On the whole, the US Algorithmic Accountability Act of 2022 (US AAA) is a pragmatic approach to balancing the benefits and risks of automated decision systems. Yet there is still room for improvement. This commentary highlights how the US AAA can both inform and learn from the European Artificial Intelligence Act (EU AIA).

With the rapid advances in science and technology, Artificial Intelligence (AI) has been developing exponentially and transforming the world in ways we could never have envisioned. Its applications...

This study contributes to the constantly accumulating evidence on the effects of customer incivility (CI) on service employee exhaustion. Previous research has demonstrated that surface acting (SA) acts as a mediating variable in the relationship between CI and exhaustion. This study extended prior findings in two ways. The results of Study 1 (315 retail sales employees, 62.2% female) demonstrated that SA mediates the positive relationship between CI and exhaustion while controlling for employees’ trait positive and negative affectivity (NA). The results (...) of Study 2 (292 customer service representatives, 51% female) supported a moderated mediation model demonstrating that trait emotional intelligence (EI) buffers the direct and indirect (through SA) effects of CI on exhaustion. Specifically, it was found that employees exposed to many uncivil customer behaviors but high in trait EI reported using less SA and, thus, experienced fewer exhaustion symptoms than their low in trait EI counterparts. These results highlight EI as an important personal resource that mitigates the adverse effects of CI on service employees’ exhaustion, and suggest that organizations should consider implementing EI training programmes for their frontline service employees. (shrink)

Hauser considers John Searle's attempt to distinguish acts from movements. On Searle's account, the difference between me raising my arm and my arm's just going up (e.g., if you forcibly raise it), is the causal involvement of my intention to raise my arm in the former, but not the latter, case. Yet, we distinguish a similar difference between a robot's raising its arm and its robot arm just going up (e.g., if you manually raise it). Either robots are rightly credited (...) with intentions or it's not intention that distinguishes action from mere movement. In either case acts are attributable to robots. Since the truth of such attributions depends not on the speaker's "intentional stance" but on "intrinsic" features of the things they are not merely figurative "as if" attributions. Gunderson allows that internally propelled programmed devices (Hauser Robots) do act but denies that they have the mental properties such acts seem to indicate. Rather, given our intuitive conviction that these machines lack consciousness, such performances evidence the dementalizability of acts.Hauser replies that the performances in question provide prima facie warrant for attributions of mental properties that considerations of consciousness are insufficient to override. (shrink)

Human oversight has become a key mechanism for the governance of artificial intelligence (“AI”). Human overseers are supposed to increase the accuracy and safety of AI systems, uphold human values, and build trust in the technology. Empirical research suggests, however, that humans are not reliable in fulfilling their oversight tasks. They may be lacking in competence or be harmfully incentivised. This creates a challenge for human oversight to be effective. In addressing this challenge, this article aims to make three contributions. (...) First, it surveys the emerging laws of oversight, most importantly the European Union’s Artificial Intelligence Act (“AIA”). It will be shown that while the AIA is concerned with the competence of human overseers, it does not provide much guidance on how to achieve effective oversight and leaves oversight obligations for AI developers underdefined. Second, this article presents a novel taxonomy of human oversight roles, differentiated along whether human intervention is constitutive to, or corrective of a decision made or supported by an AI. The taxonomy allows to propose suggestions for improving effectiveness tailored to the type of oversight in question. Third, drawing on scholarship within democratic theory, this article formulates six normative principles which institutionalise distrust in human oversight of AI. The institutionalisation of distrust has historically been practised in democratic governance. Applied for the first time to AI governance, the principles anticipate the fallibility of human overseers and seek to mitigate them at the level of institutional design. They aim to directly increase the trustworthiness of human oversight and to indirectly inspire well-placed trust in AI governance. (shrink)

This paper describes a study of the effects of two acts of social intelligence, namely mimicry and social praise, when used by an artificial social agent. An experiment ( N = 50) is described which shows that social praise—positive feedback about the ongoing conversation—increases the perceived friendliness of a chat-robot. Mimicry—displaying matching behavior—enhances the perceived intelligence of the robot. We advice designers to incorporate both mimicry and social praise when their system needs to function as a social actor. Different ways (...) of implementing mimicry and praise by artificial social actors in an ambient persuasive scenario are discussed. (shrink)

By introducing the concept of “mental data,” Palermos (2023) highlights an underappreciated aspect of data ethics that policymakers would do well to heed. Sweeping artificial intelligence (AI) legi...

