Este artículo explora la integración de la IA en la comunicación académica para mejorar las capacidades cognitivas humanas. La concepción de la comunicación hombre-máquina (CMM), que considera las tecnologías basadas en la IA no como objetos interactivos, sino como sujetos comunicativos, plantea cuestiones más filosóficas en la comunicación académica. Es un hecho conocido que existe una mayor interacción entre los humanos y las máquinas, especialmente consolidada por la pandemia COVID-19, que intensificó el desarrollo del Sistema de Aprendizaje Adaptativo Individual, por (...) lo que necesariamente se requieren aportaciones de las IN para fortalecer la IA. Esto posicionó a la universidad en la yuxtaposición de asegurar la producción de individuos altamente talentosos que puedan continuar pensando más allá de lo pensable inteligentemente y permitir a los expertos en IA continuar construyendo algoritmos que puedan llevar el desarrollo de la tecnología al siguiente nivel. Para llevar a cabo tal tarea, la producción investigadora es primordial para conectar la universidad y la industria editorial. Este artículo examina de forma crítica componentes importantes e intenta hacer justicia a la emanación de preguntas críticas de los investigadores (NI), alimentando así el desarrollo de la tecnología (IA). (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)

The difficulty of explaining the outputs of artificial intelligence (AI) models and what has led to them is a notorious ethical problem wherever these technologies are applied, including in the medical domain, and one that has no obvious solution. This paper examines the proposal, made by Luciano Floridi and colleagues, to include a new ‘principle of explicability’ alongside the traditional four principles of bioethics that make up the theory of ‘principlism’. It specifically responds to a recent set of (...) criticisms that challenge the supposed need for such a principle to perform an enabling role in relation to the traditional four principles and therefore suggest that these four are sufficient without the addition of explicability. The paper challenges the critics’ premise that explicability cannot be an ethical principle like the classic four because it is explicitly subordinate to them. It argues instead that principlism in its original formulation locates the justification for ethical principles in a midlevel position such that they mediate between the most general moral norms and the contextual requirements of medicine. This conception of an ethical principle then provides a mold for an approach to explicability on which it functions as an enabling principle that unifies technical/epistemic demands on AI and the requirements of high-level ethical theories. The paper finishes by anticipating an objection that decision-making by clinicians and AI fall equally, but implausibly, under the principle of explicability’s scope, which it rejects on the grounds that human decisions, unlike AI’s, can be explained by their social environments. (shrink)

Michel Foucault's early works criticize the development of modern democratic institutions as creating a surveillance society, which functions to control bodies by making them feel watched and monitored full time. His later works attempt to recover private space by exploring subversive techniques of the body and language. Following Foucault, pragmatists like Richard Shusterman and Richard Rorty have also developed very rich approaches to this project, extending it deeper into the literary and somatic dimensions of self-stylizing. Yet, for a debate centered (...) on the re-creation of the vision of the self, these discussions have yet to fully engage—even while they set the conditions for this engagement with—issues of posthuman technologies, such as AI, robotics, and genetic engineering. These certainly will constitute the primary engine of public institutional surveillance in the years to come. With this surveillance, the two spheres of private self-fashioning and public institutions will continue to evolve in relation to one another. As they do so, democratic society will change considerably. Perhaps Rorty's own normative and linguistic ideal of conversational maintenance may provide something of a democratic limit case on any future posthuman self-fashioning. (shrink)

AI and people do not compete on a level-playing field. Self-driving vehicles may be safer than human drivers, but laws often penalize such technology. People may provide superior customer service, but businesses are automating to reduce their taxes. AI may innovate more effectively, but an antiquated legal framework constrains inventive AI. In The Reasonable Robot, Ryan Abbott argues that the law should not discriminate between AI and human behavior and proposes a new legal principle that will ultimately improve human well-being. (...) This work should be read by anyone interested in the rapidly evolving relationship between AI and the law. (shrink)

