Artificial intelligence (AI) and robotics are digital technologies that will have significant impact on the development of humanity in the near future. They have raised fundamental questions about what we should do with these systems, what the systems themselves should do, what risks they involve, and how we can control these. - After the Introduction to the field (§1), the main themes (§2) of this article are: Ethical issues that arise with AI systems as objects, i.e., tools made and used (...) by humans. This includes issues of privacy (§2.1) and manipulation (§2.2), opacity (§2.3) and bias (§2.4), human-robot interaction (§2.5), employment (§2.6), and the effects of autonomy (§2.7). Then AI systems as subjects, i.e., ethics for the AI systems themselves in machine ethics (§2.8) and artificial moral agency (§2.9). Finally, the problem of a possible future AI superintelligence leading to a “singularity” (§2.10). We close with a remark on the vision of AI (§3). - For each section within these themes, we provide a general explanation of the ethical issues, outline existing positions and arguments, then analyse how these play out with current technologies and finally, what policy consequences may be drawn. (shrink)

This paper presents the main topics, arguments, and positions in the philosophy of AI at present (excluding ethics). Apart from the basic concepts of intelligence and computation, the main topics of ar-tificial cognition are perception, action, meaning, rational choice, free will, consciousness, and normativity. Through a better understanding of these topics, the philosophy of AI contributes to our understand-ing of the nature, prospects, and value of AI. Furthermore, these topics can be understood more deeply through the discussion of AI; so (...) we suggest that “AI Philosophy” provides a new method for philosophy. (shrink)

Some authors have recently suggested that it is time to consider rights for robots. These suggestions are based on the claim that the question of robot rights should not depend on a standard set of conditions for ‘moral status’; but instead, the question is to be framed in a new way, by rejecting the is/ought distinction, making a relational turn, or assuming a methodological behaviourism. We try to clarify these suggestions and to show their highly problematic consequences. While we find (...) the suggestions ultimately unmotivated, the discussion shows that our epistemic condition with respect to the moral status of others does raise problems, and that the human tendency to empathise with things that do not have moral status should be taken seriously—we suggest that it produces a “derived moral status”. Finally, it turns out that there is typically no individual in real AI that could even be said to be the bearer of moral status. Overall, there is no reason to think that robot rights are an issue now. (shrink)

There is, in some quarters, concern about high–level machine intelligence and superintelligent AI coming up in a few decades, bringing with it significant risks for humanity. In other quarters, these issues are ignored or considered science fiction. We wanted to clarify what the distribution of opinions actually is, what probability the best experts currently assign to high–level machine intelligence coming up within a particular time–frame, which risks they see with that development, and how fast they see these developing. We thus (...) designed a brief questionnaire and distributed it to four groups of experts in 2012/2013. The median estimate of respondents was for a one in two chance that high-level machine intelligence will be developed around 2040–2050, rising to a nine in ten chance by 2075. Experts expect that systems will move on to superintelligence in less than 30 years thereafter. They estimate the chance is about one in three that this development turns out to be ‘bad’ or ‘extremely bad’ for humanity. (shrink)

There seems to be dilemma whether we should direct our efforts in AI ethics towards problems that are clearly visible on the horizon today (short-term), or towards problems for which we see significant probability of them occurring at some point (long-term), provided they are significant enough. Some authors have argued that we should put a heavy focus on the one or the other. I will argue that this is a false dilemma: Any rational agent will consider both short- and long-term (...) consequences (as well as other factors). My analysis is that the supposed dilemma rests on the assumption that we are at a very unusual situation that forces favouring of one option – what I call an “ethical singularity”. The only serious argument for this view is that the longer term involves a) an ethically “significantly different” situation, and b) that this demands a version of “ethical fanaticism”. Both premises turn out to have little in their favour. We should thus return to the “normal balance” of expected utility in AI ethics and solve problems in all relevant time horizons concurrently. (shrink)

The standard argument to the conclusion that artificial intelligence (AI) constitutes an existential risk for the human species uses two premises: (1) AI may reach superintelligent levels, at which point we humans lose control (the ‘singularity claim’); (2) Any level of intelligence can go along with any goal (the ‘orthogonality thesis’). We find that the singularity claim requires a notion of ‘general intelligence’, while the orthogonality thesis requires a notion of ‘instrumental intelligence’. If this interpretation is correct, they cannot be (...) joined as premises and the argument for the existential risk of AI turns out invalid. If the interpretation is incorrect and both premises use the same notion of intelligence, then at least one of the premises is false and the orthogonality thesis remains itself orthogonal to the argument to existential risk from AI. In either case, the standard argument for existential risk from AI is not sound.—Having said that, there remains a risk of instrumental AI to cause very significant damage if designed or used badly, though this is not due to superintelligence or a singularity. (shrink)