In a paper that recently appeared in this journal, we proposed a model that aims at providing a comprehensive account of our ability to intelligently use tools, bridging sensorimotor and reasoning-based explanations of this ability. Central to our model is the notion of generalized motor programs for tool use, which we defined as a synthesis between classic motor programs, as described in the scientific literature, and Peircean habits. In his commentary, Osiurak proposes a critique of the notion of generalized motor (...) program, and suggests that the limitations of our model can be solved by integrating it with the view that motor programs are generated by a previous mechanical reasoning, independent from sensorimotor knowledge. Here we reply that while on the one hand our reference to Peircean habits gets over the temptation to consider motor programs as fixed internal entities, it also rejects the view, endorsed by Osiurak, that intelligent practice is a mixture of antecedent abstract reasoning and subsequent motor execution. (shrink)

The EU Artificial Intelligence Act (AIA) defines four risk categories for AI systems: unacceptable, high, limited, and minimal. However, it lacks a clear methodology for the assessment of these risks in concrete situations. Risks are broadly categorized based on the application areas of AI systems and ambiguous risk factors. This paper suggests a methodology for assessing AI risk magnitudes, focusing on the construction of real-world risk scenarios. To this scope, we propose to integrate the AIA with a framework developed by (...) the Intergovernmental Panel on Climate Change (IPCC) reports and related literature. This approach enables a nuanced analysis of AI risk by exploring the interplay between (a) risk determinants, (b) individual drivers of determinants, and (c) multiple risk types. We further refine the proposed methodology by applying a proportionality test to balance the competing values involved in AI risk assessment. Finally, we present three uses of this approach under the AIA: to implement the Regulation, to assess the significance of risks, and to develop internal risk management systems for AI deployers. (shrink)

The world of artificial intelligence appears to be in rapid transition, and claims that artificial general intelligence is impossible are competing with concerns that we may soon be seeing Artificial Godlike Intelligence and that we should be very afraid of this prospect. This article discusses the issues from a psychological and social perspective and suggests that with the advent of Generative Artificial Intelligence, something that looks to humans like Artificial General Intelligence has become a distinct possibility as is the idea (...) of making it semi-autonomous: not just responding to discrete external inputs or performing specific tasks but able to prompt itself to create an ongoing stream of cognition that can possess something akin to a ‘purpose’. Add to that the ability of computers to be connected in vast networks, and we can envisage intelligences with staggering amounts of knowledge and reasoning capability, engaging with humans to anticipate and grant wishes. Such Semi-Autonomous Godlike Artificial Intelligences (SAGAIs—meaning ‘engagements’ in Hindi) could end up like Kali, wreaking death and destruction on our species or like Thor, acting as a saviour and protector of humanity. Which of these our SAGAIs most resemble could depend on whose wishes it is designed to serve: a rich oligarchy seeking ever greater wealth and power whatever the cost to others, or a populace that has compassion for each other and for life on the planet. (shrink)

Artificial intelligence research and regulation seek to balance the benefits of innovation against any potential harms and disruption. However, one unintended consequence of the recent surge in AI research is the potential re-orientation of AI technologies to facilitate criminal acts, term in this article AI-Crime. AIC is theoretically feasible thanks to published experiments in automating fraud targeted at social media users, as well as demonstrations of AI-driven manipulation of simulated markets. However, because AIC is still a relatively young and inherently (...) interdisciplinary area—spanning socio-legal studies to formal science—there is little certainty of what an AIC future might look like. This article offers the first systematic, interdisciplinary literature analysis of the foreseeable threats of AIC, providing ethicists, policy-makers, and law enforcement organisations with a synthesis of the current problems, and a possible solution space. (shrink)

Droit et complexité. Le rapprochement de ces deux mots pourrait passer pour incongru. L'idéal du droit ne tend-il pas, en effet, à la rigueur et à la clarté garantes de certitudes et d'efficacité? Cet ouvrage, tiré des travaux du colloque tenu à Brest en mars 2006 a pris un parti inverse en faisant le choix, d'une certaine façon pascalien, de dialoguer avec l'incertitude dans des échanges très ouverts qui ont confirmé l'ampleur du changement de perspectives sur le droit. Un changement (...) que traduit bien le vocabulaire : régulation, pluralisation des ordres normatifs, dissémination dans des réseaux, internormativité, droit de coordination, procéduralisation, ajustement, négociation, expérimentation, flexibilité d'un droit devenu " droit souple ", voire " droit soluble "... Le système semble s'être converti à la modestie en perdant non de sa massivité comme l'a récemment souligné le Conseil d'Etat, mais en perdant de sa monumentalité pyramidale intimidante au profit d'un plasma de normes de plus en plus imbriquées dans des rapports de complémentarité, de négociation, de synergie déployés dans la dimension horizontale. La frontière entre les différentes catégories de normes persiste certes, mais elle se brouille, vire au " flou ". Si bien que là où prévalaient des distinctions nettes et des normes chimiquement pures, stables, s'imposent désormais des alliages, des rapports d'interdépendance analogues aux fils de trame d'un tissu. Edgar Morin aime à rappeler que le mot complexe signifie " tisser ensemble " et il définit la complexité comme " un tissu [...] de constituants hétérogènes inséparablement associés ". (shrink)

Artificial Intelligence research and regulation seek to balance the benefits of innovation against any potential harms and disruption. However, one unintended consequence of the recent surge in AI research is the potential re-orientation of AI technologies to facilitate criminal acts, term in this chapter AI-Crime. AIC is theoretically feasible thanks to published experiments in automating fraud targeted at social media users, as well as demonstrations of AI-driven manipulation of simulated markets. However, because AIC is still a relatively young and inherently (...) interdisciplinary area—spanning socio-legal studies to formal science—there is little certainty of what an AIC future might look like. This chapter offers the first systematic, interdisciplinary literature analysis of the foreseeable threats of AIC, providing ethicists, policy-makers, and law enforcement organisations with a synthesis of the current problems, and a possible solution space. (shrink)

