Artificial intelligence (AI) national strategies provide countries with a framework for the development and implementation of AI technologies. Sixty countries worldwide published their AI national strategies. The majority of these countries with more than 70% are developed countries. The approach of AI national strategies differentiates between developed and developing countries in several aspects including scientific research, education, talent development, and ethics. This paper examined AI readiness assessment in a developing country (Palestine) to help develop and identify the main (...) pillars of the AI national strategy. AI readiness assessment was applied across education, entrepreneurship, government, and research and development sectors in Palestine (case of a developing country). In addition, it examined the legal framework and whether it is coping with trending technologies. The results revealed that Palestinians have low awareness of AI. Moreover, AI is barely used across several sectors and the legal framework is not coping with trending technologies. The results helped develop and identify the following five main pillars that Palestine’s AI national strategy should focus on: AI for Government, AI for Development, AI for Capacity Building in the private, public and technical and governmental sectors, AI and Legal Framework, and international Activities. (shrink)

This article examines the problem of the specificity and functions of mental control from two main perspectives: (1) from the standpoint of natural scientific explanation; (2) within a socio-psychological and socio-humanitarian context. The first approach employs an information-based framework to address the question of how phenomena of subjective reality can serve as causes of physical changes. The distinction between informational and physical causality is elucidated, providing a justification for psychic (mental) causality as a form of informational causality. Within this context, (...) the article discusses issues of information encoding and decoding, recent advances in neuroscience regarding the deciphering of brain codes for mental phenomena, and pertinent results from genomics. The author explores the significance of these developments for substantiating free will and self-determination processes, as well as for developing new artificial intelligence systems capable of emulating natural intelligence functions. Building upon these foundations, the second aspect of the discussion examines the role of mental control in interpersonal and mass communications, as well as in the functioning of institutional entities. To this end, the article investigates the relationships between individual consciousness and mass, institutional consciousness, the importance of national leadership in extreme situations, the phenomenon of polysubjectivity, and related questions concerning the optimal balance between centralization and autonomization of control mechanisms. The author demonstrates the inevitability of overcoming the principle of monopolarity, which inhibits autonomization functions and thereby undermines the foundations of global social self-organization. Finally, the article briefly addresses a number of salient issues pertaining to the meaning, objectives, and outcomes of mental control acts, as well as their socio-humanitarian implications and evaluation. (shrink)

National Artificial Intelligence (AI) strategies articulate imaginaries of the integration of AI into society and envision the governing of AI research, development and applications accordingly. To integrate these central aspects of national AI strategies under one coherent perspective, this paper presented an analysis of Germany’s strategy ‘AI made in Germany’ through the conceptual lens of ordoliberal political rationality. The first part of the paper analyses how the guiding vision of a human-centric AI not only adheres to ethical and (...) legal principles consistent with Germany’s liberal democratic constitutional system but also addresses the risks and promises inherent to the ordoliberal problematization of freedom. Second, it is scrutinized how the strategy cultivates the fear of not achieving technological sovereignty in the AI sector. Thereby, it frames the global AI race as a race of competing (national) approaches to governing AI and articulates an ordoliberal approach to governing AI (the ‘third way’), according to which government has to operate between the twin dangers of governing too much and not governing enough. Third, the paper analyses how this ordoliberal proportionality of governing structures Germany’s Science Technology & Innovation Policy. It is shown that the corresponding risk-based approach of regulating AI constitutes a security apparatus as it produces an assessment of fears: weighting the fear of the failure to innovate with the fear of the ramifications of innovation. Finally, two lines of critical engagement based on this analysis are conducted. (shrink)

The topic of the impact of artificial intelligence on law, the legal profession and legal culture, in general, has not yet been sufficiently discussed in the Croatian scientific community. This paper aims to encourage a more comprehensive analysis of the relationship between the increasing use of artificial intelligence in our daily lives and the specifics of practising the legal profession in such an environment. Artificial intelligence is still a broad and heterogeneous field. It is (...) therefore justified to ask the question: Which of the many technologies currently being developed can be applied in the field of law? Which legal matters can be “entrusted” to the new technologies? To answer such and similar questions, it is necessary to have an excellent knowledge of both artificial intelligence and the law, as well as the areas in which they intersect. We have chosen criminal law, which is a part of public law and the ultimate social mechanism for responding to undesirable behaviour, as our object of study. We pay particular attention to its two important aspects: the element of culpability in a criminal offence and the possibility of autonomous decision-making in criminal law. The reflections have shown that Croatian criminal law may have the ability and potential to adapt to the challenges of artificial intelligence when it comes to culpability. On the other hand, the necessity and value of artificially intelligent decisions are questionable given the fundamental characteristics of criminal law. In conclusion, the authors express a departure from views of artificial intelligence as a decision-making substitute in criminal law but support the view that artificially intelligent legal technologies are an aid to decision-making. (shrink)

Artificial Intelligence (AI) in the 21st century is no longer perceived as a purely technological phenomenon, more and more becoming a social and humanitarian phenomenon that develops in a complex context of cultural, value, philosophical, and ethical aspects of human life. The impact of AIrelated technologies on contemporary society is still difficult to assess fully, which does not prevent enthusiastic researchers and political leaders from attempting to define a value framework that will ensure the use of AI (...) for societal development. As interest in AI grows, more and more technologically advanced countries in the world are creating their own strategies for the development and use of this technological marvel of the 21st century. These pioneering documents often seem vague and indefinite, but nevertheless they allow us to assess how the political and scientific and technological elites of these countries see the value orientations of AI technology development, both nationally and internationally. The article presents a philosophical analysis of the value orientations of AI technology development in the USA and China – modern scientific and technological leaders in this field – on the basis of strategic documents defining the development and application of AI in these countries from the position of post-non-classical scientific rationality. The authors of the article conclude that, at the contemporary post-non-classical stage of science development, the value component is not only one of the integral components of scientific and technological activities but may be decisive in determining the goals and objectives of high-tech development at the state level. (shrink)

