It is not uncommon for people to suffer identity crises. Yet, faced with similarly disruptive circumstances, some people plunge into an identity crisis while others do not. How must selfhood be construed given that people are vulnerable to identity crises? And how must agency be construed given that some people skirt potential identity crises and renegotiate the terms of their personal identity without losing their equilibrium -- their sense of self? If an adequate theory of the self and agency must (...) be able to account for this capacity to avert identity crises, I argue that it must include an account of agentic corporeity. After explaining what an identity crisis is, I examine Charles Taylor’s and David Velleman’s accounts of identity and agency and argue that their omission of agentic corporeity makes it impossible for them to convincingly account for the ability to avert an identity crisis. In the spirit of Merleau-Ponty’s account of the intentional arc and J. J. Gibson’s account of the relation between corporeity and affordances, I sketch an account of psychocorporeal practical intelligence that includes three main components – psychocorporeal insight, psychocorporeal values, and psychocorporeal versatility. I conclude by connecting my position to Aristotle’s views about practical understanding and by arguing that both Taylor and Velleman have reason to embrace my position. (shrink)

This chapter treats Hubert Dreyfus’ account of skilled coping as part of his wider project of demonstrating the sovereignty of practical intelligence over all other forms of intelligence. In contrast to the standard picture of human beings as essentially rational, individual agents, Dreyfus argued powerfully on phenomenological and empirical grounds that humans are fundamentally embedded, absorbed, and embodied. These commitments are present throughout Dreyfus’ philosophical writings, from his critique of Artificial Intelligence research in the 1970s and (...) 1980s to his rejection of John McDowell’s conceptualism in his 2005 APA Presidential Address. The present chapter articulates Dreyfus’ proposal for a contentless, non-mentalistic form of intentionality by contrasting his position with that of his U.C. Berkeley colleague John Searle and defending it as a plausible alternative to the so-called “Standard Story” of intentional action as the effect of an agent’s mental states. (shrink)

Legg and Hutter, as well as subsequent authors, considered intelligent agents through the lens of interaction with reward-giving environments, attempting to assign numeric intelligence measures to such agents, with the guiding principle that a more intelligent agent should gain higher rewards from environments in some aggregate sense. In this paper, we consider a related question: rather than measure numeric intelligence of one Legg- Hutter agent, how can we compare the relative intelligence of two Legg-Hutter agents? We propose (...) an elegant answer based on the following insight: we can view Legg-Hutter agents as candidates in an election, whose voters are environments, letting each environment vote (via its rewards) which agent (if either) is more intelligent. This leads to an abstract family of comparators simple enough that we can prove some structural theorems about them. It is an open question whether these structural theorems apply to more practical intelligence measures. (shrink)

The AI Robotics Ethics Society (AIRES) is a non-profit organization founded in 2018 by Aaron Hui to promote awareness and the importance of ethical implementation and regulation of AI. AIRES is now an organization with chapters at universities such as UCLA (Los Angeles), USC (University of Southern California), Caltech (California Institute of Technology), Stanford University, Cornell University, Brown University, and the Pontifical Catholic University of Rio Grande do Sul (Brazil). AIRES at PUCRS is the first international chapter of AIRES, and (...) as such, we are committed to promoting and enhancing the AIRES Mission. Our mission is to focus on educating the AI leaders of tomorrow in ethical principles to ensure that AI is created ethically and responsibly. As there are still few proposals for how we should implement ethical principles and normative guidelines in the practice of AI system development, the goal of this work is to try to bridge this gap between discourse and praxis. Between abstract principles and technical implementation. In this work, we seek to introduce the reader to the topic of AI Ethics and Safety. At the same time, we present several tools to help developers of intelligent systems develop "good" models. This work is a developing guide published in English and Portuguese. Contributions and suggestions are welcome. (shrink)

Can nonhuman animals and artificial intelligence (AI) entities be attributed moral agency? The general assumption in the philosophical literature is that moral agency applies exclusively to humans since they alone possess free will or capacities required for deliberate reflection. Consequently, only humans have been taken to be eligible for ascriptions of moral responsibility in terms of, for instance, blame or praise, moral criticism, or attributions of vice and virtue. Animals and machines may cause harm, but they cannot be appropriately (...) ascribed moral responsibility for their behavior. This thesis challenges the conventional paradigm by proposing an alternative approach where moral agency is conceived as the competence to participate in moral responsibility practices. By shifting focus from intra-individual to contextual and socially situated features, this practice-focused approach appears to make the attribution of moral agency to nonhuman animals and AI entities more plausible than commonly assumed. Moreover, considering the current and potential future prevalence of nonhuman animals and AI entities in everyday settings and social contexts, a potential extension of moral agency to such entities could very well transform our social, moral, and legal practices. Hence, this thesis proposes that the attribution or withholding of moral agency to different entities should be carefully evaluated, considering the potential normative implications. (shrink)

Artificial intelligence (AI) profoundly influences a number of societal structures today, including religious dynamics. Using Bernard Lonergan’s critical realism as a lens, this article investigates the intersections of AI and religious traditions in their shared pursuit of the common good. Beginning with Lonergan’s principle that humans construct their understanding through cognitive processes, we examine how AI-mediated realities align with or challenge traditional religious tenets. By delving into specific cases, we spotlight AI’s role in reshaping religious symbols, rituals, and even (...) creating novel spiritual meanings. Using Lonergan’s insights on the balance between subjectivity and objectivity, I analyze AI’s potential to both create new sacred spaces and challenge religious orthodoxy. The crux of the discussion centers on the negotiation between religious values and technological innovation, assessing how AI can bolster religious life while maintaining its core essence. Ultimately, this article underscores the importance of the common good in the age of AI-driven religious evolution. (shrink)