May lethal autonomous weapons systems—‘killer robots ’—be used in war? The majority of writers argue against their use, and those who have argued in favour have done so on a consequentialist basis. We defend the moral permissibility of killer robots, but on the basis of the non-aggregative structure of right assumed by Just War theory. This is necessary because the most important argument against killer robots, the responsibility trilemma proposed by Rob Sparrow, makes the same assumptions. We show that the (...) crucial moral question is not one of responsibility. Rather, it is whether the technology can satisfy the requirements of fairness in the re-distribution of risk. Not only is this possible in principle, but some killer robots will actually satisfy these requirements. An implication of our argument is that there is a public responsibility to regulate killer robots ’ design and manufacture. (shrink)

It is known that big data analytics and AI pose a threat to privacy, and that some of this is due to some kind of “black box problem” in AI. I explain how this becomes a problem in the context of justification for judgments and actions. Furthermore, I suggest distinguishing three kinds of opacity: 1) the subjects do not know what the system does (“shallow opacity”), 2) the analysts do not know what the system does (“standard black box opacity”), or (...) 3) the analysts cannot possibly know what the system might do (“deep opacity”). If the agents, data subjects as well as analytics experts, operate under opacity, then these agents cannot provide justifications for judgments that are necessary to protect privacy, e.g., they cannot give “informed consent”, or guarantee “anonymity.” It follows from these points that agents in big data analytics and AI ofen cannot make the judgments needed to protect privacy. So I conclude that big data analytics makes the privacy problems worse and the remedies less effective. As a positive note, I provide a brief outlook on technical ways to handle this situation. (shrink)

Will future lethal autonomous weapon systems (LAWS), or ‘killer robots’, be a threat to humanity? The European Parliament has called for a moratorium or ban of LAWS; the ‘Contracting Parties to the Geneva Convention at the United Nations’ are presently discussing such a ban, which is supported by the great majority of writers and campaigners on the issue. However, the main arguments in favour of a ban are unsound. LAWS do not support extrajudicial killings, they do not take responsibility away (...) from humans; in fact they increase the abil-ity to hold humans accountable for war crimes. Using LAWS in war would probably reduce human suffering overall. Finally, the availability of LAWS would probably not increase the probability of war or other lethal conflict—especially as compared to extant remote-controlled weapons. The widespread fear of killer robots is unfounded: They are probably good news. (shrink)

Proceedings of the 5th conference "Philosophy of AI", December 2023, Erlangen (PhAI 2023).

The dialogue develops arguments for and against a broad new world system - info-computationalist naturalism - that is supposed to overcome the traditional mechanistic view. It would make the older mechanistic view into a special case of the new general info-computationalist framework (rather like Euclidian geometry remains valid inside a broader notion of geometry). We primarily discuss what the info-computational paradigm would mean, especially its pancomputationalist component. This includes the requirements for a the new generalized notion of computing that would (...) include sub-symbolic information processing. We investigate whether pancomputationalism can provide the basic causal structure to the world and whether the overall research program of info-computationalist naturalism appears productive, especially when it comes to new approaches to the living world, including computationalism in the philosophy of mind. (shrink)

The contribution of the body to cognition and control in natural and artificial agents is increasingly described as “off-loading computation from the brain to the body”, where the body is said to perform “morphological computation”. Our investigation of four characteristic cases of morphological computation in animals and robots shows that the ‘off-loading’ perspective is misleading. Actually, the contribution of body morphology to cognition and control is rarely computational, in any useful sense of the word. We thus distinguish (1) morphology that (...) facilitates control, (2) morphology that facilitates perception and the rare cases of (3) morphological computation proper, such as ‘reservoir computing.’ where the body is actually used for computation. This result contributes to the understanding of the relation between embodiment and computation: The question for robot design and cognitive science is not whether computation is offloaded to the body, but to what extent the body facilitates cognition and control – how it contributes to the overall ‘orchestration’ of intelligent behaviour. (shrink)

We discuss at some length evidence from the cognitive science suggesting that the representations of objects based on spatiotemporal information and featural information retrieved bottomup from a visual scene precede representations of objects that include conceptual information. We argue that a distinction can be drawn between representations with conceptual and nonconceptual content. The distinction is based on perceptual mechanisms that retrieve information in conceptually unmediated ways. The representational contents of the states induced by these mechanisms that are available to a (...) type of awareness called phenomenal awareness constitute the phenomenal content of experience. The phenomenal content of perception contains the existence of objects as separate things that persist in time and time, spatiotemporal information, and information regarding relative spatial relations, motion, surface properties, shape, size, orientation, color, and their functional properties. (shrink)

The philosophy of AI has seen some changes, in particular: 1) AI moves away from cognitive science, and 2) the long term risks of AI now appear to be a worthy concern. In this context, the classical central concerns – such as the relation of cognition and computation, embodiment, intelligence & rationality, and information – will regain urgency.