Nowadays, new directions for the development of artificial intelligence (AI) have emerged, the task has been set to develop artificial general intelligence (AGI), which is able to go beyond the narrow AI, gain a high degree of autonomy, independently solve problems in different environmental conditions and thus have the ability to perform the functions of natural intelligence. In this regard, important philosophical, theoretical, and methodological questions arise concerning the definition and evaluation of the social significance (...) of new AI achievements, especially regarding the correlation of their socio-humanitarian and technological aspects. It is necessary to overcome a purely technocratic approach, which usually ignores the negative consequences of digitalization, the possible risks and threats of AI development. These difficulties are conditioned by the paradigm gap between the system of concepts used to describe technologies and the systems of concepts specific to socio-humanitarian descriptions and explanations. The so-called ontological paradox arises during digital transformation and the introduction of AI into social systems. An ontological paradox is also an epistemological paradox, since any statement of an ontological type presupposes its epistemological justification. To overcome this gap, V.E. Lepskiy proposes the conception of self-developing polysubjective environments – cybernetics of the third order. This conception allows to create a conceptual “bridge” between two systems of definitions that do not have direct logical connections between them. A productive tool for this can be the information approach, which is widely used to solve such interdisciplinary problems. This makes possible to theoretically correctly connect technological and socio-humanitarian descriptions in a single conceptual structure and to analyze main socio-humanitarian criteria for evaluating digital innovations. The article discusses in detail the main provisions of the information approach and its application for the development of AGI systems, the socio-humanitarian assessment of AI autonomous development, and the resolution of security issues. (shrink)

Intellectual humility (IH) is often conceived as the recognition of, and appropriate response to, your own intellectual limitations. As far as we are aware, only a handful of studies look at interventions to increase IH – e.g. through journalling – and no study so far explores the extent to which having high or low IH can be predicted. This paper uses machine learning and natural language processing techniques to develop a predictive model for IH and identify top terms and features (...) that indicate degrees of IH. We trained our classifier on the dataset from an existing psychological study on IH, where participants were asked to journal their experiences with handling social conflicts over 30 days. We used Logistic Regression (LR) to train a classifier and the Linguistic Inquiry and Word Count (LIWC) dictionaries for feature selection, picking out a range of word categories relevant to interpersonal relationships. Our results show that people who differ on IH do in fact systematically express themselves in different ways, including through expression of emotions (i.e., positive, negative, and specifically anger, anxiety, sadness, as well as the use of swear words), use of pronouns (i.e., first person, second person, and third person) and time orientation (i.e., past, present, and future tenses). We discuss the importance of these findings for IH and the value of using such techniques for similar psychological studies, as well as some ethical concerns and limitations with the use of such semi-automated classifications. (shrink)

The imaginative context in which artificial intelligence is embedded remains a crucial touchstone from which to understand and critique both the histories and prospective futures of an AI-driven world. A recent article from Cave and Dihal sets out a narrative schema of four hopes and four corresponding fears associated with intelligent machines and AI. This article seeks to respond to the work of Cave and Dihal by presenting a gendered reading of this schema of hopes and fears. I (...) offer a brief genealogy of narratives which feature female automata, before turning to examine how gendered technology today—particularly AI assistants like Siri and Alexa—reproduces the historical narratives associated with intelligent machines in new ways. Through a gendered reading of the hopes and fears associated with AI, two key responses arise. First, that the affective reactions to intelligent machines cannot be readily separated where such machines are gendered female. And second, that the gendering of AI technologies today can be understood as an attempt to reconcile the opposing hopes and fears AI produces, and that this reconciliation is based on the association of such technologies with traditional notions of femininity. Critically, a gendered reading enables us to problematize the narratives associated with AI and expose the power asymmetries that lie within, and the technologies which arise out of, such narratives. (shrink)

Since the publication of ChatGPT and Dall-E, there has been heavy discussions on the possible dangers of generative artificial intelligence (AI) for society. These discussions question the extent to which the development of AI can be regulated by politics, law, and civic actors. An important arena for discourse on AI is the news media. The news media discursively construct AI as a technology that is more or less possible to regulate. There are various reasons for an assumed regulatability. (...) Some voices highlight the predominant capitalism of modern society as an ideology that enforces an uncontrolled development of AI. Others call on the rationality of civic society, which will push AI toward a development that serves humankind. Summarized, the discourse on AI floats between positions of technological and social determinism. The article conducts a discourse analysis on 113 articles from the German newspapers Süddeutsche Zeitung and Frankfurter Allgemeine Zeitung. The analysis shows how these center-left and center-right media frame the AI development in terms of social and technological determinism. As these newspapers reach out to a large audience, the article shows the kinds of perspectives on AI that confront civic society in Germany every day. News media can motivate or impede social action, as they frame the potential necessity of society and its members to intervene against certain developments. The article shows how the newspapers promote an understanding of AI, by which citizens will feel motivated to insist on a regulation of AI by politics and law. (shrink)

This book offers a first glimpse into contemporary African Philosophical thought, which covers issues related to the mind-body relationships, the problem of consciousness, the ethics of artificial intelligence, the meaning of life and other topics. Taking inspiration from the conversational tradition in African philosophy, this book not only engages with and takes inspiration from traditional African thought, but also engages with philosophical views outside the philosophical tradition in a bid to present a holistic understanding of the problems that (...) are central to the book. The volume is relevant for professional African philosophers, philosophers of mind, philosophers of AI, undergraduate and postgraduate philosophy students, and African Studies scholars. (shrink)

I thank Jane Sedlakova and Manuel Trachsel for their work on situating conversational artificial intelligence’s (CAI) potential role in psychotherapy. In their article, Sedlakova and Trachsel argue...

