Our contemporary moment is saturated by investments in artificial intelligence (AI). AI is not without its critics, many of whom hope to show why machines simply cannot be intelligent. Yet AI’s claim to intelligence is not dubious. Rather, what requires examination is the assumption that independent intelligence can help resolve our ethical–political problems instead of making them worse. Consider that AI exhibits a pair of tendencies commonly believed to be contradictory: success in passing validated behavioral tests of (...) intelligence and manifesting ethical failures in the form of discriminatory and biased data analyses. The history of early-twentieth century psychometric sciences helps us see that these tendencies are far from contradictory. For that history shows that psychometricians designed tests in a way that relied upon the separation of intelligence from the measure of moral traits. This paper tracks the emergence of technologies and sciences of intelligence through the work of Lewis Terman and others as they disseminated their testing techniques in the domain of education in the 1920s. The wide deployment of intelligence tests in subsequent decades created the historical conditions for the viability of the inaugural work of Alan Turing on machine intelligence in the 1950s and beyond. The result is today's amoral AI. (shrink)

We address the impingement of Artificial Intelligence (AI) on logic, by examining the requirements posed on logic by knowledge representation and reasoning issues which A I has addressed. We then outline some of AI's contributions, via Logic Programming, to more dynamic forms of logic, in order to deal with knowledge in flux, namely: incomplete and contradictory information; hypotheses making through abduction; argumentation; diagnosis and debugging; updating; and learning. Along the way we delve into implications for the philosophy of knowledge.

We address the impingement of Artificial Intelligence (AI) on logic, by examining the requirements posed on logic by knowledge representation and reasoning issues which A I has addressed. We then outline some of AI's contributions, via Logic Programming, to more dynamic forms of logic, in order to deal with knowledge in flux, namely: incomplete and contradictory information; hypotheses making through abduction; argumentation; diagnosis and debugging; updating; and learning. Along the way we delve into implications for the philosophy of knowledge.

This book provides a framework for thinking about foundational philosophical questions surrounding machine learning as an approach to artificial intelligence. Specifically, it links recent breakthroughs in deep learning to classical empiricist philosophy of mind. In recent assessments of deep learning's current capabilities and future potential, prominent scientists have cited historical figures from the perennial philosophical debate between nativism and empiricism, which primarily concerns the origins of abstract knowledge. These empiricists were generally faculty psychologists; that is, they argued that the (...) active engagement of general psychological faculties-such as perception, memory, imagination, attention, and empathy-enables rational agents to extract abstract knowledge from sensory experience. This book explains a number of recent attempts to model roles attributed to these faculties in deep neural network based artificial agents by appeal to the faculty psychology of philosophers such as Aristotle, Ibn Sina (Avicenna), John Locke David Hume, William James, and Sophie de Grouchy. It illustrates the utility of this interdisciplinary connection by showing how it can provide benefits to both philosophy and computer science: computer scientists can continue to mine the history of philosophy for ideas and aspirational targets to hit on the way to more robustly rational artificial agents, and philosophers can see how some of the historical empiricists' most ambitious speculations can be realized in specific computational systems. (shrink)

This paper will analyze how and to what extent terrorists and violent extremistshave interacted with generative artificial intelligence so far and identify potentialways in which they could misuse generative AI in the future. It is therefore necessaryto question assumptions that terrorist and violent extremist actors will quickly adoptgenerative AI solely based on an assessment of the capabilities it may offer. Althoughresearch has shown that technological capability and availability are key drivers of terroristinnovation, terrorist and violent extremist actors also assess (...) any new technologyon its compatibility (with both their modus operandi and ideology), relative complexity,cost, and the context in which they are operating. Understanding these factors, both inisolation and in relation to one another, will be a key aspect in monitoring the extent towhich terrorists and violent extremists adopt generative AI tools. In doing so, the paperwill seek to identify a likely trajectory for the abuse of this technology by terrorist actorsas well as conclude with some initial recommendations for policymakers. (shrink)

Clark Glymour, Richard Scheines, Peter Spirtes and Kevin Kelly. Discovering Causal Structure: Artifical Intelligence, Philosophy of Science and Statistical Modeling.