Speech acts are a staple of everyday communicative life, but only became a topic of sustained investigation, at least in the English-speaking world, in the middle of the Twentieth Century.[1] Since that time “speech act theory” has been influential not only within philosophy, but also in linguistics, psychology, legal theory, artificial intelligence, literary theory and many other scholarly disciplines.[2] Recognition of the importance of speech acts has illuminated the ability of language to do other things than describe reality. In the (...) process the boundaries among the philosophy of language, the philosophy of action, the philosophy of mind and even ethics have become less sharp. In addition, an appreciation of speech acts has helped lay bare an implicit normative structure within linguistic practice, including even that part of this practice concerned with describing reality. Much recent research aims at an accurate characterization of this normative structure underlying linguistic practice. (shrink)

Departing from popular imaginations around artificial intelligence (AI), this article engages in the I in the AI acronym but from perspectives outside of mathematics, computer science and machine learning. When intelligence is attended to here, it most often refers to narrow calculating tasks. This connotation to calculation provides AI an image of scientificity and objectivity, particularly attractive in societies with a pervasive desire for numbers. However, as is increasingly apparent today, when employed in more general areas of our messy socio-cultural (...) realities, AI- powered automated systems often fail or have unintended consequences. This article will contribute to this critique of AI by attending to Nicholas of Cusa and his treatment of intelligence. According to him, intelligence is equally dependent on an ability to handle the unknown as it unfolds in the present moment. This suggests that intelligence is organic which ties Cusa to more contemporary discussions in tech philosophy, neurology, evolutionary biology, and cognitive sciences in which it is argued that intelligence is dependent on having—and acting through—an organic body. Understanding intelligence as organic thus suggests an oxymoronic relationship to artificial. (shrink)

Traditionally, most of the research on occupational burnout has focused on organizational stressors, such as workload and time pressure, and has overlooked the emotional nature of customer service work and its effect on burnout. This study was designed to examine the effects of individuals’ affective traits and affective states on burnout. The main hypothesis of this study was that emotional intelligence acts as a moderator in the relationship between negative emotions felt by employees during their interactions with clients and emotional (...) exhaustion. A total of 137 service sector employees rated the extent to which they felt four positive emotions and four negative emotions while interacting with clients. The results indicated that negative affectivity was significantly associated with higher levels of emotional exhaustion, whereas high positive affectivity showed the reverse pattern. It was also observed that employees who declared greater intensity of negative emotions reported more symptoms of emotional exhaustion. However, as predicted, this effect was observed only among employees who were low in the trait of emotional intelligence. Negative emotions and emotional exhaustion were unrelated among employees who were high in trait emotional intelligence. (shrink)

Regulation is nothing without enforcement. This particularly holds for the dynamic field of emerging technologies. Hence, this article has two ambitions. First, it explains how the EU´s new Artificial Intelligence Act (AIA) will be implemented and enforced by various institutional bodies, thus clarifying the governance framework of the AIA. Second, it proposes a normative model of governance, providing recommendations to ensure uniform and coordinated execution of the AIA and the fulfilment of the legislation. Taken together, the article explores how the (...) AIA may be implemented by national and EU institutional bodies, encompassing longstanding bodies, such as the European Commission, and those newly established under the AIA, such as the AI Office. It investigates their roles across supranational and national levels, emphasizing how EU regulations influence institutional structures and operations. These regulations may not only directly dictate the structural design of institutions but also indirectly request administrative capacities needed to enforce the AIA. (shrink)

The EU proposal for the Artificial Intelligence Act (AIA) defines four risk categories: unacceptable, high, limited, and minimal. However, as these categories statically depend on broad fields of application of AI, the risk magnitude may be wrongly estimated, and the AIA may not be enforced effectively. This problem is particularly challenging when it comes to regulating general-purpose AI (GPAI), which has versatile and often unpredictable applications. Recent amendments to the compromise text, though introducing context-specific assessments, remain insufficient. To address this, (...) we propose applying the risk categories to specific AI scenarios, rather than solely to fields of application, using a risk assessment model that integrates the AIA with the risk approach arising from the Intergovernmental Panel on Climate Change (IPCC) and related literature. This model enables the estimation of the magnitude of AI risk by considering the interaction between (a) risk determinants, (b) individual drivers of determinants, and (c) multiple risk types. We use large language models (LLMs) as an example. (shrink)

In 2021, 193 Member States at UNESCO’s General Conference adopted the Recommendation on the Ethics of Artificial Intelligence as the first important step towards a future global standard-setting instrument on the subject. The text reflects an emerging consensus among the international community about the growing ethical concerns with artificial intelligence (AI). Among these concerns are also serious risks and dangers attributed to the manipulative effects of AI, which can be further exacerbated by the creative combination of AI with other innovative (...) technologies or applications, such as brain–computer interfaces (BCIs), functional magnetic resonance imaging (fMRI), robotics, and big data. The risks for individuals and society as a whole caused by manipulation through AI are already well known and have recently also been addressed by the European Union having released a proposal for an Artificial Intelligence Act (AIA). Among multiple risks related to AI, the AIA singles out the specific dangers related to AI systems that deploy “subliminal techniques beyond a person’s consciousness to materially distort a person’s behaviour in a manner that causes or is likely to cause that person or another person physical or psychological harm”. The present article thus aims to highlight the known and potential dangers related to AI systems manipulating human thoughts and behaviour through subliminal and supraliminal means and methods. To this end, it advocates the joint study of law and the senses captured by the concept of legal synaesthesia to correspond to the need for an interdisciplinary debate covering the complexity of the links between AI, related technologies, human perception based on the senses and the mind, as well as the role and instruments of law in the future organization of societies in this world. (shrink)