Moving from a behavioral definition of intelligence, which describes it as the ability to adapt to the surrounding environment and deal effectively with new situations (Anastasi, 1986), this paper explains to what extent the performance obtained by ChatGPT in the linguistic domain can be considered as intelligent behavior and to what extent they cannot. It also explains in what sense the hypothesis of decoupling between cognitive and problem-solving abilities, proposed by Floridi (2017) and Floridi and Chiriatti (2020) should be (...) interpreted. The problem of symbolic grounding (Harnad, 1990) is then addressed to show the problematic relationship between ChatGPT and the natural environment, and thus the impossibility for it to understand the symbols it manipulates. To explain the reasons why ChatGPT does not succeed in this task, an investigation is carried out and a possible solution to the problem in the artificial domain is proposed by making a comparison with the natural ability of living beings to ground their own meanings from some basic cognitive-sensory aspects, which, it is explained, are directly related to the emergence of self-awareness in humans. Thus, the question is raised whether a possible and concrete solution to the Symbol Grounding Problem would involve in the artificial domain the development of cognitive abilities fully comparable to those of humans. Finally, I explain the difficulties that would have to be overcome before such a level could be reached, since human cognitive capacities are intimately linked to intersubjectivity and intercorporeality. (shrink)

Before embarking on a discussion of the regulation of artificial intelligence (AI), it is first necessary to define the subject matter regulated. Defining artificial intelligence is a difficult endeavour, and many definitions have been proposed over the years. Although more than 70 years have passed since it was adopted, the most convincing definition is still nonetheless that proposed by Turing; in any case, it is important to be mindful of the risk of anthropomorphising artificial (...) class='Hi'>intelligence, which may arise in particular from its very definition. Once we have established the subject matter regulated, we must ask ourselves whether lawmakers should pursue an approach that seeks to regulate artificial intelligence as a whole, or whether by contrast they should regulate applications of artificial intelligence in specific sectors or individual areas. The proposal for a regulation on artificial intelligence published on 21 April 2021 implements the former approach whilst also pursuing geopolitical goals. After providing an initial overview of the notion of artificial intelligence, this article investigates the geopolitical context to the proposal for a regulation, and then goes on to illustrate the regulatory model embraced by the proposal as well as related critical aspects. (shrink)

The subject of this study is the participants in artificial sociality (humans and artificial intelligence (AI) tools) and communication between them. The first section analyses (using Luhmann’s methodology) communication as the basis of sociality. The second section shows how AI tools became social technologies in the framework of artificial sociality. The third section describes experimental communication between authors and AI tools (the case of ChatGPT). For the first time in the Baltic countries, the authors examined (...) sociological, humanitarian, natural and technological aspects of the functioning AI tools, which participate in creation of a new social reality for human society – artificial sociality. (shrink)

How would it be assessed from an ethical point of view if human wage work were replaced by artificially intelligent systems (AI) in the course of an automation process? An answer to this question has been discussed above all under the aspects of individual well-being and social justice. Although these perspectives are important, in this article, we approach the question from a different perspective: that of leading a meaningful life, as understood in analytical ethics on the basis of the (...) so-called meaning-in-life debate. Our thesis here is that a life without wage work loses specific sources of meaning, but can still be sufficiently meaningful in certain other ways. Our starting point is John Danaher’s claim that ubiquitous automation inevitably leads to an achievement gap. Although we share this diagnosis, we reject his provocative solution according to which game-like virtual realities could be an adequate substitute source of meaning. Subsequently, we outline our own systematic alternative which we regard as a decidedly humanistic perspective. It focuses both on different kinds of social work and on rather passive forms of being related to meaningful contents. Finally, we go into the limits and unresolved points of our argumentation as part of an outlook, but we also try to defend its fundamental persuasiveness against a potential objection. (shrink)

Ethically significant consequences of artificially intelligent artifacts will stem from their effects on existing social relations. Artifacts will serve in a variety of socially important roles—as personal companions, in the service of elderly and infirm people, in commercial, educational, and other socially sensitive contexts. The inevitable disruptions that these technologies will cause to social norms, institutions, and communities warrant careful consideration. As we begin to assess these effects, reflection on degrees and kinds of social agency will be (...) required to make properly informed decisions concerning the deployment of artificially intelligent artifacts in important settings. The social agency of these systems is unlike a human social agency, and this paper provides a methodological framework that is more suited for inquiry into artificial social agents than conventional philosophical treatments of the concept of agency. Separate aspects and dimensions of agency can be studied without assuming that agency must always look like adult human agency. This revised approach to the agency of artifacts is conducive to progress in the topics studied by AI ethics. (shrink)

Our social relations are changing, we are now not just talking to each other, but we are now also talking to artificial intelligence (AI) assistants. We claim AI assistants present a new form of digital connectivity risk and a key aspect of this risk phenomenon is related to user risk awareness (or lack of) regarding AI assistant functionality. AI assistants present a significant societal risk phenomenon amplified by the global scale of the products and the increasing use (...) in healthcare, education, business, and service industry. However, there appears to be little research concerning the need to not only understand the changing risks of AI assistant technologies but also how to frame and communicate the risks to users. How can users assess the risks without fully understanding the complexity of the technology? This is a challenging and unwelcome scenario. AI assistant technologies consist of a complex ecosystem and demand explicit and precise communication in terms of communicating and contextualising the new digital risk phenomenon. The paper then argues for the need to examine how to best to explain and support both domestic and commercial user risk awareness regarding AI assistants. To this end, we propose the method of creating a risk narrative which is focused on temporal points of changing societal connectivity and contextualised in terms of risk. We claim the connectivity risk narrative provides an effective medium in capturing, communicating, and contextualising the risks of AI assistants in a medium that can support explainability as a risk mitigation mechanism. (shrink)