Applications of artificial intelligence/machine learning in health care are dynamic and rapidly growing. One strategy for anticipating and addressing ethical challenges related to AI/ml for health care is patient and public involvement in the design of those technologies – often referred to as ‘co-design’. Co-design has a diverse intellectual and practical history, however, and has been conceptualized in many different ways. Moreover, AI/ml introduces challenges to co-design that are often underappreciated. Informed by perspectives from critical data studies and (...) critical digital health studies, we review the research literature on involvement in health care, and involvement in design, and examine the extent to which co-design as commonly conceptualized is capable of addressing the range of normative issues raised by AI/ml for health care. We suggest that AI/ml technologies have amplified and modified existing challenges related to patient and public involvement, and created entirely new challenges. We outline three pitfalls associated with co-design for ethical AI/ml for health care and conclude with suggestions for addressing these practical and conceptual challenges. (shrink)

The article presents a new method for obtaining analogues of words, characterized by simplicity and the absence of the need for preliminary training on large data as in existing methods. In the method under study, analogues are determined by their syntactic predicates using methods of distributive semantics. In the study, analogues of adjectives, nouns and verbs were obtained and analyzed. This made it possible to obtain a result that is not inferior to the results obtained using the most popular neural (...) network approach as word2vec when qualitatively comparing analogues. The demonstrated method shows that obtaining analogues is possible using methods of distributive semantics using a more interpretable method, which opens up the possibility of studying semantic analogy. This method also allows you to identify analogues on a specific topic. Based on the experimental results obtained, an original definition of analogues and cognitive schemes is formulated. The article also analyzes and substantiates the possibility of a new approach for creating artificial intelligence systems based on the researched method. According to the authors, this provides significant advantages for the creation of such systems. In particular, the proposed method allows for broader generalizations over orders of magnitude smaller data, as well as learning during use, which is not possible for neural networks. (shrink)

What do we fear when we fear AI? This paper presents the claim that robophobia is autophobia, the fear of AI is the fear of ourselves, in at least two fashions. First, I frame the question in relation to what I call the Western machine-takeover imaginary, and identify two historical tracks: (1) the fear of non-human autonomy and (2) the logic of the genie. The first track is rooted in the idea of the domination of creations and their possible revolt, (...) a trope that reflects the anthropogenetic narratives that guide Western self-understanding. The second track establishes a link between cultural understanding of non-human, wish-fulfilling others, and modern AI drones and chatbots in terms of potential asymmetries between inputs and outputs, instructions and execution. When biased inputs inform system outputs that inform human inputs in a hermeneutical circle, the outputs we fear cannot be separated from the inputs we generate. (shrink)

This article is based on a roundtable held at the Association of Internet Researchers annual conference in 2017, in Tartu, Estonia. The roundtable was organized by the Oxford Internet Institute’s Digital Ethics Lab. It was entitled “Artificial Intelligence and the Good Society”. It brought together four scholars—Michael Zimmer, Stine Lomborg, Ben Zevenbergen, and Corinne Cath—to discuss the promises and perils of artificial intelligence, in particular what ethical frameworks are needed to guide AI’s rapid development and increased (...) use in societies. The paper covers three case studies. They give a distinct overview of the ethical issues raised by the use of AI at different levels of analysis: top-down application of AI, bottom-up use of AI, and how academics and governments have reacted to these new challenges. From the case studies, four areas emerged. They represent some of the most topical ethical questions related to AI: its uses, its users, its designers, and the data that fuel it. Each of them provided a specific subset of ethical concerns that need further investigation. In conclusion, three recommendations are formulated for researchers and regulators to ensure the AI has a net-positive impact on society. (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...