What kind of activity are non-human animals capable of? A venerable tradition insists that lack of language confines them to ‘mere behaviour’. This article engages with this ‘lingualism’ by developing a positive, bottom-up case for the possibility of animal agency. Higher animals cannot just act, they can act intelligently, rationally, intentionally and for reasons. In developing this case I draw on the interplay of behaviour, cognition and conation, the unduly neglected notion of intelligence and its connection to rationality, the need (...) to recognize that reasons are objective conditions, and the difference between the ability to act for reasons and the capacity to reflect on reasons. (shrink)

Intelligent Transportation Systems are expected to automate how parking slots are booked by trucks. The intrinsic dynamic nature of this problem, the need of explanations and the inclusion of private data justify an agent-based solution. Agents solving this problem act with a Believe Desire Intentions reasoning, and are implemented with JASON. Privacy of trucks becomes protected sharing a list of parkings ordered by preference. Furthermore, the process of assigning parking slots takes into account legal requirements on breaks and driving time (...) limits. Finally, the agent simulations use the distances, the number of trucks and parkings corresponding to the proportions of the current European Union data. The performance of the proposed solution is tested in these simulations with three different distances against an alternative with complete knowledge. The difference in efficiency, the number of illegal breaks and the traveled distances are measured in them. Comparing the results, we can conclude that the nonprivate alternative is slightly better in performance while both alternatives do not produce illegal breaks. In this way the simulations show that the proposed privacy protection does not impose a relevant handicap in efficiency. (shrink)

Accountability is a cornerstone of the governance of artificial intelligence (AI). However, it is often defined too imprecisely because its multifaceted nature and the sociotechnical structure of AI systems imply a variety of values, practices, and measures to which accountability in AI can refer. We address this lack of clarity by defining accountability in terms of answerability, identifying three conditions of possibility (authority recognition, interrogation, and limitation of power), and an architecture of seven features (context, range, agent, forum, standards, process, (...) and implications). We analyse this architecture through four accountability goals (compliance, report, oversight, and enforcement). We argue that these goals are often complementary and that policy-makers emphasise or prioritise some over others depending on the proactive or reactive use of accountability and the missions of AI governance. (shrink)

In this article the central philosophical issues concerning human-level artificial intelligence (AI) are presented. AI largely changed direction in the 1980s and 1990s, concentrating on building domain-specific systems and on sub-goals such as self-organization, self-repair, and reliability. Computer scientists aimed to construct intelligence amplifiers for human beings, rather than imitation humans. Turing based his test on a computer-imitates-human game, describing three versions of this game in 1948, 1950, and 1952. The famous version appears in a 1950 article in Mind, ‘Computing (...) Machinery and Intelligence’ (Turing 1950). The interpretation of Turing's test is that it provides an operational definition of intelligence (or thinking) in machines, in terms of behavior. ‘Intelligent Machinery’ sets out the thesis that whether an entity is intelligent is determined in part by our responses to the entity's behavior. Wittgenstein frequently employed the idea of a human being acting like a reliable machine. A ‘living reading-machine’ is a human being or other creature that is given written signs, for example Chinese characters, arithmetical symbols, logical symbols, or musical notation, and who produces text spoken aloud, solutions to arithmetical problems, and proofs of logical theorems. Wittgenstein mentions that an entity that manipulates symbols genuinely reads only if he or she has a particular history, involving learning and training, and participates in a social environment that includes normative constraints and further uses of the symbols. (shrink)

In the debate on whether to ban LAWS, moral arguments are mainly used. One of these arguments, proposed by Sparrow, is that the use of LAWS goes hand in hand with the responsibility gap. Together with the premise that the ability to hold someone responsible is a necessary condition for the admissibility of an act, Sparrow believes that this leads to the conclusion that LAWS should be prohibited. In this article, it will be shown that Sparrow’s argumentation for both premises (...) is not convincing. If one interprets the thesis that responsibility (first premise) is necessary in a descriptive sense, this assertion clashes with military theory and practice. And even if you focus on the normative interpretation, that claim does not stand. The second premise for Sparrow’s conclusion, namely that you cannot hold anyone responsible for LAWS’ (mis)deeds, is based on the idea that control is a necessary condition for responsibility. It will be shown that this idea too is not correct, which means that Sparrow’s control argument does not do the work it should do. From this, we can conclude that Sparrow’s justification for his claim that LAWS should be banned is insufficient, and neither can we conclude that the thesis of a responsibility gap has in any case been undermined. However, it will also be argued that someone may be responsible for the actions of LAWS, or that it cannot be excluded that one can be held responsible. (shrink)

