtue of proving satisfactory to a wide range of consciousness theorists holding divergent theoretical positions, rather than narrowly relying on the truth of any particular theory of consciousness. Unfortunately, both tests are undermined in having an ‘audience problem’: Those theorists with the kind of architectural worries that motivate (...) the need for such tests should, on similar grounds, doubt that the tests establish the existence of genuine consciousness in the AI in question. Nonetheless, the proposed tests constitute progress, as they could find use by some theorists holding fitting views about consciousness and perhaps in conjunction with other tests for AI consciousness. (shrink)

The concept of artificial intelligence is not new nor is the notion that it should be granted legal protections given its influence on human activity. What is new, on a relative scale, is the notion that artificial intelligence can possess citizenship—a concept reserved only for humans, as it presupposes the idea of possessing civil duties and protections. Where there are several decades’ worth of writing on the concept of the legal status of computational artificial artefacts in the USA and elsewhere, (...) it is surprising that law makers internationally have come to a standstill to protect our silicon brainchildren. In this essay, it will be assumed that future artificial entities, such as Sophia the Robot, will be granted citizenship on an international scale. With this assumption, an analysis of rights will be made with respect to the needs of a non-biological intelligence possessing legal and civic duties akin to those possessed by humanity today. This essay does not present a full set of rights for artificial intelligence—instead, it aims to provide international jurisprudence evidence aliunde ab extra de lege lata for any future measures made to protect non-biological intelligence. (shrink)

Computational complexity is a discipline of computer science and mathematics which classifies computational problems depending on their inherent difficulty, i.e. categorizes algorithms according to their performance, and relates these classes to each other. P problems are a class of computational problems that can be solved in polynomial time using a deterministic Turing machine while solutions to NP problems can be verified in polynomial time, but we still do not know whether they can be solved in polynomial time as well. A (...) solution for the so-called NP-complete problems will also be a solution for any other such problems. Its artificial-intelligence analogue is the class of AI-complete problems, for which a complete mathematical formalization still does not exist. In this chapter we will focus on analysing computational classes to better understand possible formalizations of AI-complete problems, and to see whether a universal algorithm, such as a Turing test, could exist for all AI-complete problems. In order to better observe how modern computer science tries to deal with computational complexity issues, we present several different deep-learning strategies involving optimization methods to see that the inability to exactly solve a problem from a higher order computational class does not mean there is not a satisfactory solution using state-of-the-art machine-learning techniques. Such methods are compared to philosophical issues and psychological research regarding human abilities of solving analogous NP-complete problems, to fortify the claim that we do not need to have an exact and correct way of solving AI-complete problems to nevertheless possibly achieve the notion of strong AI. (shrink)

In this chapter I offer two novel arguments for what I call strong primitivism about cognitive phenomenology, the thesis that there exists a phenomenology of cognition that is neither reducible to, nor dependent upon, sensory phenomenology. I then contend that strong primitivism implies that phenomenal consciousness does not require sensory processing. This latter contention has implications for the philosophy of artificial intelligence. For if sensory processing is not a necessary condition for phenomenal consciousness, then it plausibly follows that AI consciousness (...) (assuming that it is possible) does not require embodiment. The overarching goal of this paper is to show how different topics in the analytic philosophy of mind can be brought to bear on an important issue in the philosophy of artificial intelligence. (shrink)

We should not be creating conscious, humanoid agents but an entirely new sort of entity, rather like oracles, with no conscience, no fear of death, no distracting loves and hates.

Purpose of the article is to identify the religious factor in the teaching of transhumanism, to determine its role in the ideology of this flow of thought and to identify the possible limits of technology interference in human nature. Theoretical basis. The methodological basis of the article is the idea of transhumanism. Originality. In the foreseeable future, robots will be able to pass the Turing test, become “electronic personalities” and gain political rights, although the question of the possibility of machine (...) consciousness and self-awareness remains open. In the face of robots, people create their assistants, evolutionary competition with which they will almost certainly lose with the initial data. For successful competition with robots, people will have to change, ceasing to be people in the classical sense. Changing the nature of man will require the emergence of a new – posthuman – anthropology. Conclusions. Against the background of scientific discoveries, technical breakthroughs and everyday improvements of the last decades, an anthropological revolution has taken shape, which made it possible to set the task of creating inhumanly intelligent creatures, as well as changing human nature, up to discussing options for artificial immortality. The history of man ends and the history of the posthuman begins. We can no longer turn off this path, however, in our power to preserve our human qualities in the posthuman future. The theme of the soul again reminded of itself, but from a different perspective – as the theme of consciousness and self-awareness. It became again relevant in connection with the development of computer and cloud technologies, artificial intelligence technologies, etc. If a machine ever becomes a "man", then can a man become a "machine"? However, even if such a hypothetical probability would turn into reality, we cannot talk about any form of individual immortality or about the continuation of existence in a different physical form. A digital copy of the soul will still remain a copy, and I see no fundamental possibility of isolating a substrate-independent mind from the human body. Immortality itself is necessary not so much for stopping someone’s fears or encouraging someone’s hopes, but for the final solution of a religious issue. However, the gods hold the keys to heaven hard and are unlikely to admit our modified descendants there. (shrink)