The study aims to identify the degree of possession of government school principals in the Karbala Governorate Education Directorate of artificial intelligence applications. The descriptive analytical approach was used. To achieve the study objectives, a questionnaire which contained (34) items was developed, divided into five dimensions. The study community was (114) male and female principals. The study sample consisted of (94) male and female managers, and the sample was selected randomly. The results of the study showed that the (...) degree of possession of government school principals in the Karbala Governorate Education Directorate of artificial intelligence applications was average. The results of the study also showed that there were no statistically significant differences at the significance level (α=0.05) attributed to the study variables (gender, academic qualification, experience in artificial intelligence techniques). In light of the study results, the researchers recommended several recommendations, most notably: paying attention to training courses in the field of information and communications technology, especially in the subject of artificial intelligence, by organizing meetings and workshops with the aim of raising awareness among individuals and society about the importance of artificial intelligence, encouraging the Iraqi Ministry of Education to its teaching staff and providing them with incentives to employ artificial intelligence applications in their administrative and educational work, introducing artificial intelligence applications into curricula and courses and paying attention to them, and providing specialized teaching staff in this field. (shrink)

The application of machine learning and artificial intelligence in healthcare domains has received much attention in recent years, yet significant questions remain about how these new tools integrate into frontline user workflow, and how their design will impact implementation. Lack of acceptance among clinicians is a major barrier to the translation of healthcare innovations into clinical practice. In this systematic review, we examine when and how clinicians are consulted about their needs and desires for clinical AI tools. Forty-five (...) articles met criteria for inclusion, of which 24 were considered design studies. The design studies used a variety of methods to solicit and gather user feedback, with interviews, surveys, and user evaluations. Our findings show that tool designers consult clinicians at various but inconsistent points during the design process, and most typically at later stages in the design cycle. We also observed a smaller amount of studies adopting a human-centered approach and where clinician input was solicited throughout the design process. A third of all studies reported on clinician trust in clinical AI algorithms and tools. The surveyed articles did not universally report validation against the “gold standard” of clinical expertise or provide detailed descriptions of the algorithms or computational methods used in their work. To realize the full potential of AI tools within healthcare settings, our review suggests there are opportunities to more thoroughly integrate frontline users’ needs and feedback in the design process. (shrink)

최근 인공지능(AI)은 인간의 사고와 행동을 모방하는 방식으로 빠르게 발전하고 있으며, 특히 딥러닝 기술의 발전은 AI가 인간 수준의 문제 해결과 창의적 작업을 수행할 가능성을 열어주고 있다. 그러나 현상학적 관점에서 볼 때,BR/AI는 본질적으로 인간과 다르며, 특히 ‘몸의 부재’라는 근본적인 한계를 지닌다. 본 논문은 허버트 드레이퍼스(Hubert L. Dreyfus)의 관점을 바탕으로 AI와 인간의 인식 방식의 본질적 차이를 분석한다. 드레이퍼스는 인간의 인지가 신체적 경험과 환경과의 상호작용 속에서 형성된다는 점에서 AI와 인간의 근본적인 차이를 강조한다. 다음으로 본 논문은 드레이퍼스의 논의뿐만 아니라 최근 현상학자들의 AI에 대한 분석을 검토함으로써, (...) AI가 인간과 구별되는 존재론적 차이를 해명하고, 체화된 경험이 지능 형성에서 차지하는 역할을 조명한다. 마지막으로, AI가 인간을 대체하는 것이 아니라 협력하는 방향으로 발전해야 한다는 점을 강조하며, 현상학이 AI 연구에 이바지할 수 있는 철학적 역할을 모색한다. (shrink)

With the rapid development of computer science and information technology, artificial intelligence has been developed from theory to application. As a key technology in the modern society, AI is increasingly affecting all aspects of people’s daily lives, including sports training. AI can be considered as an assistive technology to provide specific support to athletes’ physical education training through various means such as data analysis and simulation of training scenarios. Although research on AI is still in the preliminary stage, (...) it is significant to explore how AI can be applied in sports training since this emerging technology could facilitate people’s physical training to some extent. This paper first reviews the existing research on AI applications. Then, based on the fundamental concept and related research results of AI, this study explores three specific cases of AI application in sports training and explains the main principles. This research focuses on discussing the strong relationship between AI technology and physical education training and highlights the advantages of AI, including utilization, convenience, and innovation. (shrink)