In emphasising improvement, smooth coping and success over variability and regression, skill theory has overlooked the processes performers at all levels develop and rely on for managing bodily and affective fluctuations, and their impact on skilled performance. I argue that responding to the instability and variability of unique bodily capacities is a vital feature of skilled action processes. I suggest that embodied intelligence – a term I use to describe a set of abilities to perceptively interpret and make use of (...) information from body, mind, environment and task requirements, and to modulate one’s focus, awareness and action strategies accordingly – is critical for performing well-learned skills in vulnerable situations. It is critical for staying safe. To investigate these components of skilled action, I employ a cognitive ethnographic method, combined with apprenticeship on the static trapeze, to produce two ‘experience near’ case studies. These document in-situ experiences of awareness, self-regulation and embodied intelligence. Both reveal strong connections between a reflective awareness of bodily vulnerability and variability, and self-regulatory processes – specifically, the down- and up-regulation of anxiety. I then reflect on these case studies in relation to a prospective sense of agency, the awareness of control acts that may lead to performance outcomes. With increased clarity on these features of embodied intelligence and attention during action, other researchers can build on this study to further probe and map the maintenance and functions of embodied intelligence in dealing with the instability of skills. (shrink)

We consider the Search for ExtraTerrestrial Intelligence (SETI) activities from a bioethical standpoint. In particular, we argue that there is a moral duty to search for other intelligent beings in the Universe. Some of them could – and are likely to be – morally enhanced in the sense that they are not only capable of unmistakable moral reasoning but are also capable of consistently acting upon the results of such deliberations. Even if the probability of finding such morally superior beings (...) is small, it is higher than zero in any case; in fact, our astrobiological knowledge suggests that this probability is significant. Hence, there are both deductive and inductive arguments for the proposition that our duty is to search for such morally superior extraterrestrial beings. In other words, there is a duty to undertake and support our SETI efforts. The argument to that effect runs parallel to some of the arguments deployed in current debates on human moral enhancement. (shrink)

""Catching Ourselves in the Act" is no less than an attempt to explain intelligence. Delightful how the author dismantles traditional views in.

Could an artificial intelligence become a legal person? As of today, this question is only theoretical. No existing computer program currently possesses the sort of capacities that would justify serious judicial inquiry into the question of legal personhood. The question is nonetheless of some interest. Cognitive science begins with the assumption that the nature of human intelligence is computational, and therefore, that the human mind can, in principle, be modelled as a program that runs on a computer. Artificial intelligence (AI) (...) research attempts to develop such models. But even as cognitive science has displaced behavioralism as the dominant paradigm for investigating the human mind, fundamental questions about the very possibility of artificial intelligence continue to be debated. This Essay explores those questions through a series of thought experiments that transform the theoretical question whether artificial intelligence is possible into legal questions such as, "Could an artificial intelligence serve as a trustee?" What is the relevance of these legal thought experiments for the debate over the possibility of artificial intelligence? A preliminary answer to this question has two parts. First, putting the AI debate in a concrete legal context acts as a pragmatic Occam's razor. By reexamining positions taken in cognitive science or the philosophy of artificial intelligence as legal arguments, we are forced to see them anew in a relentlessly pragmatic context. Philosophical claims that no program running on a digital computer could really be intelligent are put into a context that requires us to take a hard look at just what practical importance the missing reality could have for the way we speak and conduct our affairs. In other words, the legal context provides a way to ask for the "cash value" of the arguments. The hypothesis developed in this Essay is that only some of the claims made in the debate over the possibility of AI do make a pragmatic difference, and it is pragmatic differences that ought to be decisive. Second, and more controversially, we can view the legal system as a repository of knowledge-a formal accumulation of practical judgments. The law embodies core insights about the way the world works and how we evaluate it. Moreover, in common-law systems judges strive to decide particular cases in a way that best fits the legal landscape-the prior cases, the statutory law, and the constitution. Hence, transforming the abstract debate over the possibility of AI into an imagined hard case forces us to check our intuitions and arguments against the assumptions that underlie social decisions made in many other contexts. By using a thought experiment that explicitly focuses on wide coherence, we increase the chance that the positions we eventually adopt will be in reflective equilibrium with our views about related matters. In addition, the law embodies practical knowledge in a form that is subject to public examination and discussion. Legal materials are published and subject to widespread public scrutiny and discussion. Some of the insights gleaned in the law may clarify our approach to the artificial intelligence debate. (shrink)

With wit and intelligence, Leo Katz seeks to understand the basic rules and concepts underlying the moral, linguistic, and psychological puzzles that plague the criminal law. "_Bad Acts and Guilty Minds_... revives the mind, it challenges superficial analyses, it reminds us that underlying the vast body of statutory and case law, there is a rationale founded in basic notions of fairness and reason.... It will help lawyers to better serve their clients and the society that permits attorneys to hang out (...) their shingles."—Edward N. Costikyan, _New York Times Book Review_. (shrink)