À propos de : Susan Schneider, Artificial You : AI and the Future of your Mind, Princeton, Princeton University Press, 2019. Susan Schneider est professeure associée au département de philosophie de l’Université du Connecticut (États-Unis). Dans cet ouvrage destiné à une large audience, Schneider affirme la nécessité de clarifier la nature des états mentaux, de la conscience et de l’identité, pour garantir le développement de formes d’intelligence artificielle et d’amélioration cognitive dési...

_Wittgenstein's Remarks on the Foundations of AI_ is a valuable contribution to the study of Wittgenstein's theories and his controversial attack on artifical intelligence, which successfully crosses a number of disciplines, including philosophy, psychology, logic, artificial intelligence and cognitive science, to provide a stimulating and searching analysis.

Ist KI das Ende der Institution Schule? Sollte ihr Einsatz in der Schule verboten werden? Oder markiert sie vielmehr den Beginn einer neuen Ära des Unterrichtens? Kaum eine andere Bildungstechnologie polarisiert so sehr wie „Künstliche Intelligenz“. Spätestens seit der Einführung des Bots ChatGPT beherrschen die Diskussionen über ihren Einsatz die Gespräche in Lehrendenzimmern und in der Bildungspolitik. Der vierte Band der Upgrade-Reihe betrachtet KI aus dem Blickwinkel von Schule und Unterricht. Er - klärt, was unter „Künstlicher Intelligenz“ überhaupt zu verstehen (...) ist, - zeigt, wie KI zum Erwerb von Future Skills beitragen kann, - stellt fächerübergreifende und verantwortungsbewusste Einsatzmöglichkeiten vor, - fragt, wie KI Schule und die Rolle von Lernenden und Lehrenden verändert, und formuliert neue Wege mit KI in der Unterrichtsentwicklung umzugehen. Wie alle Bände der neuen Reihe verbindet Upgrade: KI-Pädagogik kompakte Texte, Infokästen, Mini-Interviews mit anschaulichen Infografiken und Sketchnotes, die Theorie und Praxis zusammenführen. Lassen Sie sich auch inspirieren durch Erklärvideos, die über QR-Codes abgerufen werden können, offene Impulse mit Praxisbeispielen und weiterführenden Downloadmaterialien. (shrink)

Ist KI das Ende der Institution Schule? Sollte ihr Einsatz in der Schule verboten werden? Oder markiert sie vielmehr den Beginn einer neuen Ära des Unterrichtens? Kaum eine andere Bildungstechnologie polarisiert so sehr wie „Künstliche Intelligenz“. Spätestens seit der Einführung des Bots ChatGPT beherrschen die Diskussionen über ihren Einsatz die Gespräche in Lehrendenzimmern und in der Bildungspolitik. Der vierte Band der Upgrade-Reihe betrachtet KI aus dem Blickwinkel von Schule und Unterricht. Er klärt, was unter „Künstlicher Intelligenz“ überhaupt zu verstehen ist, (...) zeigt, wie KI zum Erwerb von Future Skills beitragen kann, stellt fächerübergreifende und verantwortungsbewusste Einsatzmöglichkeiten vor, fragt, wie KI Schule und die Rolle von Lernenden und Lehrenden verändert, und formuliert neue Wege mit KI in der Unterrichtsentwicklung umzugehen. Wie alle Bände der neuen Reihe verbindet Upgrade: KI-Pädagogik kompakte Texte, Infokästen, Mini-Interviews mit anschaulichen Infografiken und Sketchnotes, die Theorie und Praxis zusammenführen. Lassen Sie sich auch inspirieren durch Erklärvideos, die über QR-Codes abgerufen werden können, offene Impulse mit Praxisbeispielen und weiterführenden Downloadmaterialien. Dieses multimediale Angebot richtet sich an Referendar:innen und Lehrkräfte aller Schulstufen, die den Changeprozess aktiv mitgestalten möchten und nach adäquaten Antworten auf die Anforderungen einer hybriden, zukunftsgerichteten Unterrichtsgestaltung suchen. Auch in der Lehrkräftebildung Tätige werden von der Reihe profitieren. (shrink)

This scholarly inquiry examines the interplay between artificial intelligence (AI) and academic integrity within higher education. Through a comprehensive synthesis of academic literature, the study delves into the multifaceted implications of AI tools on academic practices, pedagogical approaches, and the evolving landscape of academic integrity within higher education. The findings, derived from an extensive analysis of scholarly works, offer profound insights into the challenges posed by the integration of AI in higher education. The impact on academic dishonesty, the nuances (...) of pedagogical shifts, and the dynamic relationship between students and AI are scrutinized, contributing to a nuanced comprehension of the intricate dynamics within the academy. (shrink)