From artistic performances in the visual arts and in music to motor control in gymnastics, from tool use to chess and language, humans excel in a variety of skills. On the plausible assumption that skillful behavior is a visible manifestation of intelligence, a theory of intelligence—whether human or not—should be informed by a theory of skills. More controversial is the question as to whether, in order to theorize about intelligence, we should study certain skills in particular. My (...) target is the view that only a particular class/kind of skill (i.e., ‘theoretical’, or ‘intellectual’ skills, versus ‘practical’, or ‘embodied’ skills) manifests intelligence, or especially does so. I call this view ‘Intelligence Elitism’. Intelligence Elitism is pervasive in popular culture, in academic culture, as well as in psychometrics. It has, arguably, a long pedigree in philosophy (though explicit arguments for it are rare). But it is a substantive view which, if false, can promote unfairness. In this article, I defend Intelligence Socialism—the claim that intelligent behavior is everywhere skillful behavior is. I go on to isolate the best case for the further Elitist claim that, even if all skillful behavior is intelligent in some modest sense of ‘intelligence’, there is a principled difference in intelligence between theoretical, or intellectual, skills, on one side, and practical, or embodied skills, on the other, and I show it wanting. (shrink)

The article argues that AI can enhance the measurement and implementation of democratic processes within political parties, known as Intra-Party Democracy (IPD). It identifies the limitations of traditional methods for measuring IPD, which often rely on formal parameters, self-reported data, and tools like surveys. Such limitations lead to partial data collection, rare updates, and significant resource demands. To address these issues, the article suggests that specific data management and Machine Learning techniques, such as natural language processing and sentiment analysis, can (...) improve the measurement and practice of IPD. (shrink)

The present paper aims at contributing to the ethical debate on the impacts of artificial intelligence (AI) systems on human autonomy. More specifically, it intends to offer a clearer understanding of the design challenges to the effort of aligning driving automation technologies to this ethical value. After introducing the discussion on the ambiguous impacts that AI systems exert on human autonomy, the analysis zooms in on how the problem has been discussed in the literature on connected and automated vehicles (...) (CAVs). On this basis, it is claimed that the issue has been mainly tackled on a fairly general level, and mostly with reference to the controversial issue of crash-optimization algorithms, so that only limited design insights have been drawn. However, integrating ethical analysis and design practices is critical to pursue the implementation of such an important ethical value into CAV technologies. To this aim, it is argued, a more applied approach targeted at examining the impacts on human autonomy of current CAV functions should also be explored. As an example of the intricacy of this task, the case of automated route planning is discussed in some detail. (shrink)

The notion of computation has changed the world more than any previous expressions of knowledge. However, as know-how in its particular algorithmic embodiment, computation is closed to meaning. Therefore, computer-based data processing can only mimic life’s creative aspects, without being creative itself. AI’s current record of accomplishments shows that it automates tasks associated with intelligence, without being intelligent itself. Mistaking the abstract for the concrete has led to the religion of “everything is an output of computation”—even the humankind that (...) conceived the computer. The hypostatized role of computers explains the increased dependence on them. The convergence machine called deep learning is only the most recent form through which the deterministic theology of the machine claims more than what it actually is: extremely effective data processing. A proper understanding of complexity, as well as the need to distinguish between the reactive nature of the artificial and the anticipatory nature of the living are suggested as practical responses to the challenges posed by machine theology. (shrink)

My topic is the intelligent guidance of action. In this paper I offer an empirically grounded case for four ideas: that [a] cognitive processes of practical reasoning play a key role in the intelligent guidance of action, [b] these processes could not do so without significant enabling work done by both perception and the motor system, [c] the work done by perceptual and motor systems can be characterized as the generation of information specialized for action guidance, which in turn (...) suggests that [d] the cognitive processes of practical reasoning that play a key role in the guidance of intelligent action are not the abstract, syllogistic ones philosophers often treat as the paradigm of practical reasoning. Rather, these cognitive processes are constrained by, and work well with, the specialized concepts outputted by perception and the feedback outputted by sensorimotor processes. (shrink)

There is considerable enthusiasm about the prospect that artificial intelligence (AI) will help to improve the safety and efficacy of health services and the efficiency of health systems. To realize this potential, however, AI systems will have to overcome structural problems in the culture and practice of medicine and the organization of health systems that impact the data from which AI models are built, the environments into which they will be deployed, and the practices and incentives that structure their (...) development. This perspective elaborates on some of these structural challenges and provides recommendations to address potential shortcomings. (shrink)

Abstract: Artificial Intelligence (AI) is revolutionizing the agricultural sector by enhancing productivity and sustainability. This paper explores the transformative impact of AI technologies on agriculture, focusing on their applications in precision farming, predictive analytics, and automation. AI-driven tools enable more efficient management of crops and resources, leading to improved yields and reduced environmental impact. The paper examines key AI technologies, including machine learning algorithms for crop monitoring, robotics for automated planting and harvesting, and data analytics for optimizing resource use. (...) Additionally, it addresses challenges such as data privacy, technology adoption barriers, and the ethical implications of AI in farming. By integrating AI into agricultural practices, the industry can achieve greater efficiency and sustainability, paving the way for future advancements. (shrink)

Advanced AI systems are rapidly making their way into medical research and practice, and, arguably, it is only a matter of time before they will surpass human practitioners in terms of accuracy, reliability, and knowledge. If this is true, practitioners will have a prima facie epistemic and professional obligation to align their medical verdicts with those of advanced AI systems. However, in light of their complexity, these AI systems will often function as black boxes: the details of their contents, calculations, (...) and procedures cannot be meaningfully understood by human practitioners. When AI systems reach this level of complexity, we can also speak of black-box medicine. In this paper, we want to argue that black-box medicine conflicts with core ideals of patient-centered medicine. In particular, we claim, black-box medicine is not conducive for supporting informed decision-making based on shared information, shared deliberation, and shared mind between practitioner and patient. (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)