The paper argues that the reference of perceptual demonstratives is fixed in a causal nondescriptive way through the nonconceptual content of perception. That content consists first in spatiotemporal information establishing the existence of a separate persistent object retrieved from a visual scene by the perceptual object segmentation processes that open an object-file for that object. Nonconceptual content also consists in other transducable information, that is, information that is retrieved directly in a bottom-up way from the scene (motion, shape, etc). The (...) nonconceptual content of the mental states induced when one uses a perceptual demonstrative constitutes the mode of presentation of the perceptual demonstrative that individuates but does not identify the object of perceptual awareness and allows reference to it. On that account, perceptual demonstratives put us in a de re relationship with objects in the world through the non-conceptual information retrieved directly from the objects in the environment. (shrink)

The theory that all processes in the universe are computational is attractive in its promise to provide an understandable theory of everything. I want to suggest here that this pancomputationalism is not sufficiently clear on which problem it is trying to solve, and how. I propose two interpretations of pancomputationalism as a theory: I) the world is a computer and II) the world can be described as a computer. The first implies a thesis of supervenience of the physical over computation (...) and is thus reduced ad absurdum. The second is underdetermined by the world, and thus equally unsuccessful as theory. Finally, I suggest that pancomputationalism as metaphor can be useful. – At the Paderborn workshop in 2008, this paper was presented as a commentary to the relevant paper by Gordana Dodig-Crnkovic " Info-Computationalism and Philosophical Aspects of Research in Information Sciences". (shrink)

In October 2011, the “2nd European Network for Cognitive Systems, Robotics and Interaction”, EUCogII, held its meeting in Groningen on “Autonomous activity in real-world environments”, organized by Tjeerd Andringa and myself. This is a brief personal report on why we thought autonomy in real-world environments is central for cognitive systems research and what I think I learned about it. --- The theses that crystallized are that a) autonomy is a relative property and a matter of degree, b) increasing autonomy of (...) an artificial system from its makers and users is a necessary feature of increasingly intelligent systems that can deal with the real-world and c) more such autonomy means less control but at the same time improved interaction with the system. (shrink)

Despite significant advancements in XAI, scholars note a persistent lack of solid conceptual foundations and integration with broader scientific discourse on explanation. In response, emerging research draws on explanatory strategies from various sciences and the philosophy of science literature to fill these gaps. This paper outlines a mechanistic strategy for explaining the functional organization of deep learning systems, situating recent developments in explainable AI within a broader philosophical context. According to the mechanistic approach, the explanation of opaque AI systems involves (...) identifying mechanisms that drive decision making. For deep neural networks, this means discerning functionally relevant components, such as neurons, layers, circuits, or activation patterns, and understanding their roles through decomposition, localization, and recomposition. Proof-of-principle case studies from image recognition and language modeling align these theoretical approaches with mechanistic interpretability research from OpenAI and Anthropic. The findings suggest that pursuing mechanistic explanations can uncover elements that traditional explainability techniques may overlook, ultimately contributing to more thoroughly explainable AI. (shrink)

This paper investigates the prospects of Rodney Brooks’ proposal for AI without representation. It turns out that the supposedly characteristic features of “new AI” (embodiment, situatedness, absence of reasoning, and absence of representation) are all present in conventional systems: “New AI” is just like old AI. Brooks proposal boils down to the architectural rejection of central control in intelligent agents—Which, however, turns out to be crucial. Some of more recent cognitive science suggests that we might do well to dispose of (...) the image of intelligent agents as central representation processors. If this paradigm shift is achieved, Brooks’ proposal for cognition without representation appears promising for full-blown intelligent agents—Though not for conscious agents. (shrink)

[This is the short version of: Müller, Vincent C. and Bostrom, Nick (forthcoming 2016), ‘Future progress in artificial intelligence: A survey of expert opinion’, in Vincent C. Müller (ed.), Fundamental Issues of Artificial Intelligence (Synthese Library 377; Berlin: Springer).] - - - In some quarters, there is intense concern about high–level machine intelligence and superintelligent AI coming up in a few dec- ades, bringing with it significant risks for human- ity; in other quarters, these issues are ignored or considered science (...) fiction. We wanted to clarify what the distribution of opinions actually is, what probability the best experts currently assign to high–level machine intelligence coming up within a particular time–frame, which risks they see with that development and how fast they see these developing. We thus designed a brief questionnaire and distributed it to four groups of experts. Overall, the results show an agreement among experts that AI systems will probably reach overall human ability around 2040-2050 and move on to superintelligence in less than 30 years thereafter. The experts say the probability is about one in three that this development turns out to be ‘bad’ or ‘extremely bad’ for humanity. (shrink)