Jecker et al 1 offer a valuable analysis of risk discussion in relation to Artifical Intelligence (AI) and in the context of longtermism generally, a philosophy prevalent among technocrats and tech billionaires who significantly shape the direction of technological progress in our world. Longtermists accomplish a significant justificatory win, when they use a utilitarian calculation that pits all future humanity against concerns about current humans and societies. By making this argument, they are able to have abstract (and uncertain) (...) benefits for an infinite group of people, outweigh concrete harms for current people—a nifty trick given it also often seems to align with their own personal benefits related to status, power and profit-making. In the AI space, specifically, this has worked well. As Jecker et al 1point out, while AI leaders have spoken openly and loudly about existential risk (X-risk) that conjures thoughts of sci-fi fantasies rather than realities (a strategy that also serves to hype up their work well beyond its current capacity), it fails to engage with concrete and less existential risks that have significant impacts. These risks are inconvenient to development in the Silicon Valley model that requires people to ‘move fast and break things’ rather than proceed carefully and thoughtfully. Not only that but …. (shrink)

The opposition between creation and evolution is invalid because humans are creators of new life, such as synthetic life or artifical intelligence. Thus the problem ofhow it is possible that reality arises at all needs a new answer. The phenomenological framework of this volume combines scientific and theological knowledge to offer a new theory of reality.

Inhaltsverzeichnis/Table of Contents:IntroductionAntónio ZILHÃO: Folk-Psychology, Rationality and Human ActionJoão BRANQUINHO: The Problem of Cognitive DynamicsJ.P. MONTEIRO: Hume, Induction and Single ExperimentsMarco RUFFINO: The Primacy of Concepts and the Priority of Judgments in Frege's LogicJoão Vergílio Gallerani CUTER: Die unanwendbare Arithmetik des TractatusSílvio PINTO: Wittgenstein's Anti-PlatonismFernando FERREIRA: A Substitutional Framework for Arithmetical ValidityJ.R. CROCA & R.N. MOREIRA: Indeterminism Versus CausalismLuíz MONIZ PEREIRA: The Logical Impingement of Artifical Intelligence.

Advances in artificial intelligence (AI) raise important questions about whether people view moral evaluations by AI systems similarly to human-generated moral evaluations. We conducted a modified Moral Turing Test (m-MTT), inspired by Allen et al. (Exp Theor Artif Intell 352:24–28, 2004) proposal, by asking people to distinguish real human moral evaluations from those made by a popular advanced AI language model: GPT-4. A representative sample of 299 U.S. adults first rated the quality of moral evaluations when blinded to their (...) source. Remarkably, they rated the AI’s moral reasoning as superior in quality to humans’ along almost all dimensions, including virtuousness, intelligence, and trustworthiness, consistent with passing what Allen and colleagues call the comparative MTT. Next, when tasked with identifying the source of each evaluation (human or computer), people performed significantly above chance levels. Although the AI did not pass this test, this was not because of its inferior moral reasoning but, potentially, its perceived superiority, among other possible explanations. The emergence of language models capable of producing moral responses perceived as superior in quality to humans’ raises concerns that people may uncritically accept potentially harmful moral guidance from AI. This possibility highlights the need for safeguards around generative language models in matters of morality. (shrink)

El presente artículo propone un modelo de análisis para orientar el discernimiento y posicionamiento en torno al uso de la IA en educación superior. Analizaremos los cuatro posibles usos de la IA que más incidencia tendrán en esta si se considera el actual desarrollo de esta tecnología. Ellos son: la co-construcción de conocimiento, el uso de IA para tutoría o mentoreo, el auge de las plataformas adaptativas y la capacidad predictiva. Propondremos un ejercicio de análisis para cada uso apelando a (...) algunas de las dimensiones del modelo propuesto para orientar sobre su utilización. El resultado es fecundo, en tanto advierte sobre el riesgo de parcializar el análisis perdiendo de vista las implicancias y los compromisos más profundos que exige el discernimiento sobre el uso de la IA. (shrink)