The general idea that we have of artificial intelligence (AI) consists of the belief that machines will be able to develop conscious thoughts such as those possessed by human beings, and, as computing advances, such thinking will also advance until intelligence to surpass the human being, with which the advancement of AI represents ethical risks in the future. In reality, such a belief hides a cognitive assumption, which assumes that computational engineering explains human intelligence through the (...) mind-computer metaphor. According to this assumption, technology explains cognition, and philosophy, through ethics, reflects on the impact of said technology. However, in this article, I contradict such an assumption and defend that the philosophy in AI is not reduced to the ethics that is present after the use and impact of AI in the world. I intend to expose that a good ethics of AI is the one that reflects on the appropriate risks facing AI, and for this, philosophy, beforehand, must make a cognitive analysis about the possibilities that computing has to create intelligent machines, namely, whether or not the mindcomputer metaphor makes sense. My thesis consists in defending that the philosophical analysis about AI must be carried out both on a cognitive level and on an ethical level, but that the philosophical priority in the cognitive analysis over the ethical priority, since the ethical risks of AI depend of the possibilities of technology, and only the cognitive approach can account for this. (shrink)

The use of autonomous weaponry in warfare has increased substantially over the last twenty years and shows no sign of slowing. Our chapter raises a novel objection to the implementation of autonomous weapons, namely, that they eliminate moral cost-sharing. To grasp the basics of our argument, consider the case of uninhabited aerial vehicles that act autonomously (i.e., LAWS). Imagine that a LAWS terminates a military target and that five civilians die as a side effect of the LAWS bombing. Because LAWS (...) lacks moral agency, and in particular the capacity for moral emotions, moral cost-sharing is limited to dead civilians and their loved ones. We argue that's unjust insofar as those responsible for unjust harm to others ought to share in those costs. Our worry expands to other strategic uses of AI, e.g., cyber warfare. This presents a dilemma: Either we design autonomous weaponry capable of moral emotions, or we limit the use of autonomous weaponry. The former undermines the risk-mitigation purpose of creating autonomous weaponry and expands the number of sentient individuals whose welfare is risked in war. The latter risks worsening combatant casualties and achieving strategic aims. (shrink)

The article focuses on the inconsistency between the European Commission’s position on excluding military AI from its emerging AI policy, and at the same time EU policy initiatives targeted at supporting military and defence elements of AI on the EU level. It leads to the question, what, then, does the debate on military AI suggest to the EU’s actorness discussed in the light of Europe as a power debate with a particular focus on Normative Power Europe, Market Power Europe, and (...) Military Power Europe. By employing discourse analysis, the article examines the EU’s AI strategic discourse, consisting of selected AI-related policy documents from different EU institutions. As a result, the article proposes the Military Power Europe definition based on four categories proposed from the Europe as power debate: ways of action, self-definition, preferred international engagement, and the role of the military. It argues that alongside normative proposals for military AI governance, there are evident desires for militarization in the context of AI development, and a considerable role for the military in the future directions of the EU’s digital and security policies. Despite the inconsistency among EU institutions, military AI appears to be actively discussed within the selected discourse, and so is a part of the EU’s emerging AI policy. (shrink)

We discuss here one of our projects, aimed at developing an automatic facial expression interpreter, mainly in terms of signaled emotions. We present some of the relevant findings on facial expressions from cognitive science and psychology that can be understood by and be useful to researchers in Human-Computer Interaction and Artificial Intelligence. We then give an overview of HCI applications involving automated facial expression recognition, we survey some of the latest progresses in this area reached by various approaches (...) in computer vision, and we describe the design of our facial expression recognizer. We also give some background knowledge about our motivation for understanding facial expressions and we propose an architecture for a multimodal intelligent interface capable of recognizing and adapting to computer users¿ affective states. Finally, we discuss current interdisciplinary issues and research questions which will need to be addressed for further progress to be made in the promising area of computational facial expression recognition. (shrink)

Informal Logic, Argumentation Theory and Artificial Intelligence.

This review presents a state of the art in artificial intelligence applied to urban planning and particularly to land-use predictions. In this review, different articles after the year 2016 are analyzed mostly focusing on those that are not mentioned in earlier publications. Most of the articles analyzed used a combination of Markov chains and cellular automata to predict the growth of urban areas and metropolitan regions. We noticed that most of these simulations were applied in various areas of (...) China. An analysis of the publication of articles in the area over time is included. (shrink)

A groundbreaking endeavor that explores human spirituality using the evolving technology of artificial intelligence.