Cognition is commonly taken to be computational manipulation of representations. These representations are assumed to be digital, but it is not usually specified what that means and what relevance it has for the theory. I propose a specification for being a digital state in a digital system, especially a digital computational system. The specification shows that identification of digital states requires functional directedness, either for someone or for the system of which it is a part. In the case or digital (...) representations, to be a token of a representational type, where the function of the type is to represent. [An earlier version of this paper was discussed in the web-conference "Interdisciplines" https://web.archive.org/web/20100221125700/http://www.interdisciplines.org/adaptation/papers/7 ]. (shrink)

Artificial intelligence (AI) is a digital technology that will be of major importance for the development of humanity in the near future. AI has raised fundamental questions about what we should do with such systems, what the systems themselves should do, what risks they involve and how we can control these. - After the background to the field (1), this article introduces the main debates (2), first on ethical issues that arise with AI systems as objects, i.e. tools made and (...) used by humans; here, the main sections are privacy (2.1), manipulation (2.2), opacity (2.3), bias (2.4), autonomy & responsibility (2.6) and the singularity (2.7). Then we look at AI systems as subjects, i.e. when ethics is for the AI systems themselves in machine ethics (2.8.) and artificial moral agency (2.9). Finally we look at future developments and the concept of AI (3). For each section within these themes, we provide a general explanation of the ethical issues, we outline existing positions and arguments, then we analyse how this plays out with current technologies and finally what policy conse-quences may be drawn. (shrink)

We can formulate an argument against AI creativity from agency. By some accounts, creativity requires agency, and agency is, many think, not possible for AI. This is due to the typical conception of agency as a capacity for intentional action. Intentional action is thought to require mental states, a severe challenge for machine intelligence. On the face of things, the agency argument seems to provide a straightforward route to argue for the impossibility of AI creativity. However, this path, I argue, (...) is not so clear. In this paper, I outline the agency argument against AI creativity, before calling into question the apparent simplicity of this argument. I argue, ultimately, that the reasoning behind the inclusion of agency in accounts of creativity does not necessitate the use of intentional action, but can instead be satisfied by a minimal teleological account of agency. (shrink)

Translation of Mark Sainsbury: Paradoxes (Cambridge University Press 1988).

This is the editorial for a special volume of JETAI, featuring papers by Omohundro, Armstrong/Sotala/O’Heigeartaigh, T Goertzel, Brundage, Yampolskiy, B. Goertzel, Potapov/Rodinov, Kornai and Sandberg. - If the general intelligence of artificial systems were to surpass that of humans significantly, this would constitute a significant risk for humanity – so even if we estimate the probability of this event to be fairly low, it is necessary to think about it now. We need to estimate what progress we can expect, what (...) the impact of superintelligent machines might be, how we might design safe and controllable systems, and whether there are directions of research that should best be avoided or strengthened. (shrink)

What proper role should considerations of risk, particularly to research subjects, play when it comes to conducting research on human enhancement in the military context? We introduce the currently visible military enhancement techniques (1) and the standard discussion of risk for these (2), in particular what we refer to as the ‘Assumption’, which states that the demands for risk-avoidance are higher for enhancement than for therapy. We challenge the Assumption through the introduction of three categories of enhancements (3): therapeutic, preventive, (...) and pure enhancements. This demands a revision of the Assumption (4), alongside which we propose some further general principles bearing on how to balance risks and benefits in the context of military enhancement research. We identify a particular type of therapeutic enhancements as providing a more responsible path to human trials of the relevant interventions than pure enhancement applications. Finally, we discuss some possible objections to our line of thought (5). While acknowledging their potential insights, we ultimately find them to be unpersuasive, at least provided that our proposal is understood as fully non-coercive towards the candidates for such therapeutic enhancement trials. (shrink)

Floridi and Taddeo propose a condition of “zero semantic commitment” for solutions to the grounding problem, and a solution to it. I argue briefly that their condition cannot be fulfilled, not even by their own solution. After a look at Luc Steels' very different competing suggestion, I suggest that we need to re-think what the problem is and what role the ‘goals’ in a system play in formulating the problem. On the basis of a proper understanding of computing, I come (...) to the conclusion that the only sensible ground-ing problem is how we can explain and re-produce the behavioral ability and function of meaning in artificial computational agents. (shrink)