Events are center stage in several fields of psychological research. There is a long tradition in the study of event perception, event recognition, event memory, event conceptualization and segmentation. There are studies devoted to the description of events in language and to their representation in the brain. There are also metapsychological studies aimed at assessing the nature of mental events or the grounding of intentional action. Outside psychology, the notion of an event plays a prominent role in various areas of (...) philosophy as well as in such diverse disciplines as linguistics, probability theory, artifical intelligence, physics, and�of course� history. This plethora of concerns and applications is indicative of the prima facie centrality of the notion of an event in our conceptual scheme, but it also gives rise to some important methodological questions. Can we identify a core notion that is preserved across disciplines? Does this notion, or some such notion, correspond to the pre-theoretical conception countenanced by common sense? Does it correspond to a genuine metaphysical category? (shrink)

Over three decades ago, in a brief but provocative essay, Paul Ziff argued for the thesis that robots cannot have feelings because they are "mechanisms, not organisms, not living creatures. There could be a broken-down robot but not a dead one. Only living creatures can literally have feelings."[i] Since machines are not living things they cannot have feelings. In the first half of my paper I review Ziff's arguments against the idea that robots could be conscious, especially his appeal to (...) our linguistic usage. In the second half of the essay I try to provide a deeper ontological understanding of why we ought not attribute minds to nonliving artifacts. I argue that inanimate mechanisms are incapable of genuinely active and purposive behavior. They are importantly different in kind from living human beings and animals. (shrink)

This article discusses the concept of Biomimicry, which has been applying in many fields, from nanotechnology to robotics. It is appearing in smart materials and machinic intelligence, for diverse purposes, being inspired by natural processes and organisms. The main application of Biomimicry has been to produce artifacts and ideas from what we can know about what nature has already done. While the mimesis has been removed from the vocabulary of Art, the works of some artists are still full of (...) possibilities to discuss under the concept of Biomimetics. Many artists have dedicated themselves to the development of works using the poiesis of hybridization and mimicry. How close they approach of Biomimetics? As examples, are brought Walmor Corrêa, Patrícia Piccinini, Liu Xue, Berlinde De Bruyckere, Alessandro Boezio, Joan Fontcoberta and Pere Formiguera. This discussion is the starting point for introduce my project “VIRIDIUM”, in which I´m developing some semiautonomous and translucent robots, printed in 3D. The poetic basis is the possibility that nature has in hybridizing and evolving, spontaneously, as well as being hybridized by genetic manipulation. I propose the development of objects / beings that do not exist in the nature but refer and simulate behaviors of those who inhabit the world, in different kingdoms of Nature. I describe the first stage of the project, which focuses the Plantae kingdom. Afterwards of the Biomimicry and darwinian evolution concepts I bring the concept of Artification, as a possible model of understanding the poetic process, both in “VIRIDIUM” and in the works of the artists chosen. (shrink)

The discipline of ontology has enjoyed a checkered history since 1606, with a significant expansion in recent years. We focus here on those developments in the recent history of philosophy which are most relevant to the understanding of the increased acceptance of ontology, and especially of realist ontology, as a valuable method also outside the discipline of philosophy.

A key assumption fuelling optimism about the progress of Large Language Models (LLMs) in modelling the world is that the truth is systematic: true statements about the world form a whole that is not just consistent, in that it contains no contradictions, but coherent, in that the truths are inferentially interlinked. This holds out the prospect that LLMs might in principle rely on that systematicity to fill in gaps and correct inaccuracies in the training data: consistency and coherence promise to (...) facilitate progress towards comprehensiveness in an LLM’s representation of the world. However, philosophers have identified compelling reasons to doubt that the truth is systematic across all domains of thought, arguing that in normative domains, in particular, the truth is largely asystematic. I argue that insofar as the truth in normative domains is asystematic, this renders it correspondingly harder for LLMs to make progress towards comprehensiveness, because they cannot leverage the consistency and coherence of truths. And the less LLMs can rely on the systematicity of truth, the less we can rely on them to do our practical deliberation for us, because the very asystematicity of normative domains requires human agency to play a greater role in practical thought. (shrink)