Abstract: This research paper explores the transformative impact of artificial intelligence (AI) on digital media, examining both the opportunities it presents and the challenges it poses. The integration of AI into digital media has revolutionized content creation, distribution, and analytics, offering unprecedented levels of personalization, efficiency, and insight. Automated journalism, AI- driven recommendation systems, and advanced audience analytics are among the key areas where AI is making significant contributions. However, the adoption of AI also brings ethical considerations, including concerns (...) about bias, privacy, and transparency. This paper analyzes case studies of successful and unsuccessful AI implementations in digital media, highlighting lessons learned and best practices. Finally, it looks ahead to future trends and developments, providing a comprehensive overview of the current state and potential future of AI in digital media. Through this exploration, the paper aims to provide valuable insights for academics, industry professionals, and policymakers on harnessing the power of AI while addressing its challenges. (shrink)

Intelligent neurotechnology is an emerging field that combines neurotechnologies like brain-computer interface (BCI) with artificial intelligence. This paper introduces a capability framework to assess the responsible use of intelligent BCI systems and provide practical ethical guidance. It proposes two tests, the threshold and flourishing tests, that BCI applications must meet, and illustrates them in a series of cases. After a brief introduction (Section 1), Section 2 sets forth the capability view and the two tests. It illustrates the threshold (...) test using examples from clinical medicine of BCI applications that enable patients with profound disabilities to function at a threshold level through computer mediation. Section 3 illustrates the flourishing test by exploring possible future applications of BCI involving neuroenhancements for healthy people, using examples adapted from research currently underway in the US military. Section 3 applies a capability lens to a complex case involving dual effects, both therapeutic and non-therapeutic, showing how the threshold and flourishing tests resolve the case. Section 4 replies to three objections: neurorights are the best tool for assessing BCI; the two tests are moving targets; and the analysis utilizes a capability view to do work it is not designed for. The paper concludes that a capability view offers unique advantages and gives practical guidance for evaluating the responsible use of present and future BCI applications. Extrapolating from our analysis may help guide other emerging technologies, such as germline gene editing, expected to impact central human capabilities. (shrink)

In their Why Machines Will Never Rule the World, Landgrebe and Smith (2023) argue that it is impossible for artificial general intelligence (AGI) to succeed, on the grounds that it is impossible to perfectly model or emulate the “complex” “human neurocognitive system”. However, they do not show that it is logically impossible; they only show that it is practically impossible using current mathematical techniques. Nor do they prove that there could not be any other kinds of theories than those (...) in current use. Even if perfect theories were impossible or unlikely, perfection may not be needed and may even be unhelpful. (shrink)

Bringing a unique perspective to the burgeoning ethical and legal issues surrounding the presence of artificial intelligence in our daily lives, the book uses theory and practice on animal rights and the rights of nature to assess the status of robots. -/- Through extensive philosophical and legal analyses, the book explores how rights can be applied to nonhuman entities. This task is completed by developing a framework useful for determining the kinds of personhood for which a nonhuman entity might (...) be eligible, and a critical environmental ethic that extends moral and legal consideration to nonhumans. The framework and ethic are then applied to two hypothetical situations involving real-world technology—animal-like robot companions and humanoid sex robots. Additionally, the book approaches the subject from multiple perspectives, providing a comparative study of legal cases on animal rights and the rights of nature from around the world and insights from structured interviews with leading experts in the field of robotics. Ending with a call to rethink the concept of rights in the Anthropocene, suggestions for further research are made. -/- An essential read for scholars and students interested in robot, animal and environmental law, as well as those interested in technology more generally, the book is a ground-breaking study of an increasingly relevant topic, as robots become ubiquitous in modern society. (shrink)

This paper explores the integration of multiple intelligences and artificial intelligence (AI) in language learning, focusing on its potential to enhance personalization and engagement. Drawing from existing research and studies conducted in various contexts, including the Philippines, this study aims to contribute to the understanding of the benefits, challenges, and effectiveness of this integration. The paper begins with an introduction that highlights the background and significance of integrating multiple intelligences and AI in language learning, identifying research gaps, objectives, research (...) questions, and the theoretical framework. A literature review provides an overview of multiple intelligences theory by Howard Gardner, the role of AI in language learning, and identifies gaps in the existing literature. The methodology section outlines the research design and approach, participant selection, data collection methods, validity and reliability measures, and ethical considerations. Findings and results are presented through the analysis of qualitative data, exploring emergent themes and patterns. The discussion section critically examines the identified research gaps, discusses the validity and reliability of the study, addresses the scope and limitations, and explores the implications of the findings for theory, practice, and future research. The conclusion summarizes the key findings and contributions of the study, reflects on the achievement of research objectives, offers recommendations for further research, and provides final remarks tying together the main points of the study. This paper contributes to the existing body of knowledge by providing insights into the integration of multiple intelligences and AI in language learning and its impact on personalization, engagement, and language learning outcomes. (shrink)

In this paper, we argue that because of the advent of Artificial Intelligence, the secret ballot is now much less effective at protecting voters from voting related instances of social ostracism and social punishment. If one has access to vast amounts of data about specific electors, then it is possible, at least with respect to a significant subset of electors, to infer with high levels of accuracy how they voted in a past election. Since the accuracy levels of Artificial (...) Intelligence are so high, the practical consequences of someone inferring one’s vote are identical to the practical consequences of having one’s vote revealed directly under an open voting regime. Therefore, if one thinks that the secret ballot is at least partly justified because it protects electors against voting related social ostracism and social punishment, one should be morally troubled by how Artificial Intelligence today can be used to infer individual electors’ past voting behaviour. (shrink)

Δ.Δακρότσης, «Τεχνητή νοημοσύνη και εκφραστικότητα: η αναγκαιότητα περάσματος της εννοιολογικής γνώσης από το μονοπάτι της αισθητικής εποπτείας» (Artificial Intelligence and expressiveness: The necessity for conceptual knowledge to go through the path of aesthetic perception), Days of Art in Greece, Τεύχος 18, Φθινόπωρο 2024, σς 26-39.