Artificial intelligence (AI) involves considerable risks and uncertainties. Consequently, there is a growing need for normative guidance. In addition to an ethical understanding of AI-related issues, a legal framework is needed to ensure that important ethical aspects are adequately considered in the development and application of AI technologies. Therefore, regulatory frameworks have emerged, such as the European Union’s 2024 AI Act. However, it is an open question to what extent AI regulation aligns with AI ethics guidelines. This paper aims to (...) fill this research gap by comparing relevant ethics guidelines with legal frameworks. We focus on ethical aspects that are understood in these texts as ‘principles,’ ‘values,’ ‘recommendations’ or ‘requirements’ and provide a systematization of these aspects. A specific finding of the comparison is that in the current legal proposals, the value ‘well-being’ and its connected principles are not yet operationalized. However, these aspects are shared elements of the main ethics guidelines. This knowledge can be useful for the further development of the legal framework by illustrating important ethical aspects of AI that are not (yet) transferred to the legal realm. It is an open question how the legal system should deal with this issue. (shrink)

The declared goal of this paper is to fill this gap: “... cognitive systems research needs questions or challenges that define progress. The challenges are not (yet more) predictions of the future, but a guideline to what are the aims and what would constitute progress.” – the quotation being from the project description of EUCogII, the project for the European Network for Cognitive Systems within which this formulation of the ‘challenges’ was originally developed (http://www.eucognition.org). So, we stick out our neck (...) and formulate the challenges for artificial cognitive systems. These challenges are articulated in terms of a definition of what a cognitive system is: a system that learns from experience and uses its acquired knowledge (both declarative and practical) in a flexible manner to achieve its own goals. (shrink)

Digital ethics, also known as computer ethics or information ethics, is now a lively field that draws a lot of attention, but how did it come about and what were the developments that lead to its existence? What are the traditions, the concerns, the technological and social developments that pushed digital ethics? How did ethical issues change with digitalisation of human life? How did the traditional discipline of philosophy respond? The article provides an overview, proposing historical epochs: ‘pre-modernity’ prior to (...) digital computation over data, via the ‘modernity’ of digital data processing to our present ‘post-modernity’ when not only the data is digital, but our lives themselves are largely digital. In each section, the situation in technology and society is sketched, and then the developments in digital ethics are explained. Finally, a brief outlook is provided. (shrink)

In this review, we present some ethical imperatives observed in this pandemic from a data ethics perspective. Our exposition connects recurrent ethical problems in the discipline, such as, privacy, surveillance, transparency, accountability, and trust, to broader societal concerns about equality, discrimination, and justice. We acknowledge data ethics role as significant to develop technological, inclusive, and pluralist societies. - - - Resumen: En esta revisión, exponemos algunos de los imperativos éticos observados desde la ética de datos en esta pandemia. Nuestra exposición (...) busca conectar problemas éticos típicos dentro de esta disciplina, a saber, privacidad, vigilancia, transparencia, responsabilidad y confianza, con preocupaciones a nivel social relacionadas con la igualdad, discrimi nación y justicia. Consideramos que la ética de datos tiene un rol significativo para desarrollar sociedades tecnificadas, inclusivas y pluralistas. (shrink)

This paper explores how our concept of creativity has to be rethought in light of the increasing role of emerging generative Artificial Intelligence (GenAI) technologies in creative practice, thereby enriching the concept to include collective creativity produced by humans and AI. Collective creativity arises from the collective practices of people in relation to their nature, environment, cultures, societies, techniques, technologies, and AI. This conception of collective creativity challenges the traditional idea of the individual genius. By expanding our concept of creativity, (...) we are able to acknowledge the processes and products of humans and AI as creative. Exploring case studies of co-created art, music, and text, I argue that AI can be creative and demonstrate how AI can be creative and enhance our creativity. (shrink)

Einleitung 1 -/- Kritik des Positivismus: Realismus «Was kann ich wissen?» 1 Erklärung und Referenz (1973) 1 2 Sprache und Wirklichkeit (1975) 38 3 Was ist ‹Realismus›? (1975) 77 -/- Der dritte Weg: Interer Realismus statt metaphysischem Realismus oder Positivismus 4 Modelle und Wirklichkeit (1980) 112 5 Referenz und Wahrheit (1980) 159 6 Wie man zugleich interner Realist und transzendentaler Idealist sein kann (1980) 191 7 Warum es keine Fertigwelt gibt (1982) 218 -/- Auf des Messers Schneide: Interner Realismus und (...) Relativismus 8 Wozu die Philosophen? (1986) 259 9 Realismus mit menschlichem Antlitz (1988/90) 284 10 Irrealismus und Dekonstruktion (1992) 330 -/- Bibliographie der Schriften von Hilary Putnam 363 I Bücher 363 II Aufsätze, Vorträge und Vorlesungen 365 III Übersetzungen ins Deutsche 385 -/- Literaturverzeichnis 387 Register 413. (shrink)