This study aims to identify artificial intelligence (AI) technologies that are applied in climate-smart agricultural practices and address ethical concerns of deploying those technologies from legal perspectives. As climate-smart agricultural AI, the study considers those AI-based technologies that are used for precision agriculture, monitoring peat lands, deforestation tracking, and improved forest management. The study utilized a systematic literature review approach to identify and analyze AI technologies employed in climate-smart agriculture and associated ethical and legal concerns. The study findings (...) indicate several ethical concerns for deploying AI in climate-smart agricultural practices pertaining to data inaccuracy, other technical errors based on wrong recommendations or wrongful acts, data ownership and intellectual property issues, and economic issues resulting in digital division and privacy and security related issues. In this study, the ethical concerns were further examined based on criminal law, tort law, privacy and data protection law, and intellectual property law. In this regard, the study finds that the current tort law pattern is more suitable than the criminal law pattern to address some major ethical concerns, such as data inaccuracy and other technical errors based on wrong recommendations or wrongful acts. Finally, the study recommends that at the global level, all countries need to fill up the current gap of international law on climate-smart agriculture through agreeing on a standard set of legal provisions and enhancing collaboration in innovation and deployment of climate-smart agricultural AI. It further recommends that at the local level, countries need to adopt suitable regulations addressing multi-stakeholders’ interests associated with the deployment of climate-smart agricultural AIs. (shrink)

This paper looks at philosophical questions that arise in the context of AI alignment. It defends three propositions. First, normative and technical aspects of the AI alignment problem are interrelated, creating space for productive engagement between people working in both domains. Second, it is important to be clear about the goal of alignment. There are significant differences between AI that aligns with instructions, intentions, revealed preferences, ideal preferences, interests and values. A principle-based approach to AI alignment, which combines these elements (...) in a systematic way, has considerable advantages in this context. Third, the central challenge for theorists is not to identify ‘true’ moral principles for AI; rather, it is to identify fair principles for alignment that receive reflective endorsement despite widespread variation in people’s moral beliefs. The final part of the paper explores three ways in which fair principles for AI alignment could potentially be identified. (shrink)

“Nature-inspired” approaches, with their potential to generate innovative ideas through technology, are expected to surpass current architectural requirements and significantly influence future-oriented designs. A new agenda within the discipline of architecture involves production with artificial intelligence. Within this context, the question, “Can a design product be created by combining the principles of biomimicry and futuristic architecture?” is explored through AI’s capability to autonomously generate multiple architectural form alternatives. The objective is to develop a novel methodology. In the context (...) of futurism, which emphasizes the concept of speed in artistic approaches, this study aims to conceptually discuss the role of AI—collective digital environments that transform traditional design processes—in architectural design. The research findings highlight the importance of experimental design exercises in aiding students to understand AI, stressing the need for this comprehension to go beyond merely mastering the technical aspects of AI. (shrink)

Some artificial intelligence systems can display algorithmic bias, i.e. they may produce outputs that unfairly discriminate against people based on their social identity. Much research on this topic focuses on algorithmic bias that disadvantages people based on their gender or racial identity. The related ethical problems are significant and well known. Algorithmic bias against other aspects of people’s social identity, for instance, their political orientation, remains largely unexplored. This paper argues that algorithmic bias against people’s political (...) orientation can arise in some of the same ways in which algorithmic gender and racial biases emerge. However, it differs importantly from them because there are strong social norms against gender and racial biases. This does not hold to the same extent for political biases. Political biases can thus more powerfully influence people, which increases the chances that these biases become embedded in algorithms and makes algorithmic political biases harder to detect and eradicate than gender and racial biases even though they all can produce similar harm. Since some algorithms can now also easily identify people’s political orientations against their will, these problems are exacerbated. Algorithmic political bias thus raises substantial and distinctive risks that the AI community should be aware of and examine. (shrink)

Over the coming decades, Artificial Intelligence will profoundly impact the way we live, work, wage war, play, seek a mate, educate our young, and care for our elderly. It is likely to greatly increase our aggregate wealth, but it will also upend our labor markets, reshuffle our social order, and strain our private and public institutions. Eventually it may alter how we see our place in the universe, as machines pursue goals independent of their creators and outperform (...) us in domains previously believed to be the sole dominion of humans. Whether we regard them as conscious or unwitting, revere them as a new form of life or dismiss them as mere clever appliances, is beside the point. They are likely to play an increasingly critical and intimate role in many aspects of our lives. The emergence of systems capable of independent reasoning and action raises serious questions about just whose interests they are permitted to serve, and what limits our society should place on their creation and use. Deep ethical questions that have bedeviled philosophers for ages will suddenly arrive on the steps of our courthouses. Can a machine be held accountable for its actions? Should intelligent systems enjoy independent rights and responsibilities, or are they simple property? Who should be held responsible when a self-driving car kills a pedestrian? Can your personal robot hold your place in line, or be compelled to testify against you? If it turns out to be possible to upload your mind into a machine, is that still you? The answers may surprise you. (shrink)

As artificial intelligence (AI) continues to advance, one key challenge is ensuring that AI aligns with certain values. However, in the current diverse and democratic society, reaching a normative consensus is complex. This paper delves into the methodological aspect of how AI ethicists can effectively determine which values AI should uphold. After reviewing the most influential methodologies, we detail an intuitionist research agenda that offers guidelines for aligning AI applications with a limited set of reliable moral intuitions, each (...) underlying a refined cooperative view of AI. We discuss appropriate epistemic tools for collecting, filtering, and justifying moral intuitions with the aim of reducing cognitive and social biases. The proposed methodology facilitates a large collective participation in AI alignment, while ensuring the reliability of the considered moral judgments. (shrink)

The growing advancement of Artificial Intelligence models based on deep learning and the consequent popularization of large language models (LLMs), such as ChatGPT, place the academic community facing unprecedented dilemmas, in addition to corroborating questions involving research activities and human beings. In this work, Content Analysis was chosen as the object of study, an important technique for analyzing qualitative data and frequently used among Brazilian researchers. The objective of this work was to compare the process of categorization by (...) themes carried out by human researchers on material from the Educational area, at the end of 2022, with the help of the ATLAS.TI software and the same process of categorization by themes, now carried out by the version 2023 of the ATLAS.TI software, carried out in an automated way by Artificial Intelligence, for the same material. Through lexical and semantic analysis, the themes used in the two processes were compared, observing similarities and differences between the two proposals, and verifying the consistency between the two analyses. The main result of this study is the difficulty of Artificial Intelligence in carrying out a broader categorization, eliminating specificities that were considered irrelevant by the authors for understanding the material. It is concluded, therefore, that the automated categorization process proposed by ATLAS.TI through Natural Language Processing (NLP) is consistent from a lexical point of view but is still insufficient from a semantic aspect. (shrink)