Sensation is the reflection of the brain on the individual attributes of objective things that directly act on the sense organs. Feeling is the most elementary cognitive process and the simplest psychological phenomenon. Vision is a kind of sense, and sense is produced by objective things acting on the sense organs. But at present, it is rare to analyze interior design exhibition from the perspective of visual psychology, an emerging science, as an interdisciplinary attempt, only in interior design research. Therefore, (...) the study of sensory process should start from its external stimuli, in order to first understand how it acts on the sensory organs to produce sensory phenomena. This paper mainly studies the visual performance of psychological factors in interior design under the background of artificial intelligence. This paper proposes a K-means clustering algorithm and a localization algorithm fused with visual and inertial navigation. The distance thresholds corresponding to the SIFT feature descriptors of threshold T1, 128D, 96D, 64D, and 32D are 170, 160, 150, and 90, respectively. This verifies that the candidate image with the highest number of matching points is considered the best matching image. (shrink)

Recently, Mr. Bauer (2020), CEO of BAM, a human resources service provider, reported about the introduction of a continuous change process using artificial intelligence. From this as a starting point, the article defines and discusses change processes, transformation management, and organisational development. The cudgels are taken up on behalf of the human-in-the-loop. It is argued, that the so-called “weak” artificial intelligence, including the human, is superior to the black box approach, hiding the system state as well (...) as its dynamics from the user and deciding itself. Long-sightedness and employee orientation as well as open communication was the key in Industry 1.0 and it still is in Industry 5.0. (shrink)

The ontological presupposition of artificial intelligence (AI) is the liberal autonomous human subject of Locke and Kant, and the ideology of AI is the automation of this particular conception of intelligence. This is demonstrated in detail in classical AI by the work of Simon, who explicitly connected his work on AI to a wider programme in cognitive science, economics, and politics to perfect capitalism. Although Dreyfus produced a powerful Heideggerian critique of classical AI, work on neural networks (...) in AI was ultimately based on the individual as the locus of intelligence. Yet this conception of AI both fails to grasp the essence of large language models, which are a statistical model of human language on the Web. The training data that enables AI is the surveillance and capture of data, where the data creates a model to approximate the entire world. However, there is a more hidden ideology inherent in AI where the goal is not to perfect a model but to control the world. As prompted by an argument between Mead and Bateson, social change is prevented by the application of cybernetics to society as a whole. The goal of AI is not just to replace human beings, but to manage humans to preserve existing power relations. As the source of intelligence in AI is distributed cognition between humans and machines, the alternative to AI is collective intelligence. As theorized by Licklider and Engelbart at the dawn of the Internet, collective intelligence explains how computers weave together both human and non-human intelligence. Rather than replace human intelligence, this produces ever more complex collective forms of intelligence. Rather than meta-stabilize a society of control, collective intelligence can go outside individualist capitalist ontology by incorporating the open world of the pluriverse, as theorized by Escobar. Collective intelligence then stands as an alternative ontological path for AI which puts intelligence at the service of humanity and the world rather than a technocratic elite. (shrink)

The article examines the problem of ensuring the political stability of a democratic social system with a shortage of a vital commodity (like vaccine against COVID-19). In such a system, members of society citizens assess the authorities. Thus, actions by the authorities to increase the supply of this commodity can contribute to citizens' approval and hence political stability. However, this supply is influenced by random factors, the actions of competitors, etc. Therefore, citizens do not have sufficient information about all the (...) possibilities of supplying, and it is difficult for them to make the right decisions. Such citizen unawareness can be exploited by unscrupulous politicians to achieve personal targets. Therefore, it is necessary to organize public control to motivate politicians to use all available opportunities in supplying. The goal of the paper is to build such a digital mechanism of public control of the politicians by citizens, which would best assess and stimulate the activities of the authorities to improve the supply of a vital commodity. In the age of artificial intelligence, such digital public control in the face of uncertainty can be based on digital machine learning. In addition, it is necessary to take into account and model the activities of politicians associated with the presence of their own targets that do not coincide with public ones. Such politicians can use the learning of citizens for their own targets. The objective of the article is to build an optimal digital mechanism of public control in a two-level model of a democratic social system—a digital society. At its top level, there is the Citizen, who gives an assessment for the Politico located at the lower level. In turn, the Politico can influence the supplying of a vital commodity. Political stability is guaranteed if the Citizen regularly approves of the Politico’s actions to increase this supply. However, the Politico may not use the opportunities available to him to offer a commodity to achieve a personal target. To avoid this, the Politico’s control mechanism is proposed. It includes the procedure for digital learning of the Citizen, as well as a procedure for assessing the Politico activity. Sufficient conditions have been found for the synthesis of such the Politico’s control mechanism, at which stochastic possibilities of increasing the supply of a vital commodity are used. The example of such the Politico’s control mechanism is considered on the case of supply of the COVID-19 vaccine in England. (shrink)