There is much discussion about whether the human mind is a computer, whether the human brain could be emulated on a computer, and whether at all physical entities are computers (pancomputationalism). These discussions, and others, require criteria for what is digital. I propose that a state is digital if and only if it is a token of a type that serves a particular function - typically a representational function for the system. This proposal is made on a syntactic level, assuming (...) three levels of description (physical, syntactic, semantic). It suggests that being digital is a matter of discovery or rather a matter of how we wish to describe the world, if a functional description can be assumed. Given the criterion provided and the necessary empirical research, we should be in a position to decide on a given system (e.g. the human brain) whether it is a digital system and can thus be reproduced in a different digital system (since digital systems allow multiple realization). (shrink)

Some AI systems employ simulated representations of real-world scenarios, and these simulations are sometimes called ‘imagination’ in the engineering literature. Can imagination be attributed to AI systems? This paper will consider this question from a conceptual engineering perspective. Some key properties of imagination are identified, which characterise imagination’s relation to other mental states and its epistemic function. Simulations run by AI systems resemble human imagination with respect to these properties only partially. Thus a purely descriptive approach, which aims to address (...) the question of AI imagination by identifying the conditions that delineate our present concept of imagination, has limited prospects. Nevertheless, there are normative reasons to countenance AI imagination when simulation-based AI systems are seen as possible models of human intelligence. Some suggestions for adopting an AI-friendly concept of imagination will be offered. (shrink)

This paper explores the profound cognitive and affective impacts of Large Language Models (LLMs) and Generative AI (GenAI) on human thought, imagination, and especially our emotional life by analysing our interaction with different styles of GenAI agents especially when presented as virtual personalities. I describe how LLL-based agents can be presented using one of three broad metaphors of interaction, namely as Assistants, Extenders and Companions. Each metaphor of interaction implies distinctive cognitive patterns for their human interactant. I explore especially the (...) shape of some current interactions with GenAI companions and analyse their roles as cognitive and affective mind shapers. I analyse how Companion AI agents based on LLM technology can come to be treated as ‘Ersatz Others’ taking up deep roles in our cognitive and affective lives. I explore some of the perhaps unexpected implications of the deep reliance on such systems especially from the point of view of the theory of the extended mind and the mind-technology problem and show how this new sort of cognitive and affective environment for the human mind produces some new ethical challenges and may even reshape our future understandings of what minds are. (shrink)

Die Entwicklungen in der Künstlichen Intelligenz (KI) sind spannend. Aber wohin geht die Reise? Ich stelle eine Analyse vor, der zufolge exponentielles Wachstum von Rechengeschwindigkeit und Daten die entscheidenden Faktoren im bisherigen Fortschritt waren. Im Folgenden erläutere ich, unter welchen Annahmen dieses Wachstum auch weiterhin Fortschritt ermöglichen wird: 1) Intelligenz ist eindimensional und messbar, 2) Kognitionswissenschaft wird für KI nicht benötigt, 3) Berechnung (computation) ist hinreichend für Kognition, 4) Gegenwärtige Techniken und Architektur sind ausreichend skalierbar, 5) Technological Readiness Levels (TRL) (...) erweisen sich als machbar. Diese Annahmen werden sich als dubios erweisen. (shrink)

Medical expertise is an essential concept when discussing the potential value of Artificial Intelligence (AI) systems in advancing the medical field, as one of AI’s main promises is to positively complement the expertise of medical professionals. Yet, relatively few articles on medical AI explicitly mention what medical expertise entails, how it is practiced in medical contexts, and how AI systems relate to medical professionals’ expertise. We believe it is essential to focus on answering these questions to determine how AI should (...) be integrated into medical practice and how we should formulate the expected benefits of AI systems in clinical care. With this article, we conceptualize medical expertise and identify four forms of medical expertise: epistemic expertise, performative expertise, adaptive expertise, and virtuous expertise. Additionally, we highlight how this conceptualization of expertise can support the ethical evaluation of AI’s augmenting role in medical practices. (shrink)