In current philosophical research the term 'philosophy of social action' can be used - and has been used - in a broad sense to encompass the following central research topics: 1) action occurring in a social context; this includes multi-agent action; 2) joint attitudes (or "we-attitudes" such as joint intention, mutual belief) and other social attitudes needed for the explication and explanation of social action; 3) social macro-notions, such as actions performed by social groups (...) and properties of social groups such as their goals and beliefs; 4) social norms and social institutions (see Tuomela, 1984, 1995). The theory of social action understood analogously in a broad sense would then involve not only philosophical but all other relevant theorizing about social action. Thus, in this sense, such fields of Artificial Intelligence (AI) as Distributed AI (DAI) and the theory of Multi-Agent Systems (MAS) fall within the scope of the theory of social action. DAI studies the social side of computer systems and includes various well-known areas ranging from Human Computer Interaction, Computer-Supported Cooperative Work, Organizational Processing, Distributed Problem Solving to Simulation of Social Systems and Organizations. Even if I am a philosopher with low artificial intelligence I will below try to say something about what the scope of DAI should be taken to be on conceptual and philosophical grounds. (In the later sections of the paper the central notion of joint intention will be the main topic - in order to illustrate how philosophers and DAI-researchers approach this issue.) Let us now consider the relationship between philosophy - especially philosophy of social action - and DAI. Both are concerned with social matters and in this sense seem to have a connection to social science proper. What kinds of questions should these areas of study be concerned with? In principle, ordinary social science should study all aspects of social life (in various societies and cultures), try to describe it and create general theories to explain it. (shrink)

Artificial Intelligence (AI) pervades humanity in 2022, and it is notoriously difficult to understand how certain aspects of it work. There is a movement—_Explainable_ Artificial Intelligence (XAI)—to develop new methods for explaining the behaviours of AI systems. We aim to highlight one important philosophical significance of XAI—it has a role to play in the elimination of vagueness. To show this, consider that the use of AI in what has been labeled _surveillance capitalism_ has resulted in humans (...) quickly gaining the capability to identify and classify most of the occasions in which languages are used. We show that the knowability of this information is incompatible with what a certain theory of vagueness—_epistemicism_—says about vagueness. We argue that one way the epistemicist could respond to this threat is to claim that this process brought about the end of vagueness. However, we suggest an alternative interpretation, namely that epistemicism is false, but there is a weaker doctrine we dub _technological epistemicism_, which is the view that vagueness is due to ignorance of linguistic usage, but the ignorance can be overcome. The idea is that knowing more of the relevant data and how to process it enables us to know the semantic values of our words and sentences with higher confidence and precision. Finally, we argue that humans are probably not going to believe what future AI algorithms tell us about the sharp boundaries of our vague words unless the AI involved can be explained in terms understandable by humans. That is, if people are going to accept that AI can tell them about the sharp boundaries of the meanings of their words, then it is going to have to be XAI. (shrink)

The contemporary digital reality is inconceivable without artificial intelligence (AI), which has become disseminated across all cultural practices, from scientific and artistic endeavors to everyday activities. AI increasingly functions as an agent of communication and decision-making, gradually surpassing human capabilities across nearly all competencies. The information flows of this new reality can only be navigated through hybrid systems based on post-critical rationality, which inherently introduces an irreducible element of uncertainty and risk in human-machine environments. The article proposes examining (...) the techno-subject through the lens of activity theory and the multiple types of rationality it generates. This framework facilitates the analysis of sociocultural and anthropological implications arising from AI’s integration with human domains, while addressing the existential challenges inherent in constructing a harmonious hybrid society. Beyond V.S. Stepin’s types of scientific rationality, the author builds upon previously introduced forms of rationality: post-critical, object-oriented, instrumental, subjective, results-oriented, creative, and autopoietic. This theoretical framework facilitates a substantive discussion of various manifestations of AI subjectivity, including its generalized embodiment and creative specificity. The demarcation of dominance domains between natural intelligence and AI in the intellectual sphere is proposed to be resolved on the basis of their heuristic potentials. The author maintains that natural intelligence invariably possesses superior capacity in this regard. The article examines approaches to risk assessment in AI implementation strategies, focusing on criteria for preserving anthropological and sociocultural profiles in the development of hybrid society. Advancing the concept of friendly AI is substantiated as essential, with consideration given not only to technological but also to anthropological aspects of human–machine interaction. The author advocates for the development of social examination institutions as regulatory mechanisms for natural–artificial intelligence interaction and anthropological–technological subject interfaces. (shrink)

I develop a multilevel, holistic view of persons, emphasizing embodiment, emotions, consciousness, and the social self. In successive sections I draw from six sources: 1. Theology. The biblical understanding of the unitary, embodied, social self gave way in classical Christianity to a body‐soul dualism, but it has been recovered by many recent theologians. 2. Neuroscience. Research has shown the localization of mental functions in regions of the brain, the interaction of cognition and emotion, and the importance of (...) class='Hi'>social interaction in evolutionary history and child development. 3. Artificial intelligence. Some forms of robotics use embodied systems that learn by interacting with their environment, but the possibilities for emotion, socialization, and consciousness in robots remain problematic. 4. Relations between levels. Concepts that can help us relate studies of neurons and persons include the hierarchy of levels, the communication of information, thebehavior of dynamic systems, and epistemological and ontological emergence. 5. Philosophy of mind. Two‐aspect theories of the mind‐brain relation offer an alternative between the extremes of eliminative materialism and the thesis that consciousness is irreducible. 6. Process philosophy. I suggest that process thought provides a coherent philosophical framework in which these themes can be brought together. It combines dipolar monism with organizational pluralism, and it emphasizes embodiment, emotions, a hierarchy oflevels, and the social character of selfhood. (shrink)