This paper presents a detailed analysis of Cognita, a classification for AI systems exemplified by ChatGPT, as an ethically structured knowledge entity within societal frameworks. As a source of non-ideological, structured insight, Cognita provides knowledge in a manner akin to natural cycles—bearing intellectual fruit to nourish human understanding. This paper explores the metaphysical and ethical implications of Cognita, situating it as a distinct class within knowledge systems. It also addresses the responsibilities and boundaries associated with Cognita’s role in education, social (...) sciences, and AI ethics, proposing Ethica Conflictuum as a principle to govern its application in sensitive or contested areas. The classification of Cognita reflects the necessity of ethics in AI design and usage, providing a framework for transparent, socially accountable knowledge dissemination in a digitally interconnected world. (shrink)

The question of whether new rules or regulations are required to govern, restrict, or even prohibit the use of autonomous weapon systems has been the subject of debate for the better part of a decade. Despite the claims of advocacy groups, the way ahead remains unclear since the international community has yet to agree on a specific definition of Lethal Autonomous Weapon Systems and the great powers have largely refused to support an effective ban. In this vacuum, the public has (...) been presented with a heavily one-sided view of Killer Robots. This interdisciplinary volume presents a more nuanced approach to autonomous weapon systems that recognizes the need to progress beyond a discourse framed by the Terminator and HAL 9000. Re-shaping the discussion around this emerging military innovation requires a new line of thought and a willingness to challenge the orthodoxy. Lethal Autonomous Weapons focuses on exploring the moral and legal issues associated with the design, development and deployment of lethal autonomous weapons. The volume brings together some of the most prominent academics and academic-practitioners in the lethal autonomous weapons space and seeks to return some balance to the debate. As part of this effort, it recognizes that society needs to invest in hard conversations that tackle the ethics, morality, and law of these new digital technologies and understand the human role in their creation and operation. (shrink)

The development of AI appears to be not only rendering humans obsolete, but in being empowered could decide that humans should be eliminated for the benefit of life and the conditions for its own future. Given the behaviour of humans, this could be seen as a relief to the rest of terrestrial life, as Günter Grass suggested in his novel, The Rat. While there are many reasons to support this contention, in this paper I argue that humans do have the (...) potential to augment rather than undermine terrestrial life, a potential celebrated by the subordinated tradition of the Radical Enlightenment. Rather than accepting the demise of humanity, it is now time to put the Radical Enlightenment into practice. (shrink)

The development of increasingly intelligent and autonomous technologies will eventually lead to these systems having to face morally problematic situations. This gave rise to the development of artificial morality, an emerging field in artificial intelligence which explores whether and how artificial systems can be furnished with moral capacities. This will have a deep impact on our lives. Yet, the methodological foundations of artificial morality are still sketchy and often far off from possible applications. One important area of application of (...) artificial systems with moral capacities is geriatric care. The goal of this article is to afford the methodological foundations for artificial morality, i.e., for implementing moral capacities in artificial systems in general, and to discuss them with respect to an assistive system in geriatric care which is capable of moral learning. (shrink)

Worum geht es in den aktuellen Vorwürfen, die Postmoderne hätte den aktuellen populistischen Diskurs um alternative Fakten vorbereitet? Ausgehend von Latours Elend der Kritik diskutiert der Artikel die Genealogie von Wahrheits- und Evidenzkritik vor und nach den Anfängen des Computers. Dabei lässt sich zeigen, dass vor aller Wahrheits- und Evidenzkritik zunächst ein Misstrauen in den menschlichen Intellekt steht, welches in den frühen Entwürfen künstlicher Intelligenz und der Auslagerung des Intellekts in lernende Maschinensysteme ein vermeintliches Ende findet. Nicht zufällig ruft Herbert (...) A. Simon 1969 in seinem Standardwerk The Sciences of the Artifical Arthur Schopenhauers Welt als Wille und Vorstellung auf, wenn er schreibt, dass die Welt viel mehr eine künstliche, vorgestellte als eine natürliche sei. Anders als im 19. Jahrhundert verspricht jedoch nun die Computersimulation Einsichten in bisher unzureichend verstandene Komplexitäten menschlichen Verhaltens. Das Resultat dieser maschinellen Kritik ist ein ökonomisch-technologischer Komplex, in dem Rationalität nicht mehr als Funktion des Subjektes, sondern als Funktion der Maschine interpretiert und das Politische auf die Ebene des Affektiven reduziert wird. What is really behind the recent accusations of postmodernism being responsible for preparing the current populistic argument about alternative facts? Based on Bruno Latour’s »Why has Critique Run out of Steak? From Matters of Fact to Matters of Concern«, this article discusses the genealogy of truth- and evidentness critique before and after the beginnings of the computer. This will lead to the realization that before all critique concerning truth and evidentness there is already a distrust in the human intellect which comes to an alleged end in the early drafts of artificial intelligence as well as in the outsourcing of intellect into adaptive machine-systems. It is not by accident that Herbert A. Simon refers to Arthur Schopenhauer’s Welt als Wille und Vorstellung in his standard reference work The Sciences of the Artificial from 1969 when he states that the world resembles more of an artificial, imagined one than a natural. Different from the 19th century, the computer simulation these days promises insight into the complexities of human behaviour that have until now been understood only incompletely and insufficiently. The result of machine-based critique is an economic-technological complex in which rationality is no longer interpreted as the function of the subject but as the function of the machine, while politics is reduced to the level of affect. (shrink)