This paper explores aspects of GPT-3 that have been discussed as harbingers of artificial general intelligence and, in particular, linguistic intelligence. After introducing key features of GPT-3 and assessing its performance in the light of the conversational standards set by Alan Turing in his seminal paper from 1950, the paper elucidates the difference between clever automation and genuine linguistic intelligence. A central theme of this discussion on genuine conversational intelligence is that members of a linguistic community never merely respond “algorithmically” (...) to queries through a selective kind of pattern recognition, because they must also jointly attend and act with other speakers in order to count as genuinely intelligent and trustworthy. This presents a challenge for systems like GPT-3, because representing the world in a way that makes conversational common ground salient is an essentially collective task that we can only achieve jointly with other speakers. Thus, the main difficulty for any artificially intelligent model of conversation is to account for the communicational intentions and motivations of a speaker through joint attention. These joint motivations and intentions seem to be completely absent from the standard way in which systems like GPT-3 and other artificial intelligent systems work. This is not merely a theoretical issue. Since GPT-3 and future iterations of similar systems will likely be available for commercial use through application programming interfaces, caution is needed regarding the risks created by these systems, which pass for “intelligent” but have no genuine communicational intentions, and can thereby produce fake and unreliable linguistic exchanges. (shrink)

As artificial intelligence (AI) thrives and propagates through modern life, a key question to ask is how to include humans in future AI? Despite human involvement at every stage of the production process from conception and design through to implementation, modern AI is still often criticized for its “black box” characteristics. Sometimes, we do not know what really goes on inside or how and why certain conclusions are met. Future AI will face many dilemmas and ethical issues unforeseen by their (...) creators beyond those commonly discussed (e.g., trolley problems and variants of it) and to which solutions cannot be hard-coded and are often still up for debate. Given the sensitivity of such social and ethical dilemmas and the implications of these for human society at large, when and if our AI make the “wrong” choice we need to understand how they got there in order to make corrections and prevent recurrences. This is particularly true in situations where human livelihoods are at stake (e.g., health, well-being, finance, law) or when major individual or household decisions are taken. Doing so requires opening up the “black box” of AI; especially as they act, interact, and adapt in a human world and how they interact with other AI in this world. In this article, we argue for the application of cognitive architectures for ethical AI. In particular, for their potential contributions to AI transparency, explainability, and accountability. We need to understand how our AI get to the solutions they do, and we should seek to do this on a deeper level in terms of the machine-equivalents of motivations, attitudes, values, and so on. The path to future AI is long and winding but it could arrive faster than we think. In order to harness the positive potential outcomes of AI for humans and society (and avoid the negatives), we need to understand AI more fully in the first place and we expect this will simultaneously contribute towards greater understanding of their human counterparts also. (shrink)

Descendre acheter le journal? Réflexion : vous délibérez, construisez un projet, argumentez. Décision prise, la volonté vous met debout. Alors, dès le premier pas, l'acte vient à la rencontre de l'action-projet qui agrégeait dans votre tête réflexion, délibération, argumentation, décision, volonté. L'acte est une aventure. Toute la réalité imprévisible du monde se trouvait là, en réserve, dont les créations intellectuelles de l'action escamotaient la part d'inconnu. On décide une action, c'est l'acte qu'on rencontre. Mais alors, pourquoi les deux mots sont-ils (...) communément employés l'un pour l'autre, obligeant à penser l'acte dans une réduction à l'action " dans la tête "? Tel est le sujet de ce livre magistral de Gérard Mendel qui prend la suite de La psychanalyse revisitée (1988) et La société n'est pas une famille (1992). A partir d'une lecture critique de l'œuvre des grands philosophes, d'Aristote à Habermas, en passant par Saint Augustin, Descartes ou Nietzsche, Gérard Mendel montre comment la naissance philosophique de l'être il y a vingt-cinq siècles a chassé l'acte de la réflexion intellectuelle. En s'appuyant sur une étude approfondie de l' " intelligence pratique " nourrie de son expérience de terrain sur le champ social et sur la relecture des travaux fondamentaux de Winnicott, il propose une nouvelle approche théorique du sujet et de l'acte. Loin du fantasme occidental d'une domination absolue de l'esprit sur la nature et la société, s'affirme alors l'idée d'un acte, pouvoir individuel et collectif en quête d'un rapport plus harmonieux avec la réalité qui, parce qu'elle résiste continûment, reste toujours aussi blessante pour le narcissisme humain. Cette réflexion passionnante, d'une écriture toujours claire, intéressera tous ceux qui ne se satisfont pas de la césure entre théorie et pratique dans la compréhension de l'activité humaine : psychanalystes, psychologues et philosophes, bien sûr, mais aussi travailleurs sociaux et sociologues. (shrink)

The primary units of meaning in the use and comprehension of language are speech acts of the type called illocutionary acts. In Foundations of Illocutionary Logic John Searle and Daniel Vanderveken presented the first formalized logic of a general theory of speech acts. In Meaning and Speech Acts Daniel Vanderveken further develops the logic of speech acts and the logic of propositions to construct a general semantic theory of natural languages. Volume I, Principles of Language Use, explains the general principles (...) that connect meaning, reason, thought and speech acts in the semantic structure of language. It presupposes no detailed knowledge of logical formalism, and will be accessible to a large readership of students and scholars from philosophy, lingustics, cognitive psychology and computer science. Volume II, Formal Semantics of Success and Satisfaction uses the resources of philosophical and mathematical logics to develop a formalization of the laws of the semantic theory advanced in Volume I. It will be of interest to theoretical linguists and those involved in mathematical logic and artificial intelligence. (shrink)