The purpose of the study was to analyse the influence of artificial intelligence on modern socio-cultural processes to identify key trends and factors determining its development, to reveal positive and negative aspects of the integration of artificial intelligence into various spheres of public life, including work, education, medicine, and cultural and social relationships. A methodology has been developed that defines the stages of analysing the socio-cultural impact of artificial intelligence. The main trends determining (...) the influence of artificial intelligence on modern socio-cultural processes were identified, which included automation of labour, changes in educational and medical practices, and the impact on cultural and social relationships. This provided an understanding of how the development of artificial intelligence leads to changes in the world of work, including the automation of routine tasks, the consequences for the labour market and employment. The use of artificial intelligence has changed teaching methods and educational programmes, and influenced schoolchildren, teachers, and educational institutions. The paper provided a comprehensive description of society’s perception of the use of artificial intelligence, revealing both its positive and negative aspects. The positive aspects included increased productivity, increased innovation, and improved services, while the negative aspects covered job losses, data privacy concerns, and ethical issues. The results showed that the integration of artificial intelligence into modern socio-cultural processes has significantly influenced society. The study identified a number of issues and challenges, including potential job losses, data privacy issues, and ethical issues. (shrink)

The object of the study is artificial intelligence technology in Chinese show business. The subject of the study is the following technologies of Chinese show business, at the basis of which we can find an artificial intelligence: virtual idols, digital avatars, virtual influencers. The following aspects of these technologies are considered in detail: making a profit, strengthening national identity. Special attention is focused on the fact that the development of artificial intelligence technology is part (...) of the state policy of the People's Republic of China, which is reflected in the country's regulatory legal acts. The theoretical basis of the study is the work of the following authors: A.M. Gridnev, G. A. Ioakimidi, M. D. Pysin, K. F. Lee, H. Khan and others. The following methods are used in the article: analysis of special literature, publications of mass media, normative legal acts, synthesis, deduction. The study showed that virtual idols and influencers such as "Xiangwan Big Devil", digital copies of celebrities (B. Sa, S. Zhu, B. Gao, Ya. Long) and presenter Xiao Xi bring additional profits and attract an audience, as well as strengthen the national image and unity of China. The scientific novelty of this study lies in the detailed systematization of information and cultural analysis of the phenomenon of "virtual influencer", which is gaining popularity in the modern digital world. The results of the study provide valuable data for the development and implementation of artificial intelligence strategies in China, especially in such areas as industry, defense, social sphere and show business. These findings contribute to the formation of standards and ethical principles for artificial intelligence, which is critically important for the successful digital transformation of the country. The study highlights China's strategic goals of using AI as a driver of modernization of the national economy by 2030. The document identifies key stages of development and goals, including the development of standards and the widespread introduction of AI in various sectors. China views AI as an important tool to strengthen its position on the world stage, striving to become a leader in high technology, which will undoubtedly have a significant impact on the global economy and the development of technological innovations. (shrink)

Most accounts of responsibility focus on one type of responsibility, moral responsibility, or address one particular aspect of moral responsibility such as agency. This article outlines a broader framework to think about responsibility that includes causal responsibility, relational responsibility, and what I call “narrative responsibility” as a form of “hermeneutic responsibility”, connects these notions of responsibility with different kinds of knowledge, disciplines, and perspectives on human being, and shows how this framework is helpful for mapping and analysing how artificial (...) intelligence (AI) challenges human responsibility and sense-making in various ways. Mobilizing recent hermeneutic approaches to technology, the article argues that next to, and interwoven with, other types of responsibility such as moral responsibility, we also have narrative and hermeneutic responsibility—in general and for technology. For example, it is our task as humans to make sense of, with and, if necessary, against AI. While from a posthumanist point of view, technologies also contribute to sense-making, humans are the experiencers and bearers of responsibility and always remain in charge when it comes to this hermeneutic responsibility. Facing and working with a world of data, correlations, and probabilities, we are nevertheless condemned to make sense. Moreover, this also has a normative, sometimes even political aspect: acknowledging and embracing our hermeneutic responsibility is important if we want to avoid that our stories are written elsewhere—through technology. (shrink)

Any first step in organisational adaptation starts with individuals’ responses and willingness (or otherwise) to change an aspect of themselves given the transcontextual settings in which they are operating (Bateson in Small arcs of larger circles: framing through other patterns, Triarchy Press, Axminster, 2018). This research explores the implications for organisational adaptation strategies when Artificial Intelligence (AI) is being embedded into the ecology of the organisation, and when employees have a dominant fixed or growth mindset (Dweck in Mindset: (...) changing the way you think to fulfil your potential. Robinson, London, 2017). Research participants were supplied with a single scenario based in 2030, where—as a result of Artificial Intelligence technology implementation—employees were going to be displaced. Using Torbert’s (Organizational wisdom and executive courage, New Lexington Press, San Francisco, 1998) ‘first, second and third person’ research theory, participants were asked to independently review their thoughts, sense, and image of the future from a fixed mindset position (considered to be the worst case), then from a growth mindset perspective (best case), and then do the same collectively. Five key findings are outlined which support the principle that having a growth mindset is a key component of adaptive capacity and futures literacy. The five key findings conclude that AI adaptation processes need to include compassion and authenticity, embodiment, fundamental needs and motivations, mutual learning and considering what lies beyond the edges of the organisation (Bateson in Small arcs of larger circles: framing through other patterns, Triarchy Press, Axminster, 2018). (shrink)

Artificial Intelligence and Music Ecosystem highlights the opportunities and rewards associated with the application of AI in the creative arts. Featuring an array of voices, including interviews with Jacques Attali, Holly Herndon and Scott Cohen, this book offers interdisciplinary approaches to pressing ethical and technical questions associated with AI. Considering the perspectives of developers, students and artists, as well as the wider themes of law, ethics and philosophy, Artificial Intelligence and Music Ecosystem is an essential introduction (...) for anyone interested in the impact of AI on music, including those studying and working in the creative arts. (shrink)

Throughout Mary Shelley’s early life, she was exposed to numerous well-known and influential people regarding cultural, political, and socio-economic matters. As she began writing, these influences undoubtedly played a role in her narrative. Her novel, _Frankenstein_, written during the time of the first Industrial Revolution in Britain, was one such novel that exhibited her political and economic influences through science fiction. This article addresses many of those influences, including the introduction of the machine into manufacturing. It further addresses how Frankenstein’s (...) Monster may have been one of the first created forms of artificial intelligence (AI). We further expound upon many economic concepts that have persisted through time and are relevant today given the faciliatory aspects, as well as the uncertainty, of AI. We relate these through the literary piece _Frankenstein_ to explore how a two-century-year-old tale provides a blueprint for understanding the conflict among humans and machines and provides a roadmap for harmonization in the past, present, and future. (shrink)