This paper investigates the role of Inference to the Best Explanation (IBE) in Explainable Artificial Intelligence (XAI), arguing that IBE can both act as a framework for revealing the considerations and preferences behind XAI explanations and for guiding and evaluating them in a more rigorous manner. The paper focusses specifically on post-hoc explainability and model agnostic techniques, illustrating the argument through examples of salience maps and feature importance techniques. Here, IBE in XAI happens in two steps. The first aims at (...) maximising the range and accuracy of possible inferences made; the second aims to provide a certain balance of explanatory virtues given a certain why-question and stakeholder that requires an explanation. Using the language of explanatory virtues enables a more nuanced discussion about what we may like or dislike about certain explanations in the current XAI landscape and provides actionable ways of improving explanations. (shrink)

There are unusual challenges in ethics for RAS. Perhaps the issue can best be summarised as needing to consider “technically informed ethics”. The technology of RAS raises issues that have an ethical dimension, and perhaps uniquely so due to the possibility of moving human decision-making which is implicitly ethically informed to computer systems. Further, if seeking solutions to these problems – ethically aligned design, to use the IEEE’s terminology – then the solutions must be technically meaningful, capable of realisation, capable (...) of assurance, and suitable as a basis for regulation. Thus, ethics for RAS is a rich, complex multi-disciplinary concern, and perhaps more complex than many other ethical issues facing society today. It is also fast-moving. This paper has endeavoured to give an accessible introduction to some of the key issues, noting that many of them are quite subtle, and it is not possible to do them full justice in such a short document. However, we have sought to counterbalance this by giving an extensive list of initiatives, standards, etc. that focus on ethics of RAS and AI, see Annex A. (shrink)

In the aftermath of the success of attention-based transformer networks, the debate over the potential and role of consciousness in artificial systems has intensified. Prominently, the Global Neuronal Workspace Theory emerges as a front-runner in the endeavor to model consciousness in computational terms. A recent advancement in the direction of mapping the theory onto state-of-the-art machine learning tools is the model of a Global Latent Workspace. It introduces a central latent representation around which multiple modules are constructed. Leveraging dedicated encoder-decoder (...) structures, content from the central representation or any individual module, integrated via the latent space, can be translated to any other module and back with minimal loss. This paper presents a thought experiment involving a minimal setup with one deep sensory and one deep motor module, which illustrates the emergence of “globally” accessible sensorimotor representations in the central latent space connecting both modules. In the human brain, neuronally enacted knowledge of laws relating changes in sensory information to changes in motor output or corresponding efferent copy information have been proposed to constitute the biological correlates of phenomenal conscious experience. The underlying Sensorimotor Contingency Theory encompasses a rich mathematical framework. Yet, the implementation of intelligent systems based on this framework has thus far been confined to proof-of-concept and basic prototype applications. Here, the natural appearance of global latent sensorimotor representations links two major neuroscientific theories of consciousness in a powerful machine learning setup. A remaining question is whether this artificial system is conscious. (shrink)

The central concept of this edited volume is "blended cognition", the natural skill of human beings for combining constantly different heuristics during their several task-solving activities. Something that was sometimes observed like a problem as “bad reasoning”, is now the central key for the understanding of the richness, adaptability and creativity of human cognition. The topic of this book connects in a significant way with the disciplines of psychology, neurology, anthropology, philosophy, logics, engineering, logics, and AI. In a nutshell: understanding (...) better humans for designing better machines. It contains a Preface by the editors and 12 chapters. (shrink)

Special Issue “Risks of artificial general intelligence”, Journal of Experimental and Theoretical Artificial Intelligence, 26/3 (2014), ed. Vincent C. Müller. http://www.tandfonline.com/toc/teta20/26/3# - Risks of general artificial intelligence, Vincent C. Müller, pages 297-301 - Autonomous technology and the greater human good - Steve Omohundro - pages 303-315 - - - The errors, insights and lessons of famous AI predictions – and what they mean for the future - Stuart Armstrong, Kaj Sotala & Seán S. Ó hÉigeartaigh - pages 317-342 - - (...) - The path to more general artificial intelligence - Ted Goertzel - pages 343-354 - - - Limitations and risks of machine ethics - Miles Brundage - pages 355-372 - - - Utility function security in artificially intelligent agents - Roman V. Yampolskiy - pages 373-389 - - - GOLEM: towards an AGI meta-architecture enabling both goal preservation and radical self-improvement - Ben Goertzel - pages 391-403 - - - Universal empathy and ethical bias for artificial general intelligence - Alexey Potapov & Sergey Rodionov - pages 405-416 - - - Bounding the impact of AGI - András Kornai - pages 417-438 - - - Ethics of brain emulations - Anders Sandberg - pages 439-457. (shrink)