The emerging contemporary natural philosophy provides a common ground for the integrative view of the natural, the artificial, and the human-social knowledge and practices. Learning process is central for acquiring, maintaining, and managing knowledge, both theoretical and practical. This paper explores the relationships between the present advances in understanding of learning in the sciences of the artificial (deep learning, robotics), natural sciences (neuroscience, cognitive science, biology), and philosophy (philosophy of computing, philosophy of mind, natural philosophy). The question is, what (...) at this stage of the development the inspiration from nature, specifically its computational models such as info-computation through morphological computing, can contribute to machine learning and artificial intelligence, and how much on the other hand models and experiments in machine learning and robotics can motivate, justify, and inform research in computational cognitive science, neurosciences, and computing nature. We propose that one contribution can be understanding of the mechanisms of ‘learning to learn’, as a step towards deep learning with symbolic layer of computation/information processing in a framework linking connectionism with symbolism. As all natural systems possessing intelligence are cognitive systems, we describe the evolutionary arguments for the necessity of learning to learn for a system to reach human-level intelligence through evolution and development. The paper thus presents a contribution to the epistemology of the contemporary philosophy of nature. (shrink)

As systems based on opaque Artificial Intelligence (AI) continue to flourish in diverse real-world applications, understanding these black box models has become paramount. In response, Explainable AI (XAI) has emerged as a field of research with practical and ethical benefits across various domains. This paper not only highlights the advancements in XAI and its application in real-world scenarios but also addresses the ongoing challenges within XAI, emphasizing the need for broader perspectives and collaborative efforts. We bring together experts (...) from diverse fields to identify open problems, striving to synchronize research agendas and accelerate XAI in practical applications. By fostering collaborative discussion and interdisciplinary cooperation, we aim to propel XAI forward, contributing to its continued success. Our goal is to put forward a comprehensive proposal for advancing XAI. To achieve this goal, we present a manifesto of 27 open problems categorized into nine categories. These challenges encapsulate the complexities and nuances of XAI and offer a road map for future research. For each problem, we provide promising research directions in the hope of harnessing the collective intelligence of interested stakeholders. (shrink)

On a literal reading of `Computing Machinery and Intelligence'', Alan Turing presented not one, but two, practical tests to replace the question `Can machines think?'' He presented them as equivalent. I show here that the first test described in that much-discussed paper is in fact not equivalent to the second one, which has since become known as `the Turing Test''. The two tests can yield different results; it is the first, neglected test that provides the more appropriate indication (...) of intelligence. This is because the features of intelligence upon which it relies are resourcefulness and a critical attitude to one''s habitual responses; thus the test''s applicablity is not restricted to any particular species, nor does it presume any particular capacities. This is more appropriate because the question under consideration is what would count as machine intelligence. The first test realizes a possibility that philosophers have overlooked: a test that uses a human''s linguistic performance in setting an empirical test of intelligence, but does not make behavioral similarity to that performance the criterion of intelligence. Consequently, the first test is immune to many of the philosophical criticisms on the basis of which the (so-called) `Turing Test'' has been dismissed. (shrink)

The mythical bronze creature Talos (Greek: Τάλως) was worshiped initially as the god of light or the sun in the Hellenic Island of Crete. He is supposed to have lived in the peak Kouloukona of the Tallaia Mountains in the Gerontospelio cave. His relation towards bronze and fire and his continuous voyage circling the island of Crete most probably introduces the concept of the change of the four seasons. The sun was considered in the area of the South-East Mediterranean nations (...) as just judge, a guardian who monitors and judges from above all the actions of the commoners, a controller for the faithful application of laws in Crete [1]. Hesychios in his Lexicon notes that talos means sun and that the name Tallaios was initially attributed to Zeus [2]. The birth of the Olympian gods forged a new Pantheon and nomenclature forcing some of the old gods to fell into lower deities. This happened to Talos who soon became a mythical hero [1]. According to Apollodorus, the bronze creature was forged by the magnificent constructor Hephaestus as a gift to the mythical King Minoa to help him guard the island [3]. Although the verb “peritrohazo” (Greek: περιτροχαζω) was used, meaning a movement in a steady orbit (track), some depictions image him as a winged being. To protect the island, he was throwing rocks into unknown ships or in the case of a foreign landing he was burning with fire or with his flamed bronze body the intruders. He was holding copper plates with the laws of the island and his circle allowed him to pass all island sores three times daily [1,4-6]. Plato, speaks of him as a real person, suggesting he was the brother of King Rhadamanthys, thus a son of Zeus [5]. Talos may be considered as the token of the Cretan power, a symbol of technological development in the field of metalworking in prehistoric and Minoan times. An animated, programmed gigantic android to enforce its will. A primitive robot for basic actions having a power source, fire and ichor (Greek: ιχώρ) the sacred fluid in the vessels of the gods. The first manufactured being with his individual intelligence, a primary concept of artificial intelligence (AI) [7]. -/- Homer was the first to introduce the term automata (Greek: αυτόματα), to describe ingenious machines built by the supreme blacksmith god of invention and technology, God of metal and fire, Hephaestus, manufactured devices “acting of one’s own will” as the Hellenic word indicates [8]. Eons later, the humanoid automaton the “Automa cavaliere” (English: Automaton knight) appeared in the court of the nobleman and Duke of Milan Ludovico Maria Sforza. It was the year 1495, when Leonardo da Vinci presented his robotic knight, an innovative construction operated by a series of pulleys and cables, presenting though no individual mind. Although it was manufactured by a highly intelligent polymath, it could only be operated through an outer intelligence [9]. Advancements made during the Fourth Industrial Revolution allowed modern technology to manufacture intelligent machines to aid the field of invasive surgery. One of those most sophisticated devises is the da Vince Surgical Tower. -/- Launched in the setting of the 21st century, the DaVinci System is one of the most commonly employed tools/systems, which has prevailed in the field of robotic-assisted surgery [10]. One could claim that it practically reshaped the concept of surgery, providing doctors with immense capabilities, aiming towards the optimal post-operative outcome. Through visual augmentation, high resolution 3D video, enhanced precision and reduced complication rates [11] the DaVinci Si and the latest DaVinci Xi system have been implemented in a variety of surgeries, including but not limited to general, urologic, gynecologic, thoracic and even cardiac procedures; valve and coronary artery bypass graft operations [12,13]. Da Vinci is cleared globally for cardiosurgery and came in vogue to fulfill the dream of cardiac surgeons to operate in closet chest. It offers in patients the same benefits as those that open chest incision surgery procedures do [14]. -/- The more recent DaVinci Xi model was introduced to counteract commonly known drawbacks of the Si system, such as the inability to simultaneously manipulate the different abdominal quadrants [10]. It consists of four boom mounted robotic arms along with a mobile platform and a master console. The latter with the adaptable intraocular distance, the cushioned headrest, the modifiable arm bars and the flexible finger loops, is meticulously designed to meet the surgeon´s “demands” [12]. Every robotic arm has three degrees of freedom, which combined with the EndoWrist technology to imitate the delicate motion of the surgeon´s hand, acquires an extra seven degrees of freedom. Evidently, the combination of the user-friendly interface, the high-quality 3D intraoperative images, the multiple joints and sensors, as well as the surgeon himself, who can learn to handle the DaVinci Xi Surgical System in a relatively short period of time, has established the model in the surgical armamentarium, paving the way towards a continuously progressive future of minimally invasive and robotic surgery (Figure 1) [12]. -/- History testifies that the nomination of the AI surgical tower as da Vinci was wrongfully given to commemorate a majestic historical figure. It is clear that the mythical creature Talos which was fabricated by the ingenious god Hephaestus was the first true automaton in the line of AI origins. (shrink)