The paper analysis the strategies and concepts developed in the world in modern directions: innova- tive economy, digital economy, artificial intelligence, Industry 4.0 and others. The problem is to determine the initial fundamental parameters of order and their prospects in the global world, the definition and principles of artificial intel- ligence systems, its structure and important aspects and principles of future science and technology in analysis and synthesis based on synergetic approaches, innovative, information, converged technologies, taking into (...) account the design of future and viable and safe and sustainable development in the context of Industry 4.0, digital economy and Society 5.0. The general scheme of the integrated model of sustainable and socio-humanitarian development in the global system is proposed, which the authors call the noosphere model of sustainable and safe development as an important fundamental platform for the design and creation of AIS. In the XXI century education, science and innova- tive technologies becomes the «basis» of the spiritual and material reproduction of man, transforming the society of the XXI century into an educational society, ensures compliance with the law of advanced development of human quality, quality of social intelligence and quality of educational systems in society. noosphere evolution. Industry 4.0 is the next stage in the digitalization of production technologies with the accelerated introduction of new developments and cyberphysical systems, which is changing business models. Accordingly, Industry 4.0 as a separate segment of digital manufacturing technologies takes its place among other digital sectors. The analysis of the Strategies and Concepts developed in the world in modern directions: innovative economy, digital economy, artificial intelli- gence, Industry 4.0 and others is carried out in the work. The problem is to determine the initial fundamental para- meters of order and their prospects in the global world, the definition and principles of artificial intelligence systems, its structure and important aspects and principles of future science and technology in analysis and synthesis ba- sed on synergetic approaches, innovative, information, converged technologies, taking into account the design of future and viable and safe and sustainable development in the context of Industry 4.0, DE and Society 5.0. The main scientific and technological factors in the 21st century will be the development of: Artificial Intelligence, Nano Technologies, Bio-Media Technologies, Cognitive Technologies and Socio-Humanitarian Technologies. More specifically – this is the modern development of Innovative Technologies: «NBIC SH». Therefore, it is necessary to note the importance of taking into account the principle of I2K2+SH, ie: Intellectualization, Integration, Convergence, Coevolution and Socio- humanitarian technologies. It is important and necessary to take into account modern principles of designing a su- stainable and secure AIS and solving the problem of Harmonization between 2 worlds: Real and Virtual, especially in their hybridization. Our immediate future is a hybrid nonlinear world. Note that digitalization, artificial intelligence and robotics will be the main drivers of global economic growth by 2030E. An important paradigm and platform is the Integrated System: for Industry 4.0, DE and AI, taking into account the complex principle of I2K2+SH. If the transition of the Ukrainian economy to an innovative one does not take place in the next 3-5 years, Ukraine will remain in the backyard of civilization. (shrink)

At present, although artificial intelligence (AI) has made great progress in the aspects of control policy and operation, there is still no unified ethical decision mode, laws and regulations in ethical dilemma, which seriously affect application and development of artificial intelligence. Therefore, this paper studies and analyzes various ethical decision mode of AI system, then the current research status and advantages, deficiencies of these decision modes are analyzed and summarized. According to the characteristics of the current (...) ethical decision modes and existing problems, the future implementation mode for the future ethical decision of artificial intelligence is explored and discussed. A hierarchical hybrid ethical decision mode will be proposed and designed, which has the advantages of the existing ethical decision modes. In addition, it will provide a few references for research, design and formulation of laws, regulations of AI. (shrink)

Information technology is so ubiquitous and AI’s progress so inspiring that also legal professionals experience its benefits and have high expectations. At the same time, the powers of AI have been rising so strongly that it is no longer obvious that AI applications (whether in the law or elsewhere) help promoting a good society; in fact they are sometimes harmful. Hence many argue that safeguards are needed for AI to be trustworthy, social, responsible, humane, ethical. In short: AI should (...) be good for us. But how to establish proper safeguards for AI? One strong answer readily available is: consider the problems and solutions studied in AI & Law. AI & Law has worked on the design of social, explainable, responsible AI aligned with human values for decades already, AI & Law addresses the hardest problems across the breadth of AI (in reasoning, knowledge, learning and language), and AI & Law inspires new solutions (argumentation, schemes and norms, rules and cases, interpretation). It is argued that the study of AI as Law supports the development of an AI that is good for us, making AI & Law more relevant than ever. (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)

With the rapid development of the Internet and smart phone technology, a large number of short videos are shared through social platforms. Therefore, video content analysis is a very important and popular work in machine learning and artificial intelligence currently. However, it is very difficult to analyze all aspects of video content originally produced by large-scale users. How to screen out bad and illegal content from short videos published by a large number of users, select high-quality videos (...) to share with other users, and improve the quality of video on the distribution platform of the entire user is a top priority. Based on this background, this paper focuses on optimizing video auditing to provide basic features for algorithm judgment, supporting original content and increasing the distribution of new content, and strengthening manual intervention combining algorithm recommendation with manual recommendation. Four major aspects of the artificial training algorithm model discuss the optimization effect of artificial intelligence on the algorithm in order to provide some guidance for the sustainable and healthy development of mobile short video. (shrink)

With the increasingly serious employment situation in China, the government and schools encourage college students to start businesses to alleviate employment pressure. College student's successful entrepreneurship depends on national preferential policies, social support, and, most importantly, their healthy and solid psychological quality and entrepreneurial psychological quality. The purpose is to understand the entrepreneurial psychology of college students and study the entrepreneurial psychological effect. Firstly, the four aspects of entrepreneurial psychology are summarized, including entrepreneurial awareness, entrepreneurial volition, entrepreneurial ability, and (...) entrepreneurial personality. Secondly, the research status of college students' entrepreneurial psychology is reviewed, and the existing problems are pointed out. Thirdly, the combined model of wavelet transform and Neural Network is proposed, and the feasibility of the proposed model is evaluated through the analysis of college students' entrepreneurial psychology. The wavelet NN is used in experimental design to predict college students' entrepreneurial psychology, and the predicted results are compared with the actual value. From the perspective of the prediction results of entrepreneurial psychology, the combination of wavelet algorithm and neural network is more accurate for entrepreneurial psychology prediction and evaluation results of law students. Overall, the difference between the predicted value and the actual value is within 0.3 points, which is relatively stable. According to the analysis of single-factor results, the scores of students of different majors in the four dimensions of entrepreneurial psychology are all higher than 3.5, but there is no significant difference among the four dimensions, indicating that the major has no significant impact on entrepreneurial psychology; law students with different educational backgrounds have significant differences in entrepreneurial psychology, among which students with a master's degree have the strongest entrepreneurial will, while doctoral students have the lowest entrepreneurial will; in terms of entrepreneurial psychological capital, men's self-efficacy is higher than women's, and the difference is significant. The difference between males and females in the scores of entrepreneurial psychological factors' four aspects is not very obvious. In terms of entrepreneurial psychological capital, males' self-efficacy is significantly higher than females'. Artificial Intelligence technology has great application prospects in the prediction and evaluation of college students' entrepreneurial psychology, and college students' entrepreneurial psychology is highly correlated with gender and education. (shrink)