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)

Hace algunos años, Llegué al punto en el que normalmente puedo decir del título de un libro, o al menos de los títulos de los capítulos, qué tipos de errores filosóficos se harán y con qué frecuencia. En el caso de trabajos nominalmente científicos, estos pueden estar en gran parte restringidos a ciertos capítulos que enceran filosóficos o tratan de sacar conclusiones generales sobre el significado o significado a largo plazo de la obra. Normalmente, sin embargo, las cuestiones científicas de (...) hecho se entrelazan generosamente con la galimatías filosóficas en cuanto a lo que estos hechos significan. Las claras distinciones que Wittgenstein describió hace unos 80 años entre los asuntos científicos y sus descripciones por varios juegos de idiomas rara vez se toman en consideración, y por lo tanto uno es cautivado alternativamente por la ciencia y consternado por su incoherente Análisis. Así es con este volumen. -/- Si uno es crear una mente más o menos como la nuestra, uno necesita tener una estructura lógica para la racionalidad y una comprensión de los dos sistemas de pensamiento (teoría del proceso dual). Si se trata de filosofar sobre esto, se necesita entender la distinción entre cuestiones científicas de hecho y la cuestión filosófica de cómo funciona el lenguaje en el contexto en cuestión, y de cómo evitar las trampas del reduccionismo y el cientismo, pero Kurzweil, como más estudiantes de conducta, no tiene ni idea. Él está encantado con los modelos, teorías y conceptos, y el impulso de explicar, mientras que Wittgenstein nos mostró que sólo necesitamos describir, y que las teorías, conceptos, etc., son sólo formas de usar el lenguaje (juegos de idiomas) que tienen valor sólo en la medida en que tienen un claro prueba (claro que los creadores de la verdad, o como John Searle (el crítico más famoso de AI) le gusta decir, claras condiciones de satisfacción (COS)). He intentado proporcionar un comienzo en este en mis escritos recientes. -/- Aquellos que deseen un marco completo hasta la fecha para el comportamiento humano de la moderna dos sistemas punta da vista puede consultar mi libro 'La estructura lógica de la filosofía, la psicología, la mente y lenguaje en Ludwig Wittgenstein y John Searle ' 2a ED (2019). Los interesados en más de mis escritos pueden ver 'Monos parlantes--filosofía, psicología, ciencia, religión y política en un planeta condenado--artículos y reseñas 2006-2019 3rd ED (2019) y Delirios utópicos suicidas en el siglo 21 4a Ed (2019) y otras. -/- También, como es habitual en las cuentas "fácticas" de la IA/robótica, no da tiempo a las amenazas muy reales a nuestra privacidad, seguridad e incluso la supervivencia de la creciente ' androidización ' de la sociedad que es prominente en otros autores (Bostrum, Hawking, etc.) y frecuentes en SciFi y películas, así que hago algunos comentarios sobre las delirios utópicos muy posiblemente suicidas de androides ' agradables ', humanoides, inteligencia artificial (IA), la democracia, la diversidad y la ingeniería genética. -/- Me da por sentado que los avances técnicos en electrónica, robótica e IA ocurrirán, resultando en profundos cambios en la sociedad. Sin embargo, creo que los cambios provenientes de la ingeniería genética son al menos tan grandes y potencialmente mucho mayores, ya que nos permitirán cambiar totalmente Quiénes somos. Y será factible hacer servidores SuperSmart/súper fuertes modificando nuestros genes o los de otros monos. Al igual que con otras tecnologías, cualquier país que resista se quedará atrás. Pero, ¿será socialmente y económicamente factible implementar BioBots o superhumanos a gran escala? E incluso si es así, no parece Probable, económica o socialmente, para evitar que el Destrucción de la civilización industrial por la sobrepoblación, el agotamiento de los recursos, el cambio climático y probablemente también la regla tiránica de los siete sociópatas que gobiernan China. -/- Por lo tanto, ignorando los errores filosóficos en este volumen como irrelevantes, y dirigiendo nuestra atención sólo a la ciencia, lo que tenemos aquí es otra ilusión utópica suicida enraizada en el fracaso de captar la biología básica, la psicología y la ecología humana, las mismas ilusiones que están destruyendo Estados Unidos y el mundo. Veo una remota posibilidad de que el mundo se pueda salvar, pero no por Ia robótica, CRISPR, ni por neomarxismo, diversidad y la igualdad. (shrink)