Machine-based automation has long been a key factor in the modern era. However, lately, many people have been shocked by artificial intelligence (AI) applications, such as ChatGPT (OpenAI), that can perform tasks previously thought to be human-exclusive. With recent advances in natural language processing (NLP) technologies, AI can generate written content that is similar to human-made products, and this ability has a variety of applications. As the technology of large language models continues to progress by making use of colossal reservoirs (...) of digital information, AI is becoming more capable of recognizing patterns and associations within given contexts, making it especially helpful in assisting with various professional writing tasks [1]. In this paper, we will discuss several key points regarding the current state and future of AI in academia. Furthermore, since in certain aspects, acts can speak louder than words, we will also present some of our hands-on experiences of working with ChatGPT. (shrink)

Studies investigating the COVID-19 pandemic from a psychological point of view have mostly focused on psychological distress. This study adopts the framework of existential positive psychology, a second wave of positive psychology that emphasizes the importance of effective coping with the negative aspects of living in order to achieve greater wellbeing. Trait emotional intelligence (trait EI) can be crucial in this context as it refers to emotion-related personality dispositions concerning the understanding and regulation of one’s emotions and those of others. (...) The present study investigated the relationship between trait EI and both wellbeing and psychological distress (i.e., depression, anxiety, and stress), while exploring the mediating role of meaning-centered coping (proactive transformative strategies based on meaning in life) and maladaptive coping (i.e., behavioral disengagement and self-blame) during the first few months of the COVID-19 pandemic. A sample of 326 Lebanese adults completed measures of trait EI, wellbeing, psychological distress, coping, and meaning-centered coping. Results showed a strong positive correlation between trait EI and meaning-centered coping. Trait EI also correlated positively with wellbeing and negatively with psychological distress. Structural equation modeling showed that meaning-centered coping partially mediated the relationship between trait EI and wellbeing. Maladaptive coping fully mediated the relationship between trait EI and psychological distress. Findings indicate that trait EI is positively related to dealing with a stressful situation such as the pandemic in positive ways at both the cognitive level, by reformulating the situation to see something valuable in it, and behavioral level, by being proactive about it. Trait EI was positively linked to seeing the situation as an opportunity for personal growth, finding personal meaning in this situation, maintaining an attitude of hope and courage, and acting more responsibly with one’s self and others during the current crisis. In turn, this coping formula was related to lower psychological distress and improved mental health. These results are consistent with the existential positive psychology framework and can inform implementation programs and policies aiming at raising awareness and promoting healthy and successful coping during the pandemic. (shrink)

Reveals how we can each reconnect to collective intelligence and return our world to wholeness, balance, and sanity • Explains how collective intelligence manifests in flocks of birds, instantaneous knowing in indigenous peoples, and the power of sacred places • Offers ways for us to reconnect to the infinite source of wisdom that fuels collective intelligence and underscores the importance of ceremony, pilgrimage, and initiation • Draws on recent findings in New Paradigm science, traditional teachings from indigenous groups from North, (...) South, and Central America and Siberia, as well as sacred geometry, deep ecology, and expanded states of consciousness For our ancestors, collective intelligence was a normal part of life. We see it today as the mysterious force that enables flocks of birds, swarms of bees, and schools of fish to function together in perfect synchrony, communicating and cooperating at some undetectable level. At its most subtle, it’s an instantaneous knowing, shared by members of a group, of the wisest course of action that will benefit all. As Dery Dyer reveals, collective intelligence still resides within each of us, and it is the key to restoring balance and harmony to our world. She shows how it occurs spontaneously when individuals who share a need and a purpose instinctively “self-organize” into a group and function with no leader or central authority. Such groups exhibit abilities much greater than what any of their members possess individually--or what can be replicated with artificial intelligence. Dyer explains, due to an unquestioning dependence on technology, modern humanity has forgotten how to connect with collective intelligence and fallen into collective stupidity, otherwise known as mob mind or groupthink, which is now endangering the interconnected web of life on Earth. Drawing on recent findings in New Paradigm science, traditional teachings from indigenous groups, as well as sacred geometry, deep ecology, and expanded states of consciousness, the author shows how the ability to think and act collectively for the highest good is hardwired in all living beings. She explains how to release ourselves from enslavement by technology and use it more wisely toward the betterment of all life. Underscoring the vital importance of ceremony, pilgrimage, and initiation, she offers ways for us to reconnect to the infinite source of wisdom that fuels collective intelligence and which manifests everywhere in the natural world. Revealing that once we relearn how to hear the Earth, we can heal the Earth, Dyer shows how each of us has a vital role to play in restoring our world to wholeness. (shrink)