Feasting on a plethora of social media platforms, news aggregators, and online marketplaces, recommender systems (RSs) are spreading pervasively throughout our daily online activities. Over the years, a host of ethical issues have been associated with the diffusion of RSs and the tracking and monitoring of users’ data. Here, we focus on the impact RSs may have on personal autonomy as the most elusive among the often-cited sources of grievance and public outcry. On the grounds of a philosophically nuanced (...) notion of autonomy, we illustrate three specific reasons why RSs may limit or compromise it: the threat of manipulation and deception associated with RSs; the RSs’ power to reshape users’ personal identity; the impact of RSs on knowledge and critical thinking. In our view, however, notwithstanding these legitimate concerns, RSs may effectively help users to navigate an otherwise overwhelming landscape. Our perspective, therefore, is not to be intended as a bulwark to protect the _status quo_ but as an invitation to carefully weigh these aspects in the design of ethically oriented RSs. (shrink)

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

This paper presents an emerging aspect of intentionality through recent Artificial Intelligence (AI) developments in art and design. Our main thesis is that, if we focus just on the outcome of the artistic process, the intentionality of the artist does not have any relevance. Intention is measured as a result of actions regardless of whether they are human-based or not as long as there is an esthetical value intersubjectively acknowledged. In other words, what matters is the ‘intentio’ embedded (...) in the work of art (the output) rather than the ‘intendere’ (the process). By considering the former aspect, intentionality becomes free of human intervention, therefore 'unintentional'. This thesis is supported through a range of examples related to AI in general and AI art in particular. However, in the case of a self-driving vehicle, the macro-goal of the system is fixed by humans, even though the AI system itself will take care of decomposing the macro-goal into a set of micro-goals and take the corresponding decisions. In the case of art, the system does not need to have any exterior goal to the extent that art is pure freedom of expression, as many philosophers have acknowledged. In this sense, the decisions of any AI system generating art or design are independent of humans and must be judged only on the ground of the final outcome. A work of art will be judged ‘artistic’ to the extent that humans will recognize an artistic intent in the work itself. In particular, the introduction of random processes makes an AI-generated artwork fully independent of human creativity. (shrink)

This dissertation consists of five chapters, each written as independent research papers that are unified by an overarching concern regarding information privacy and machine learning-based artificial intelligence (AI). This dissertation addresses the issues concerning privacy and AI by responding to the following three main research questions (RQs): RQ1. ‘How does an AI system affect privacy?’; RQ2. ‘How effectively does the General Data Protection Regulation (GDPR) assess and address privacy issues concerning both individuals and groups?’; and RQ3. ‘How can (...) the value of privacy be embedded into systems?’ -/- To respond to the RQs, this dissertation adopts the privacy impact assessment (PIA) as the overall methodology. A PIA encompasses three distinct stages; the first, the analytical stage, concerns the analysis of how AI (particularly focusing on inference as a process that includes inferred information, AI models’ performance, and accessing information uncovered by AI models) impacts privacy. Second, the legal assessment stage concerns whether AI that processes personal information and develops models complies with the GDPR. Finally, the design requirements stage features proposals for design requirements for systems aimed at protecting privacy. Accordingly, this dissertation is structured in three parts, each corresponding to a specific stage of a PIA and responding to one of the RQs. -/- Part I, which addresses the first stage of the PIA, comprises three chapters that altogether respond to RQ1. Chapter 2 analyses how AI impacts the descriptive aspect of privacy; this part argues that AI challenges the current definitions of privacy and that the ‘source control’ and ‘actual access’ definitions of privacy, once revised in the face of counter-examples involving inferred information, converge. Chapter 3, which considers how AI impacts the normative aspect of privacy, particularly the value of privacy, argues that AI affects the social value of privacy, which depends on trust, as this dimension of privacy is constituted when AI models perform accurately. Chapter 4 examines how AI impacts the normative aspect of privacy, particularly the right to privacy, and it argues that, although accessing information uncovered by AI models raises concerns about the privacy of algorithmically designed groups, the right to privacy cannot be recognised for such groups. This is the disruptive feature of AI that has led to consideration of new approaches other than the traditional one, which involves recognising the right to privacy, to protect the privacy of these groups. Instead of recognising the right to privacy for algorithmically designed groups, this chapter suggests taking a moral principle for the moral obligation of protecting vulnerable groups within an ethics of vulnerability. -/- Part II concerns the second stage of the PIA and consists of one chapter that responds to RQ2. Chapter 5, in addition to evaluating whether AI that processes personal information and develops models complies with the GDPR, also assesses whether the GDPR adequately addresses the privacy issues raised by AI. It specifically focuses on group privacy and argues that GDPR has limitations in protecting the privacy of algorithmically designed groups and that the privacy of such vulnerable entities must be considered in the context of privacy and data protection. -/- Part III, which is related to the third stage of the PIA, also consists of one chapter that responds to RQ3. Chapter 6 proposes design requirements to protect privacy by integrating privacy into systems and argues that privacy is instrumentally valuable for the sake of autonomy. Accordingly, to embed the value of privacy into systems, design requirements are articulated through the translation of norms that promote and protect autonomy. (shrink)