We describe a method, based on Jennifer Nado’s proposal for classification procedures as targets of conceptual engineering, that implements such procedures by prompting a large language model. We apply this method, using data from the Wikidata knowledge graph, to evaluate stipulative definitions related to two paradigmatic conceptual engineering projects: the International Astronomical Union’s redefinition of PLANET and Haslanger’s ameliorative analysis of WOMAN. Our results show that classification procedures built using our approach can exhibit good classification performance and, through the generation (...) of rationales for their classifications, can contribute to the identification of issues in either the definitions or the data against which they are being evaluated. We consider objections to this method, and discuss implications of this work for three aspects of theory and practice of conceptual engineering: the definition of its targets, empirical methods for their investigation, and their practical roles. The data and code used for our experiments, together with the experimental results, are available in a Github repository (https://github.com/bradleypallen/zero-shot-classifiers-for-conceptual-engineering). (shrink)

Robert Sparrow argues that while we should recognize vice in mistreatments and cruelty towards robots, like kicking, we shouldn’t recognize virtue. I discuss some problems with this argument. While we’re supposed to investigate whether it is wrong to kick robots, Sparrow’s premise isn’t neutral about such actions, describing them with morally loaded terms like ‘cruel’. I show that such premises with morally loaded terms cannot be taken as given in Human-Robot Interaction (HRI). By focusing on graphic mistreatment scenarios and on (...) what robots resemble or represent, Sparrow and others fail to account for broader, everyday interactions. Where robots come with unique affordance mixtures, don’t necessarily resemble or represent other beings and are directly perceived (rather than fictionalized as Sparrow claims). Thus, robots can be treated in ways different than humans and animals. I emphasize how situation, context, dynamics, interaction and direct affordance perception matter in HRI, where robots play an active role, rather than being passively anthropomorphized or fictionalized. Thus, there is a need for more cognitive scientific insight into HRI ethics. Especially into the indirect robot moral patiency debate, which has been stuck with graphic mistreatment scenarios and stuck with limited descriptive concepts like anthropomorphism and taking robots as representation of other beings. (shrink)

Many Artificial Intelligence (AI) tools have been developed for suicide prevention. These technologies are wide ranging, from Language Models (LM) in chatbots for therapy or triaging, computer vision algorithms designed to detect specific human motions to the use of limited emotion theories to detect emotional states. Both their design and implementation raise ethical concerns, especially considering that - unlike clinical research on human subjects - they are not necessarily subjected to any regulations or ethics governance structures, nor does the design (...) or implementation require any formal expertise in mental health. Considering the nature of such technologies, the high-risk area they are applied in, and the explicit targeting of vulnerable populations, this is concerning. In this work, we aim to (a) give an overview of such tools, (b) provide some insight into key ethical concerns, (c) demonstrate that these technologies do not necessarily comply with existing guidelines regarding human subject research, although some of the tools would most likely be subjected to it, had they been done in a clinical setting (d) argue that there is an unmet need for specific ethics guidelines for research, scientists, and practitioners working at the intersection of AI and suicide prevention, and (e) provide such guidelines. (shrink)

This paper investigates the view that digital hypercomputing is a good reason for rejection or re-interpretation of the Church-Turing thesis. After suggestion that such re-interpretation is historically problematic and often involves attack on a straw man (the ‘maximality thesis’), it discusses proposals for digital hypercomputing with Zeno-machines , i.e. computing machines that compute an infinite number of computing steps in finite time, thus performing supertasks. It argues that effective computing with Zeno-machines falls into a dilemma: either they are specified such (...) that they do not have output states, or they are specified such that they do have output states, but involve contradiction. Repairs though non-effective methods or special rules for semi-decidable problems are sought, but not found. The paper concludes that hypercomputing supertasks are impossible in the actual world and thus no reason for rejection of the Church-Turing thesis in its traditional interpretation. (shrink)

This article delves into the evolving role of philosophy in governance debates, as affected by the emergence of Artificial Moral Agents (AMAs). It examines how AMAs, designed to make moral decisions, are shaping moral discourse and standards in various spheres of action. The analysis distinguishes between the traditional role of philosophers in critique and the potential shift towards policy drafting prompted by the development of AMAs. Ethical implications of these trends are explored, focusing on concerns about negotiability in societal standards (...) and the alignment of moral standards with human conduct. The article highlights the need for careful consideration in policy and ethical discussions in this development. (shrink)

The paper discusses the extended mind thesis with a view to the notions of “agent” and of “mind”, while helping to clarify the relation between “embodiment” and the “extended mind”. I will suggest that the extended mind thesis constitutes a reductio ad absurdum of the notion of ‘mind’; the consequence of the extended mind debate should be to drop the notion of the mind altogether – rather than entering the discussion how extended it is.