When interacting with other people, we assume that they have their reasons for what they do and believe, and experience recognizable feelings and emotions. When people act from weakness of will or are otherwise irrational, what they do can still be comprehensible to us, since we know what it is like to fall for temptation and act against one’s better judgment. Still, when someone’s experiences, feelings and way of thinking is vastly different from our own, understanding them becomes increasingly difficult. (...) Delusions and psychosis are often seen as marking the end of intelligibility. In this paper, I argue first for the importance of seeing other people as intelligible as long as this is at all possible. Second, I argue, based on both previous literature and my own lived experience, that more psychotic phenomena than previously thought can be rendered at least somewhat intelligible. Besides bizarre experiences like illusions, hallucinations and intense feelings of significance, I also explain what it is like to lose one’s bedrock, and how this loss impacts which beliefs one has reason to reject. Finally, I give an inside account of some disturbances of reason, and show that there are important similarities between certain psychotic reasoning problems and common non-pathological phenomena. (shrink)

Over the past five decades, I have been developing a distinctive view of free will according to which it requires that agents be to some degree ultimately responsible for the formation of their own wills. To act ‘of one's own free will’ in this sense is to act ‘from a will’ that is to some extent ‘of one's own free making’. A free will of this ultimate kind has been under attack in the modern era as obscure and unintelligible. In (...) this paper, I discuss the arguments for such a view and compare it to other contemporary views of free will and action. I then address criticisms that such a non‐determinist free will cannot be made intelligible or reconciled with modern science, does not allow sufficient agent control, reduces to mere chance or luck or randomness, leads to various regresses, or fails to account for moral responsibility, among other criticisms. (shrink)

I argue that intending and acting belong to the same genus: intending is a kind of doing continuous in structure with intentional acting. Future-directed intending is not a truly separate phenomenon from either the intending in action or the acting itself. Ultimately, all intentions are in action, or better still, in extended courses of action. I show how the intuitive distinction between intending and acting is based on modeling the two phenomena on the extreme and limiting cases of an otherwise (...) continuous spectrum of the ways in which agents exercise rational active intelligent guidance in the pursuit of goals. I argue that diachronic intentional agency is better understood in terms of continuity and unity of courses of active and intelligent guidance, and that the distinction between intending to do something and doing it is only a derivative and context-dependent segmentation of these continuous courses of rational active intelligent guidance. (shrink)

Wittgenstein’s Private Language Argument holds that language requires rule-following, rule following requires the possibility of error, error is precluded in pure introspection, and inner mental life is known only by pure introspection, thus language cannot exist entirely within inner mental life. Fodor defends his Language of Thought program against the Private Language Argument with a dilemma: either privacy is so narrow that internal mental life can be known outside of introspection, or so broad that computer language serves as a counter-example. (...) I suggest that the developing field of artificial intelligence (deep learning neural networks) tends to vitiate Fodor’s defense and hence vindicate the Private Language Argument. The first horn of Fodor’s dilemma requires language to encompass genuinely internal mental life, i.e. non-projected intentional states, which are not exhibited in classical machine learning but only by deep learning neural networks (artificial intelligence). Such networks act as black boxes, however, whose state cannot be understood by tracking the changes in their supervenience bases without shared context, and that shared context introduces the possibility of error. The language of artificial intelligence is not private. (shrink)

We informally discuss some recent results on the incompleteness of formal systems. These theorems, which are of great importance to contemporary mathematical epistemology, are proved using a variety of conceptual tools provably stronger than those of finitary axiomatisations. Those tools require no mathematical ontology, but rather constitute particularly concrete human constructions and acts of comprehending infinity and space rooted in different forms of knowledge. We shall also discuss, albeit very briefly, the mathematical intelligence both of God and of computers. We (...) hope in this manner to help the reader overcome formalist reductionism, while avoiding naive Platonist ontologies, typical symptoms of Godelitis which affected many in the last seventy years. (shrink)

Bringing together literary scholars, computer scientists, ethicists, philosophers of mind, and scholars from affiliated disciplines, this collection of essays offers important and timely insights into the pasts, presents, and, above all, possible futures of Artificial Intelligence. This book covers topics such as ethics and morality, identity and selfhood, and broader issues about AI, addressing questions about the individual, social, and existential impacts of such technologies. Through the works of science fiction authors such as Isaac Asimov, Stanislaw Lem, Ann Leckie, Iain (...) M. Banks, and Martha Wells, alongside key visual productions such as Ex Machina, Westworld, and Her, contributions illustrate how science fiction might inform potential futures as well as acting as a springboard to bring disciplinary knowledge to bear on significant developments of Artificial Intelligence. Addressing a broad, interdisciplinary audience, both expert and non-expert readers gain an in-depth understanding of the wide range of pressing issues to which Artificial Intelligence gives rise, and the ways in which science fiction narratives have been used to represent them. Using science fiction in this manner enables readers to see how even fictional worlds and imagined futures have very real impacts on how we understand these technologies. As such, readers are introduced to theoretical positions on Artificial Intelligence through fictional works as well as encouraged to reflect on the diverse aspects of Artificial Intelligence through its many philosophical, social, legal, scientific, and cultural ramifications. (shrink)

This chapter introduces the idea that computation is a key tool that can help us understand how the human brain works. Recent years have seen a revolution in the kinds of tasks computers can perform. Underlying these advances is the burgeoning field of machine learning, a branch of artificial intelligence, which aims at creating machines that can act without being programmed, learning from data and experience. Rather startlingly, it turns out that the same methods that allow us to make intelligent (...) machines also appear to hold the key to explaining how our brains work. In this chapter, we explore this exciting new field and some of the questions that it raises. (shrink)