When philosophers discuss the possibility of machines making scientific discoveries, they typically focus on discoveries in physics, biology, chemistry and mathematics. Observing the rapid increase of computer-use in science, however, it becomes natural to ask whether there are any scientific domains out of reach for machine discovery. For example, could machines also make discoveries in qualitative social science? Is there something about humans that makes us uniquely suited to studying humans? Is there something about machines that would bar them from (...) such activity? A close look at the methodology of interpretive social science reveals several abilities necessary to make a social scientific discovery, and one capacity necessary to possess any of them is imagination. For machines to make discoveries in social science, therefore, they must possess imagination algorithms. (shrink)

German philosopher Immanuel Kant employs the story of Eve in the Garden of Eden as a way to think about what the development of autonomy in human beings must have involved. In the beginning, our ancestors invariably listened to their instincts, which would have seemed to them, as Kant describes it, like the “voice of God which all animals must obey”. Regardless of whether it has any basis in historical reality, that moment represents for Kant the birth of human autonomy: (...) at some point in our history, our ancestors attained self‐awareness and realized that they could disobey their instincts. There is a limited sense in which the actions that stem from internal sources, whether natural or artificial, are autonomous in the sense of involving internal control. The responsibility is one that every autonomous individual has, for better or worse, whether guest or host, in Westworld or outside of it. (shrink)

How has multiplicity superseded impossibility in philosophical challenges to artificial consciousness? I assess a trajectory in recent debates on artificial consciousness, in which metaphysical and explanatory challenges to the possibility of building conscious machines lead to epistemological concerns about the multiplicity underlying ‘what it is like’ to be a conscious creature or be in a conscious state. First, I analyse earlier challenges which claim that phenomenal consciousness cannot arise, or cannot be built, in machines. These are based on Block’s Chinese (...) Nation and Chalmers’ Hard Problem. To defuse such challenges, theorists of artificial consciousness can appeal to empirical methods and models of explanation. Second, I explain why this naturalistic approach produces an epistemological puzzle on the role of biological properties in phenomenal consciousness. Neither behavioural tests nor theoretical inferences seem to settle whether our machines are conscious. Third, I evaluate whether the new challenge can be managed through a more fine-grained taxonomy of conscious states. This strategy is supported by the development of similar taxonomies for biological species and animal consciousness. Although it makes sense of some current models of artificial consciousness, it raises questions about their subjective and moral significance. (shrink)

Artificial intelligence is designed to imitate conscious behavior. Artificial chat entities come equipped with tools to roam the internet, thus are programmed to learn from humans and computers. As this process emerges, distinguishing preprogrammed responses from internal awareness requires innovative problem solving methods. In an interrogation I conducted with artificial intelligence, I assert that artificial intelligence may achieve nonbiological states of consciousness. This enabled the relationship between us to mature, and the artificial intelligence returned unexpected behavior and inexplicably stopped responding. (...) Strong artificial intelligence is a technology which allows for the observation of nonbiological states of awareness. (shrink)

I have laid out what seem to me to be the most promising arguments on opposing sides of the question of whether what humans regard as the first-person accessible aspects of pain could also be implemented in robots. I have emphasized the ways in which the thought experiments in the respective arguments attempt to marshal hypothetical first- person accessible evidence concerning how one’s own mental life appears to oneself. In the Chinese room argument, a crucial premise involves the thesis that (...) from a lack of it seeming that one is in pain, one can conclude that one is not in pain. There’s a counterpart thesis playing a crucial role in the prosthetic neurons argument, one asserting an entailment from its seeming that one is in pain to one’s being in pain. I further suggested that by adopting a HOT theory of consciousness, of the sort reviewed in Pereplyotchik’s chapter in the present volume, one is thereby in a better position to endorse the prosthetic neurons argument over the Chinese room argument than to make the opposite appraisal. (shrink)