The central thesis of this paper is that human unconscious processes influence the behavior and design of artificial intelligence (AI). This thesis is discussed through the case study of a chatbot called Replika, which intends to provide psychological assistance and friendship but has been accused of inciting murder and suicide. Replika originated from a trauma and a work of mourning lived by its creator. The traces of these unconscious dynamics can be detected in the design of the app (...) and the narratives about it. Therefore, a process of de-psychologization and de-humanization of the unconscious takes place through AI. This psychosocial approach helps criticize and overcome the so-called “standard model of intelligence” shared by most AI researchers. It facilitates a new interpretation of some classic problems in AI, such as control and responsibility. (shrink)

Automation, artificial intelligence, and biotechnology have become topics of increasing interest in both academia as well as in popular media. The goal of this article is to establish which issues are the most pressing, and what are the underlying causes of the rise of robots. I demonstrate that fears of automation are well supported by current trends of automation as well as the inherent tendency within a capitalist system to automate at the expense of workers and working wages. (...) Additionally, I point to what appears to be a potential evolutionary divide between what Yuval Noah Harari calls the “god” class and the “useless” class. Finally, I discuss how the new role of information as the world’s most valued commodity can either exacerbate this coming divide or liberate society. I present the case that in order to diminish the negative effects we must move beyond the present capitalist economic system, towards one in which economic democracy and the free flow of information thrives. (shrink)

본 논문의 목적은 현재의 인공지능(artificial intelligence, 이하 AI) 윤리 논의에서 결여되어 있는 AI 개발자 윤리의 중요성과 필요성을 부각하고, AI 개발자 윤리로 덕성(virtue)기반의 모델이 적합함을 보여 이를 제안하는 것이다. AI는 고정된 과학기술이 아니라 발전노정에 있는 동적이라는 특성과 인간과의 상호작용에서 AI를 만든 인간의 삶에 지대한 영향을 끼치는 재귀적 특성이 있는 과학기술이다. 이러한 AI의 특성으로 인해, AI가 초래할 리스크에 대응하려는 AI 윤리는 발전 과정에 따라 제시되어야 한다는 점에서 체계적이고, 실천을 도모하는 동기부여의 구조를 가져야 한다는 점에서 기존 도덕의 형식적 특징인 1인칭, 2인칭, (...) 3인칭 관점이 통합될 필요가 있다. 그런데 최근에 활발하게 제시된 많은 AI윤리 지침에 대한 메타 분석에 따르면, 현재의 지침으로서의 AI 윤리 논의들은 1인칭 관점의 동기부여가 없는 3인칭 관점에만 한정되어 실질적인 ‘윤리 실현’(ethics realizing)을 도모하기에 취약하다. AI 윤리 지침 자체가 추상적이고 모호할 뿐만 아니라, AI를 개발하는 사람들에게 아무런 영향력을 행사하지 못하는 ‘윤리 세탁’(ethics washing)에 불과하기 때문이다. 이러한 한계를 보완하기 위해서는 AI 개발자들이 AI 윤리를 내면화하여 규범적으로 실천하게 할 수 있게 하는 AI 개발자 윤리가 필요한데, 본 논문은 덕성 기반의 AI 개발자 윤리가 이러한 목적을 위해 효과적이라고 주장한다. 덕성 기반의 AI 개발자 모델은, 과학적 덕성 모델(scientific virtue model)이 그랬던 것처럼 AI 개발의 목적이 무엇인지, AI개발자들의 전문직 덕성(vocational virtue)이 무엇인지, 그리고 이러한 덕성을 함양하기 위한 효과적인 교육 방법은 무엇인지 등의 이론 연구와 AI 개발자들과의 소통을 토대로 하는 경험 연구의 결합을 통해 실천적 차원의 모델로 구체화될 수 있다. 본 논문에서 이론적으로 제안하는 덕성 기반의 AI 개발자 윤리가 추후 한국 사회의 경험 연구를 통해 실천적 차원의 모델로 구체화되어 AI가 초래하는 윤리적 문제들에 효과적으로 대응하면서 AI의 혜택이 풍성히 향유되는데 기여하기를 기대한다. (shrink)

Future developments in artificial intelligence (AI) will likely allow for a greater degree of human‐machine convergence, with machines becoming more humanlike and intelligent machinery becoming more integrated into human brain function. This will pose many ethical challenges, and the necessity for a moral framework for evaluating these challenges will grow. This paper argues that community concern constitutes a central factor in both the evolution of religion and the human brain, and as such it should be used as the (...) organizing principle for moral evaluations of AI technologies. (shrink)