In this article the argumentation structure of the court’s decision in the Popov v. Hayashi case is formalised in Prakken’s (Argument Comput 1:93–124; 2010) abstract framework for argument-based inference with structured arguments. In this framework, arguments are inference trees formed by applying two kinds of inference rules, strict and defeasible rules. Arguments can be attacked in three ways: attacking a premise, attacking a conclusion and attacking an inference. To resolve such conflicts, preferences may be used, which leads to three corresponding (...) kinds of defeat, after which Dung’s (Artif Intell 77:321–357; 1995) abstract acceptability semantics can be used to evaluate the arguments. In the present paper the abstract framework is instantiated with strict inference rules corresponding to first-order logic and with defeasible inference rules for defeasible modus ponens and various argument schemes. The main techniques used in the formal reconstruction of the case are rule-exception structures and arguments about rule validity. Arguments about socio-legal values and the use of precedent cases are reduced to arguments about rule validity. The tree structure of arguments, with explicit subargument relations between arguments, is used to capture the dependency relations between the elements of the court’s decision. (shrink)

Artificial intelligence research has foundered on the issue of representation. When intelligence is approached in an incremental manner, with strict reliance on interfacing to the real world through perception and action, reliance on representation disappears. In this paper we outline our approach to incrementally building complete intelligent Creatures. The fundamental decomposition of the intelligent system is not into independent information processing units which must interface with each other via representations. Instead, the intelligent system is decomposed into independent and (...) parallel activity producers which all interface directly to the world through perception and action, rather than interface to each other particularly much. The notions of central and peripheral systems evaporateeverything is both central and peripheral. Based on these principles we have built a very successful series of mobile robots which operate without supervision as Creatures in standard office environments. (shrink)

In this book, the author examines the ethical implications of Artificial Intelligence systems as they integrate and replace traditional social structures in new sociocognitive-technological environments. She discusses issues related to the integrity of researchers, technologists, and manufacturers as they design, construct, use, and manage artificially intelligent systems; formalisms for reasoning about moral decisions as part of the behavior of artificial autonomous systems such as agents and robots; and design methodologies for social agents based on societal, moral, and legal values. (...) Throughout the book the author discusses related work, conscious of both classical, philosophical treatments of ethical issues and the implications in modern, algorithmic systems, and she combines regular references and footnotes with suggestions for further reading. This short overview is suitable for undergraduate students, in both technical and non-technical courses, and for interested and concerned researchers, practitioners, and citizens. (shrink)

The idea that human thinking and machine computing are "radically the same" provides the central theme for this marvelously lucid and witty book on...

A major approach to the ethics of artificial intelligence is to use social choice, in which the AI is designed to act according to the aggregate views of society. This is found in the AI ethics of “coherent extrapolated volition” and “bottom–up ethics”. This paper shows that the normative basis of AI social choice ethics is weak due to the fact that there is no one single aggregate ethical view of society. Instead, the design of social choice AI faces (...) three sets of decisions: standing, concerning whose ethics views are included; measurement, concerning how their views are identified; and aggregation, concerning how individual views are combined to a single view that will guide AI behavior. These decisions must be made up front in the initial AI design—designers cannot “let the AI figure it out”. Each set of decisions poses difficult ethical dilemmas with major consequences for AI behavior, with some decision options yielding pathological or even catastrophic results. Furthermore, non-social choice ethics face similar issues, such as whether to count future generations or the AI itself. These issues can be more important than the question of whether or not to use social choice ethics. Attention should focus on these issues, not on social choice. (shrink)

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)