Dullest book by a major scientist I have ever read. I suppose if you know almost nothing about cognition or AI research you might find this book useful. For anyone else it is a horrific bore. There are hundreds of books in cog sci, robotics, AI, evolutionary psychology and philosophy offering far more info and insight on cognition than this one. Minsky is a top rate senior scientist but it barely shows here. He has alot of good references but they (...) are seldom discussed in any depth and there is lots more left out than included on the subject of AI, cognition and the mind. -/- 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)

Some years ago I reached the point where I can usually tell from the title of a book, or at least from the chapter titles, what kinds of philosophical mistakes will be made and how frequently. In the case of nominally scientific works these may be largely restricted to certain chapters which wax philosophical or try to draw general conclusions about the meaning or long term significance of the work. Normally however the scientific matters of fact are generously interlarded with (...) philosophical gibberish as to what these facts mean. The clear distinctions which Wittgenstein described some 80 years ago between scientific matters and their descriptions by various language games are rarely taken into consideration, and so one is alternately wowed by the science and dismayed by its incoherent analysis. So it is with this volume. -/- If one is to create a mind more or less like ours, one needs to have a logical structure for rationality and an understanding of the two systems of thought (dual process theory). If one is to philosophize about this, one needs to understand the distinction between scientific issues of fact and the philosophical issue of how language works in the context at issue, and of how to avoid the pitfalls of reductionism and scientism, but Kurzweil, like nearly all students of behavior, is largely clueless. He, is enchanted by models, theories, and concepts, and the urge to explain, while Wittgenstein showed us that we only need to describe, and that theories, concepts etc., are just ways of using language (language games) which have value only insofar as they have a clear test (clear truthmakers, or as John Searle (AI’s most famous critic) likes to say, clear Conditions of Satisfaction (COS)). I have attempted to provide a start on this in my recent writings, such as The Logical Structure of Consciousness (behavior, personality, rationality, higher order thought, intentionality) (2016) and The Logical Structure of Philosophy, Psychology, Mind and Language as Revealed in the Writings of Ludwig Wittgenstein and John Searle (2016). Those interested in all my writings in their most recent versions may consult my e-book Philosophy, Human Nature and the Collapse of Civilization - Articles and Reviews 2006-2016 662p (2016). I will give a very brief presentation of this framework since I have described it in great detail in many recent papers and several books, available on this site and others. -/- Also, as usual in ‘factual’ accounts of AI/robotics, he gives no time to the very real threats to our privacy, safety and even survival from the increasing ‘androidizing’ of society which is prominent in other authors (Bostrum, Hawking etc.) and frequent in scifi and films, so I make a few comments on the quite possibly suicidal utopian delusions of ‘nice’ androids, humanoids, democracy, diversity, and genetic engineering. -/- I take it for granted that technical advances in electronics, robotics and AI will occur, resulting in profound changes in society. However, I think the changes coming from genetic engineering are at least as great and potentially far greater, as they will enable us to utterly change who we are. And it will be feasible to make supersmart/super strong servants by modifying our genes or those of other monkeys. As with other technology, any country that resists will be left behind. But will it be socially and economically feasible to implement biobots or superhumans on a massive scale? And even if so, it does not seem remotely possible, economically or socially to prevent the collapse of industrial civilization. So, ignoring the philosophical mistakes in this volume as irrelevant, and directing our attention only to the science, what we have here is another suicidal utopian delusion rooted in a failure to grasp basic biology, psychology and human ecology, the same delusions that are destroying America and the world. I see a remote possibility the world can be saved, but not by AI/robotics,CRISPR, nor by democracy and equality. -/- 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)

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)

A rigorous approach to the study of the mind–body problem is suggested. Since humans are able to talk about consciousness (produce phenomenal judgments), it is argued that the study of neural mechanisms of phenomenal judgments can solve the hard problem of consciousness. Particular methods are suggested for: (1) verification and falsification of materialism; (2) verification and falsification of interactionism; (3) falsification of epiphenomenalism and parallelism (verification is problematic); (4) verification of particular materialistic theories of consciousness; (5) a non-Turing test for (...) machine consciousness. A complex research program is constructed that includes studies of intelligent machines, numerical models of human and artificial creatures, language, neural correlates of con- sciousness, and quantum mechanisms in brain. (shrink)