Intelligence analysis has many important epistemological resemblances with science (problem solving, discovery, skillful use of tools, knowledge verification) and is more interested in a posteriori than a priori knowledge, on how or the basis on which a proposition may be known. The puzzle metaphor is used in both information and archeology. Both disciplines involve collecting evidence to build as complete a picture as possible. The process of converting raw information into actionable processed intelligence is almost identical for governmental (...) and business organizations. The medical practice of diagnosing identification, collection, analysis and dissemination is similar to that of intelligence. DOI: 10.13140/RG.2.2.26511.12963. (shrink)

With the rise and public accessibility of AI-enabled decision-support systems, individuals outsource increasingly more of their decisions, even those that carry ethical dimensions. Considering this trend, scholars have highlighted that uncritical deference to these systems would be problematic and consequently called for investigations of the impact of pertinent technology on humans’ ethical decision-making. To this end, this article conducts a systematic review of existing scholarship and derives an integrated framework that demonstrates how intelligent decision-support systems (IDSSs) shape humans’ ethical decision-making. (...) In particular, we identify resulting consequences on an individual level (i.e., deliberation enhancement, motivation enhancement, autonomy enhancement and action enhancement) and on a societal level (i.e., moral deskilling, restricted moral progress and moral responsibility gaps). We carve out two distinct methods/operation types (i.e., processoriented and outcome-oriented navigation) that decision-support systems can deploy and postulate that these determine to what extent the previously stated consequences materialize. Overall, this study holds important theoretical and practical implications by establishing clarity in the conceptions, underlying mechanisms and (directions of) influences that can be expected when using particular IDSSs for ethical decisions. (shrink)

The ML community recognizes the importance of anticipating and mitigating the potential negative impacts of benchmark research. In this position paper, we argue that more attention needs to be paid to areas of ethical risk that lie at the technical and scientific core of ML benchmarks. We identify overlooked structural similarities between human IQ and ML benchmarks. Human intelligence and ML benchmarks share similarities in setting standards for describing, evaluating and comparing performance on tasks relevant to intelligence. This (...) enables us to unlock lessons from feminist philosophy of science scholarship that need to be considered by the ML benchmark community. Finally, we outline practical recommendations for benchmark research ethics and ethics review. (shrink)

Abstract: The integration of Artificial Intelligence (AI) into educational technology has revolutionized learning through Intelligent Tutoring Systems (ITS). These systems harness AI to deliver personalized, adaptive instruction that caters to individual student needs, thereby enhancing learning outcomes and engagement. This paper explores the evolution and impact of ITS, highlighting key AI technologies such as machine learning, natural language processing, and adaptive algorithms that underpin their functionality. By examining various case studies and applications, the paper illustrates how ITS have transformed (...) traditional educational practices and identifies the challenges and limitations associated with their implementation, including data privacy concerns and system biases. The discussion also extends to future directions in ITS development, emphasizing emerging trends and potential advancements. Ultimately, this paper aims to provide a comprehensive understanding of how ITS leverage AI to enhance educational experiences and propose pathways for future research in this dynamic field. (shrink)

This essay is divided into two parts. In the first part (§2), I introduce the idea of practical meaning by looking at a certain kind of procedural systems — the motor system — that play a central role in computational explanations of motor behavior. I argue that in order to give a satisfactory account of the content of the representations computed by motor systems (motor commands), we need to appeal to a distinctively practical kind of meaning. Defending the (...) explanatory relevance of semantic properties in a computationalist explanation of motor behavior, my argument concludes that practical meanings play a central role in an adequate psychological theory of motor skill. In the second part of this essay (§3), I generalize and clarify the notion of practical meaning, and I defend the intelligibility of practical meanings against an important objection. (shrink)

This article offers an overview of the main first-order ethical questions raised by robots and Artificial Intelligence (RAIs) under five broad rubrics: functionality, inherent significance, rights and responsibilities, side-effects, and threats. The first letter of each rubric taken together conveniently generates the acronym FIRST. Special attention is given to the rubrics of functionality and inherent significance given the centrality of the former and the tendency to neglect the latter in virtue of its somewhat nebulous and contested character. In addition (...) to exploring some illustrative issues arising under each rubric, the article also emphasizes a number of more general themes. These include: the multiplicity of interacting levels on which ethical questions about RAIs arise, the need to recognise that RAIs potentially implicate the full gamut of human values (rather than exclusively or primarily some readily identifiable sub-set of ethical or legal principles), and the need for practically salient ethical reflection on RAIs to be informed by a realistic appreciation of their existing and foreseeable capacities. -/- . (shrink)