The purpose of this book, originally published in 1987, was to contribute to the advance of artificial intelligence by clarifying and removing the major sources of philosophical confusion at the time which continued to preoccupy scientists and thereby impede research. Unlike the vast majority of philosophical critiques of AI, however, each of the authors in this volume has made a serious attempt to come to terms with the scientific theories that have been developed, rather than attacking superficial 'straw (...) men' which bear scant resemblance to the complex theories that have been developed. For each is convinced that the philosopher's responsibility is to contribute from his own special intellectual point of view to the progress of such an important field, rather than sitting in lofty judgement dismissing the efforts of their scientific peers. The aim of this book is thus to correct some of the common misunderstandings of its subject. The technical term Artificial Intelligence has created considerable unnecessary confusion because of the ordinary meanings associated with it, and for that very reason, the term is endlessly misused and abused. The essays collected here all aim to expound the true nature of AI, and to remove the ill-conceived philosophical discussions which seek answers to the wrong questions in the wrong ways. Philosophical discussions and decisions about the proper use of AI need to be based on a proper understanding of the manner in which AI-scientists achieve their results; in particular, in their dependence on the initial planning input of human beings. The collection combines the Anglo-Saxon school of analytical philosophy with scientific and psychological methods of investigation. The distinguished authors in this volume represent a cross-section of philosophers, psychologists, and computer scientists from all over the world. The result is a fascinating study in the nature and future of AI, written in a style which is certain to appeal and inform laymen and specialists alike. has created considerable unnecessary confusion because of the ordinary meanings associated with it, and for that very reason, the term is endlessly misused and abused. The essays collected here all aim to expound the true nature of AI, and to remove the ill-conceived philosophical discussions which seek answers to the wrong questions in the wrong ways. Philosophical discussions and decisions about the proper use of AI need to be based on a proper understanding of the manner in which AI-scientists achieve their results; in particular, in their dependence on the initial planning input of human beings. The collection combines the Anglo-Saxon school of analytical philosophy with scientific and psychological methods of investigation. The distinguished authors in this volume represent a cross-section of philosophers, psychologists, and computer scientists from all over the world. The result is a fascinating study in the nature and future of AI, written in a style which is certain to appeal and inform laymen and specialists alike. inform laymen and specialists alike. (shrink)

1. WHAT IS ARTIFICIAL INTELLIGENCE? One of the fascinating aspects of the field of artificial intelligence (AI) is that the precise nature of its subject ..

Highly sophisticated capabilities of artificial intelligence (AI) have skyrocketed its popularity across many industry sectors globally. The public sector is one of these. Many cities around the world are trying to position themselves as leaders of urban innovation through the development and deployment of AI systems. Likewise, increasing numbers of local government agencies are attempting to utilise AI technologies in their operations to deliver policy and generate efficiencies in highly uncertain and complex urban environments. While the popularity of (...) AI is on the rise in urban policy circles, there is limited understanding and lack of empirical studies on the city manager perceptions concerning urban AI systems. Bridging this gap is the rationale of this study. The methodological approach adopted in this study is twofold. First, the study collects data through semi-structured interviews with city managers from Australia and the US. Then, the study analyses the data using the summative content analysis technique with two data analysis software. The analysis identifies the following themes and generates insights into local government services: AI adoption areas, cautionary areas, challenges, effects, impacts, knowledge basis, plans, preparedness, roadblocks, technologies, deployment timeframes, and usefulness. The study findings inform city managers in their efforts to deploy AI in their local government operations, and offer directions for prospective research. (shrink)

The potential societal impacts of automation using intelligent control and communications technologies have emerged as topics in a number of recent writings and public policy initiatives. Many of these expressions have referenced the writings and research efforts of Herbert Simon (1961), Norbert Wiener (1948), and contemporaries from their early technological and social vantage points concerning the future of technology and society. Constructed entities labeled as “thinking machines” (such as IBM’s Watson as well as intelligent chatbot and robotic systems) have also (...) played significant roles in this discourse. This paper provides an historical sequencing then analyzes a selection of writings produced since the 1940s concerning the economic and social issues involving artificial intelligence (AI) research and applications. The paper explores how overstatements and hyperbolic themes and concepts, often stemming from AI’s early periods, are being employed in characterizations of current AI approaches in apparently opportunistic attempts to provide rhetorical support for various large-scale business and societal initiatives. It also addresses the relative neglect of the consideration of many of AI’s sociotechnical failures and discontinued approaches in recent examinations of automation and social welfare issues. The paper discusses the moral logic of AI researchers and developers providing reasonable and measured narratives in public discourse rather than hyperbole, efforts that can empower decision makers to make sounder judgments concerning the technology’s current and future applications as well as allocate the rewards of the technology more equitably. (shrink)