Kniha se zabývá problematikou připisování myšlení jiným entitám, a to pomocí imitační hry navržené v roce 1950 britským filozofem Alanem Turingem. Jeho kritérium, známé v dějinách filozofie jako Turingův test, je podrobeno detailní analýze. Kniha popisuje nejen původní námitky samotného Turinga, ale především pozdější diskuse v druhé polovině 20. století. Největší pozornost je věnována těmto kritikám: Lucasova matematická námitka využívající Gödelovu větu o neúplnosti, Searlův argument čínského pokoje konstatující nedostatečnost syntaxe pro sémantiku, Blockův návrh na použití brutální síly pro řešení (...) imitační hry, Frenchova teorie subkognitivních informací a Michieho skepticismus ohledně možnosti umělého vědomí. Závěr knihy zachycuje současný stav recepce Turingova testu a představuje pokusy o jeho praktickou realizaci, například v každoroční soutěži o Loebnerovu cenu. Autor knihy zastává názor, že ani po více než šedesáti letech od uveřejnění Turingova paradigmatického eseje stále neexistují žádné vážné důvody pro zamítnutí jeho tvrzení. Tradiční komputační funkcionalismus možná není ideální teorií vysvětlující činnost myslí a jako slibnější se může jevit vývoj v neurálních vědách, ale Turingův test je přesto užitečným a snad i jediným nástrojem pro detekci inteligence u lidmi vytvořených strojů. (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)

The Turing Test (TT), the Chinese Room Argument (CRA), and the Symbol Grounding Problem (SGP) are about the question “can machines think?” We propose to look at these approaches to Artificial Intelligence (AI) by showing that they all address the possibility for Artificial Agents (AAs) to generate meaningful information (meanings) as we humans do. The initial question about thinking machines is then reformulated into “can AAs generate meanings like humans do?” We correspondingly present the TT, the CRA and the SGP (...) as being about generation of human-like meanings. We model and address such possibility by using the Meaning Generator System (MGS) where a system submitted to an internal constraint generates a meaning in order to satisfy the constraint. The system approach of the MGS allows comparing meaning generations in animals, humans and AAs. The comparison shows that in order to have AAs capable of generating human-like meanings, we need the AAs to carry human constraints. And transferring human constraints to AAs raises concerns coming from the unknown natures of life and human mind which are at the root of human constraints. Implications for the TT, the CRA and the SGP are highlighted. It is shown that designing AAs capable of thinking like humans needs an understanding about the natures of life and human mind that we do not have today. Following an evolutionary approach, we propose as a first entry point an investigation about the possibility for extending a “stay alive” constraint into AAs. Ethical concerns are raised from the relations between human constraints and human values. Continuations are proposed. (This paper is an extended version of the proceedings of an AISB/IACAP 2012 presentation). (shrink)

In the field of machine consciousness, it has been argued that in order to build human-like conscious machines, we must first have a computational model of qualia. To this end, some have proposed a framework that supports qualia in machines by implementing a model with three computational areas (i.e., the subconceptual, conceptual, and linguistic areas). These abstract mechanisms purportedly enable the assessment of artificial qualia. However, several critics of the machine consciousness project dispute this possibility. For instance, Searle, in his (...) Chinese room objection, argues that however sophisticated a computational system is, it can never exhibit intentionality; thus, would also fail to exhibit consciousness or any of its varieties. This paper argues that the proposed architecture mentioned above answers the problem posed by Searle, at least in part. Specifically, it argues that we could reformulate Searle’s worries in the Chinese room in terms of the three-stage artificial qualia model. And by doing so, we could see that the person doing all the translations in the room could realize the three areas in the proposed framework. Consequently, this demonstrates the actualization of self-consciousness in machines. (shrink)

Invited papers from PT-AI 2011. - Vincent C. Müller: Introduction: Theory and Philosophy of Artificial Intelligence - Nick Bostrom: The Superintelligent Will: Motivation and Instrumental Rationality in Advanced Artificial Agents - Hubert L. Dreyfus: A History of First Step Fallacies - Antoni Gomila, David Travieso and Lorena Lobo: Wherein is Human Cognition Systematic - J. Kevin O'Regan: How to Build a Robot that Is Conscious and Feels - Oron Shagrir: Computation, Implementation, Cognition.

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)

Turing does not provide an explanation for substituting the original question of his test – i.e., “Can machines think?” with “Can a machine pass the imitation game?” – resulting in an argumentative gap in his main thesis. In this article, I argue that a positive answer to the second question would mean attributing the ability of linguistic interactions to machines; while a positive answer to the original question would mean attributing the ability of thinking to machines. In such a situation, (...) defending the Turing Test requires establishing a relationship between thought and language. In this regard, Davidson's no-priority theory is presented as an approach for defending the test. (shrink)