The discussion of artificial intelligence (AI) as a newly emerging phenomenon in the present era has always been faced with various ethical challenges. The expansion of artificial intelligence is inevitable, and since this phenomenon is related to the human and social world, anything related to humans and society falls within the realm of morality and rights. In doing so, it must be understood whether the use of artificial intelligence is an ethical matter or not. Furthermore, do humans (...) have the right to use it or not? It seems that Al-Farabi's thought in the realm of practical wisdom can provide an answer to this issue. By reflecting on the theories of this prominent philosopher in civil philosophy, the theory of natural rights is obtained, and on the other hand, Al-Farabi's ethical opinions are also consistent with the theory of natural rights and, in general, with Al-Farabi's civil philosophy. It can, therefore, be argued that, one can consider and elucidate this issue through the lens of Al-Farabi's ethical and civil school of thought. -/- . (shrink)

Forms of Artificial Intelligence (AI) are already being deployed into clinical settings and research into its future healthcare uses is accelerating. Despite this trajectory, more research is needed regarding the impacts on patients of increasing AI decision making. In particular, the impersonal nature of AI means that its deployment in highly sensitive contexts-of-use, such as in healthcare, raises issues associated with patients’ perceptions of (un) dignified treatment. We explore this issue through an experimental vignette study comparing individuals’ perceptions of (...) being treated in a dignified and respectful way in various healthcare decision contexts. Participants were subject to a 2 (human or AI decision maker) x 2 (positive or negative decision outcome) x 2 (diagnostic or resource allocation healthcare scenario) factorial design. We found evidence of a “human bias” (i.e., a preference for human over AI decision makers) and an “outcome bias” (i.e., a preference for positive over negative outcomes). However, we found that for perceptions of respectful and dignified interpersonal treatment, it matters more who makes the decisions in diagnostic cases and it matters more what the outcomes are for resource allocation cases. We also found that humans were consistently viewed as appropriate decision makers and AI was viewed as dehumanizing, and that participants perceived they were treated better when subject to diagnostic as opposed to resource allocation decisions. Thematic coding of open-ended text responses supported these results. We also outline the theoretical and practical implications of these findings. (shrink)

Artificial Intelligence refers to developing computer systems and machines that can perform tasks that usually require human intelligence. AI is an evolving field, and researchers and engineers continue to explore and develop new techniques and technologies to enhance its capabilities. The impact of AI on religions is not entirely predictable. AI is likely to affect religions or be affected by them in various ways, some of which are already becoming apparent. As with any new technology, it is up (...) to individuals and religious communities to decide how to incorporate AI into their beliefs and practices. It is worth mentioning that the mutual relevance of Sikhism and AI is likely to be complex and multifaceted. It will depend on how AI is developed, implemented, and used and the attitudes and beliefs of individual Sikhs and the Sikh community. (shrink)

We present a theory of cooperative-competitive intelligence (CCI), its measures, research program, and applications that stem from it. Within the framework of this theory, satisficing sub-optimal behavior is any behavior that does not promote a decrease in the prospective control of the functional action diversity/unpredictability (D/U) potential of the agent or team. This potential is defined as the entropy measure in multiple, context-dependent dimensions. We define the satisficing interval of behaviors as CCI. In order to manifest itself at individual (...) or team level, this capacity harnesses properties such as degeneracy, pleiotropy (pluri-potentiality), synergies, and metastability. Intelligence is embodied because intelligent behavior is deeply dependent on body functionalities, defined as entropy measures. We base our theory on three principles: (a) relativity of functional entropy/ information in agent (team)-environment systems, (b) tendency toward the satisficing level of D/U potential, and (c) tendency toward the non-decreasing D/U potential. The conjunction of these three principles provides existence of sub-optimal behaviors associated with CCI. First, we deal with the problem of how to reduce multidimensional behavior to a concept that accounts for the vast set of scenarios in which CCI is manifested. Secondly, we define and discuss the three interacting principles that underpin CCI behavior as well as providing an outline for a future CCI research program supported by agent￾based modeling and empirical research. Finally, we provide some preliminary practical issues that stem from the theory. (shrink)

In this paper I describe a novel application of contemplative techniques to software engineering with the goal of augmenting the intellectual capabilities of knowledge workers within the field in four areas: flexibility, attention, creativity, and trust. The augmentation of software engineers’ intellectual capabilities is proposed as a third complement to the traditional focus of methodologies on the process and environmental factors of the software development endeavor. I argue that these capabilities have been shown to be open to improvement through the (...) practices traditionally used in spiritual traditions, but now used increasingly in other fields of knowledge work, such as in the medical profession and the education field. Historically, the intellectual capabilities of software engineers have been treated as a given within any particular software development effort. This is argued to be an aspect ripe for inclusion within software development methodologies. (shrink)

Abstract: The integration of Artificial Intelligence (AI) into leadership practices is transforming organizational dynamics and This decision-making processes. paper explores how AI can enhance leadership effectiveness by providing data-driven insights, optimizing decision-making, and automating routine tasks. It also examines the challenges leaders face in adopting AI, including ethical considerations, potential biases in AI systems, and the need for upskilling. By analyzing current applications of AI in leadership and discussing future trends, this study aims to provide a comprehensive overview of (...) the opportunities AI presents for effective leadership and the strategies required to address its associated challenges. (shrink)

Recent years have witnessed intensive efforts to specify which requirements ethical artificial intelligence (AI) must meet. General guidelines for ethical AI consider a varying number of principles important. A frequent novel element in these guidelines, that we have bundled together under the term explicability, aims to reduce the black-box character of machine learning algorithms. The centrality of this element invites reflection on the conceptual relation between explicability and the four bioethical principles. This is important because the application of general (...) ethical frameworks to clinical decision-making entails conceptual questions: Is explicability a free-standing principle? Is it already covered by the well-established four bioethical principles? Or is it an independent value that needs to be recognized as such in medical practice? We discuss these questions in a conceptual-ethical analysis, which builds upon the findings of an empirical document analysis. On the example of the medical specialty of radiology, we analyze the position of radiological associations on the ethical use of medical AI. We address three questions: Are there references to explicability or a similar concept? What are the reasons for such inclusion? Which ethical concepts are referred to? (shrink)

In recent years a growing number of philosophers in the analytic tradition have focused their attention on the significance of human sociality. An older point of departure of analysis, which actually precedes this current tide of accounts of sociality, has revolved around the debate between “holism” and “individualism” in the philosophy of the human or social sciences and social theory. The more recent point of departure for various accounts of sociality has centered on the nature of conventions, social groups, shared (...) intentions, or collective intentionality. Putting aside the disagreements among these accounts, they all take for granted an antecedently intelligible notion of individual agency as explanatorily primitive and seek to explain the possibility of plural or collective agency in terms of the former. By contrast, other philosophers who have worked at the intersection of analytic and "continental" philosophy have emphasized the primacy of practice as the proper starting point for philosophical reflections on the nature of human sociality. In the analytic tradition this emphasis is typically framed in terms of the possibility of rule-following, a topic put on the philosophical agenda by the later Wittgenstein. Peter Winch’s and Saul Kripke’s influential but controversial readings of Wittgenstein explicitly thematize the issue of rule-following, readings which have in turn generated critical reflection in various disciplines for which this issue is relevant. -/- I begin by briefly explicating the positions of Pettit and Brandom on the issue of rule-following (putting aside any specific differences between them for the moment). Next I connect Pettit’s and Brandom’s views on rule-following, and more generally on normativity and its necessarily social basis, with the views of Theodore Schatzki and Joseph Rouse, whose conceptions of the significance of practice and its inherent sociality are indebted as much to the early Heidegger as well as the later Wittgenstein. I suggest that Pettit’s and Brandom’s views of the necessarily social nature of rule-following (i.e., practice) ought to acknowledge and integrate the shared insight of Schatzki and Rouse that practices are not only modes of activity, but constitute more basically the concrete setting or world within which practices qua modes of activity are intelligible (verständlich) at all. I conclude the paper by suggesting how an integrated account of the significance of the necessarily social nature of practice undermines the assumptions of those philosophers who seek to analyze human sociality solely on the basis of modes of interactions among individual agents. (shrink)

Modern digital technologies—from web-based services to Artificial Intelligence (AI) solutions—increasingly affect the daily lives of billions of people. Such innovation brings huge opportunities, but also concerns about design, development, and deployment of digital technologies. This article identifies and discusses five clusters of risk in the international debate about digital ethics: ethics shopping; ethics bluewashing; ethics lobbying; ethics dumping; and ethics shirking.

A process of intelligence gathering begins when a user enters a query into the system. Several objects can match the result of a query with different degrees of relevance. Most systems estimate a numeric value about how well each object matches the query and classifies objects according to this value. Many researches have focused on practices of intelligence gathering. In knowledge engineering, knowledge gathering consists in fiding it from structured and unstructured sources in a way that must represent (...) knowledge in a way that facilitates inference. DOI: 10.13140/RG.2.2.32191.15527. (shrink)

Imagine you are the CEO of a hospital [. . .]. Decisions are constantly being made in your organization about how to spend the organization's money. The amount of money available to spend is never adequate to pay for everything you wish you could spend it on, therefore you must set spending priorities. There are two questions you need to be able to answer . . . How should we set priorities in this organization? How do we know when we (...) are doing it well? When people seek to achieve good public policy, the result will tend to be good public policy. In a collective choice process, public‐spirited individual participants produce good public policy by deliberating—talking with each other, listening to each other's arguments, and being willing to learn and change their minds based on such dialogue. –Steven Kelman (1992: 181) Public policy scholars agree that those persons (or agencies) vested with the authority to establish health care priorities should elicit public input before making rationing decisions. The two most common approaches are (i) consultation and (ii) deliberation. Though deliberation has obvious advantages over consultation, it falters in the face of the objection that ordinary citizens lack the cognitive resources for the extended, rigorous inquiry required of them in undertaking the priority‐setting task. To overcome this objection, I propose that deliberative forums for health care rationing should be designed so that they imitate the natural pattern of human experience. The experience of deliberation should encompass both prolonged periods of less‐demanding cognitive activity, in which citizens passively receive information, and briefer periods of more‐demanding cognitive activity, in which they engage in active problem‐solving. In arguing for this thesis, I rely on two theoretical sources and one practical case study, in the following order: (i) John Dewey's metaphysics of experience, (ii) cognitive science research on schemas and frames, and (iii) the Health Care Council in São Paulo, Brazil. (shrink)

Whether causing flash crashes in financial markets, purchasing illegal drugs, or running over pedestrians, AI is increasingly engaging in activity that would be criminal for a natural person, or even an artificial person like a corporation. We argue that criminal law falls short in cases where an AI causes certain types of harm and there are no practically or legally identifiable upstream criminal actors. This Article explores potential solutions to this problem, focusing on holding AI directly criminally liable where it (...) is acting autonomously and irreducibly. Conventional wisdom holds that punishing AI is incongruous with basic criminal law principles such as the capacity for culpability and the requirement of a guilty mind. -/- Drawing on analogies to corporate and strict criminal liability, as well as familiar imputation principles, we show how a coherent theoretical case can be constructed for AI punishment. AI punishment could result in general deterrence and expressive benefits, and it need not run afoul of negative limitations such as punishing in excess of culpability. Ultimately, however, punishing AI is not justified, because it might entail significant costs and it would certainly require radical legal changes. Modest changes to existing criminal laws that target persons, together with potentially expanded civil liability, are a better solution to AI crime. (shrink)

The first decade of this century has seen the nascency of the first mathematical theory of general artificial intelligence. This theory of Universal Artificial Intelligence (UAI) has made significant contributions to many theoretical, philosophical, and practical AI questions. In a series of papers culminating in book (Hutter, 2005), an exciting sound and complete mathematical model for a super intelligent agent (AIXI) has been developed and rigorously analyzed. While nowadays most AI researchers avoid discussing intelligence, the award-winning (...) PhD thesis (Legg, 2008) provided the philosophical embedding and investigated the UAI-based universal measure of rational intelligence, which is formal, objective and non-anthropocentric. Recently, effective approximations of AIXI have been derived and experimentally investigated in JAIR paper (Veness et al. 2011). This practical breakthrough has resulted in some impressive applications, finally muting earlier critique that UAI is only a theory. For the first time, without providing any domain knowledge, the same agent is able to self-adapt to a diverse range of interactive environments. For instance, AIXI is able to learn from scratch to play TicTacToe, Pacman, Kuhn Poker, and other games by trial and error, without even providing the rules of the games. These achievements give new hope that the grand goal of Artificial General Intelligence is not elusive. This article provides an informal overview of UAI in context. It attempts to gently introduce a very theoretical, formal, and mathematical subject, and discusses philosophical and technical ingredients, traits of intelligence, some social questions, and the past and future of UAI. (shrink)

Abstract: The integration of Artificial Intelligence (AI) into Human Resource Management (HRM) is fundamentally transforming how organizations approach recruitment, performance management, and employee engagement. This paper explores the multifaceted impact of AI on HR practices, highlighting its role in enhancing efficiency, reducing bias, and driving strategic decision-making. Through an in-depth analysis of AI-driven recruitment tools, performance management systems, and personalized employee engagement strategies, this study examines both the opportunities and challenges associated with AI in HRM. Ethical considerations, including data (...) privacy, algorithmic bias, and the potential displacement of human jobs, are critically discussed to provide a balanced perspective on the adoption of AI technologies in the HR domain. By presenting case studies of organizations successfully leveraging AI, this paper offers insights into the future trajectory of HRM in an increasingly AI-driven world. Ultimately, the findings underscore the need for HR professionals to adapt and innovate in response to the growing influence of AI, ensuring a harmonious balance between technological advancement and the human element in the workplace. (shrink)

Dear Colleagues, -/- Recently, for an article submitted to the European Journal of Therapeutics, it was reported that the paper may have been written with artificial intelligence support at a rate of more than 50% in the preliminary examination made with Turnitin. However, the authors did not mention this in the article’s material method or explanations section. Fortunately, the article’s out-of-date content and fundamental errors in its methodology allowed us no difficulty making the desk rejection decision. -/- On the (...) other hand, similar situations that we may encounter later caused us to discuss how we would decide when the artificial intelligence support of the articles was written. The general opinion that we have adopted and currently available in the literature is that if artificial intelligence is used while writing an article, how artificial intelligence is used in the methodology should be written in detail. -/- Moreover, we encountered a much more exciting situation during our evaluation. In a few academic studies, we have seen that artificial intelligence is added as a co-author. On July 06, 2023, in the Web of Science, using the advanced search, we found four articles with the author name ChatGPT [1]. We have determined that ChatGPT is the author in one of these articles [2] and the Group Author in three [3-5]. -/- Lee [6] stated that although artificial intelligence tools are much more advanced than search engines, they cannot be an author regarding research ethics because they cannot take responsibility for what they write. Similarly, Goto and Katanoda [7] stated that it is the author’s responsibility to confirm that the texts written by ChatGPT are correct. However, Pourhoseingholi et al. [8] reported that keeping up with technology is inevitable. Additionally, they said that“this action will be more fruitful and practical in extended dimensions when international institutes like ICMJE or COPE come up with the appropriate adjustments and establish robust criteria to scheme the AI authorship”. -/- Most probably, the use of artificial intelligence applications in scientific articles and whether it can be a co-author in these papers will be discussed soon. -/- We encourage interested authors to submit their ideas to our journal as a letter to the editor. -/- Yours sincerely,. (shrink)

In everyday life, we constantly encounter and deal with useful things without pausing to inquire about the sources of their intelligibility. In Div. I of Being and Time, Heidegger undertakes just such an inquiry. According to a common reading of Heidegger's analysis, the intelligibility of our everyday encounters and dealings with useful things is ultimately constituted by practical self-understandings. In this paper, I argue that while such practical self-understandings may be sufficient to constitute the intelligibility of the tools (...) and equipment specific to many practices, these “tools of the trade” are only a small portion of the things we encounter, use, and deal with on a daily basis. Practical self-understandings cannot similarly account for the intelligibility of the more mundane things—like toothbrushes and sidewalks—used in everyday life. I consider whether an anonymous self-understanding as “one,” “anyone,” or “no one in particular” —das Man—might play this intelligibility-constituting role. In examining this possibility, another type of self-understanding comes to light: cultural identities. I show that the cultural identities into which we are “thrown,” rather than practical identities or das Man, constitute the intelligibility of the abundance of mundane things that fill our everyday lives. Finally, I spell out how this finding bears on our understanding of Heidegger's notion of authenticity. (shrink)

I argue that, for Mengzi, the kind of knowledge that features in expressions of the form ‘knowing N’, where N is a noun or a noun phrase, is not a kind of belief but is instead a capacity for intelligently performing relevant actions. My argument proceeds by showing that, first, Mengzi is committed to the view that a person knows N iff she is relevantly capable and, second, that the best explanation for this is that the kind of knowledge involved (...) in knowing N is a capacity. Finally, I motivate such a practicalist interpretation by arguing that it offers us a general but informative explanation of what it is that knowing N makes the knower capable of doing. (shrink)