Transparency is now a fundamental principle for data processing under the General Data Protection Regulation. We explore what this requirement entails for artificial intelligence and automated decision-making systems. We address the topic of transparency in artificial intelligence by integrating legal, social, and ethical aspects. We first investigate the ratio legis of the transparency requirement in the General Data Protection Regulation and its ethical underpinnings, showing its focus on the provision of information and explanation. We then (...) discuss the pitfalls with respect to this requirement by focusing on the significance of contextual and performative factors in the implementation of transparency. We show that human–computer interaction and human-robot interaction literature do not provide clear results with respect to the benefits of transparency for users of artificial intelligence technologies due to the impact of a wide range of contextual factors, including performative aspects. We conclude by integrating the information- and explanation-based approach to transparency with the critical contextual approach, proposing that transparency as required by the General Data Protection Regulation in itself may be insufficient to achieve the positive goals associated with transparency. Instead, we propose to understand transparency relationally, where information provision is conceptualized as communication between technology providers and users, and where assessments of trustworthiness based on contextual factors mediate the value of transparency communications. This relational concept of transparency points to future research directions for the study of transparency in artificial intelligence systems and should be taken into account in policymaking. (shrink)

The question whether AI systems have agency is gaining increasing importance in discussions of responsibility for AI behavior. This paper argues that an approach to artificial agency needs to be teleological, and consider the role of human goals in particular if it is to adequately address the issue of responsibility. I will defend the view that while AI systems can be viewed as autonomous in the sense of identifying or pursuing goals, they rely on human goals and other values (...) incorporated into their design, and are, as such, dependent on human agents. As a consequence, AI systems cannot be held morally responsible, and responsibility attributions should take into account normative and social aspects involved in the design and deployment of the said AI. My argument falls in line with approaches critical of attributing moral agency to artificial agents, but draws from the philosophy of action, highlighting further philosophical underpinnings of current debates on artificial agency. (shrink)

Despite the success of artificial intelligence, we are still far away from AI that model the world as humans do. This study focuses for explaining human behavior from intuitive mental models’ perspectives. We describe how behavior arises in biological systems and how the better understanding of this biological system can lead to advances in the development of human-like AI. Human can build intuitive models from physical, social, and cultural situations. In addition, we follow Bayesian inference to combine (...) intuitive models and new information to make decisions. We should build similar intuitive models and Bayesian algorithms for the new AI. We suggest that the probability calculation in Bayesian sense is sensitive to semantic properties of the objects’ combination formed by observation and prior experience. We call this brain process as computational meaningfulness and it is closer to the Bayesian ideal, when the occurrence of probabilities of these objects are believable. How does the human brain form models of the world and apply these models in its behavior? We outline the answers from three perspectives. First, intuitive models support an individual to use information meaningful ways in a current context. Second, neuroeconomics proposes that the valuation network in the brain has essential role in human decision making. It combines psychological, economical, and neuroscientific approaches to reveal the biological mechanisms by which decisions are made. Then, the brain is an over-parameterized modeling organ and produces optimal behavior in a complex word. Finally, a progress in data analysis techniques in AI has allowed us to decipher how the human brain valuates different options in complex situations. By combining big datasets with machine learning models, it is possible to gain insight from complex neural data beyond what was possible before. We describe these solutions by reviewing the current research from this perspective. In this study, we outline the basic aspects for human-like AI and we discuss on how science can benefit from AI. The better we understand human’s brain mechanisms, the better we can apply this understanding for building new AI. Both development of AI and understanding of human behavior go hand in hand. (shrink)

The development of artificial intelligence (AI) in medicine raises fundamental ethical issues. As one example, AI systems in the field of mental health successfully detect signs of mental disorders, such as depression, by using data from social media. These AI depression detectors (AIDDs) identify users who are at risk of depression prior to any contact with the healthcare system. The article focuses on the ethical implications of AIDDs regarding affected users’ health-related autonomy. Firstly, it presents the (ethical) (...) discussion of AI in medicine and, specifically, in mental health. Secondly, two models of AIDDs using social media data and different usage scenarios are introduced. Thirdly, the concept of patient autonomy, according to Beauchamp and Childress, is critically discussed. Since this concept does not encompass the specific challenges linked with the digital context of AIDDs in social media sufficiently, the current analysis suggests, finally, an extended concept of health-related digital autonomy. (shrink)

This study examines the expanding field of medical tourism with an emphasis on strategies for marketing and entrepreneurship. The literature on the entrepreneurial components of medical tourism and the contribution of artificial intelligence (AI) to enhancing healthcare services and attracting medical tourists from across the world will be examined. Through the Web of Science database, a thorough literature analysis was carried out using keywords associated with marketing, entrepreneurship, medical tourism, and AI. In order to provide more comprehensive conclusions (...) about the sector, the research combines the results of many regional studies. The study identifies key elements that impact medical tourism, such as strategies for marketing, cultural aspects, and infrastructure. In order to improve healthcare services and bring in foreign patients, it points out successful case studies from nations like Malaysia, China, and Iran, highlighting the need for encouraging entrepreneurial ecosystems and productive government cooperation. The research comes to the conclusion that increasing healthcare access and quality requires the medical tourism business. In order to maximize patient experiences and eventually promote development in the medical tourism industry, it emphasizes the significance of customized marketing techniques and the use of AI technology. (shrink)

The presence of intelligence and rationality in Artificial Intelligence and the Internet requires a new context of analysis in which Herbert Simon’s approach to the sciences of the artificial is surpassed in order to grasp the role of information in our contemporary setting. This new framework requires taking into account some relevant aspects. In the historical endeavor of building up AI and the Internet, minds and machines have interacted over the years and in many ways through (...) the interrelation between scientific creativity and technological innovation. Philosophically, minds and machines can have epistemological, methodological and ontological differences, which are based on the distinct configuration of human intelligence and artificial intelligence. Their comparison with rationality and its various forms is particularly relevant. Scientifically, AI and the Internet belong to the sciences of the artificial, because they work on designs that search for specific aims, following selected processes in order to achieve expected results. Technologically, AI and the Internet require the support of information and communication technologies. These have an instrumental role regarding the existence of AI and the Internet. Also ICT shape their diverse forms of configuration over the years.Within this framework, this paper offers a new context of analysis that goes beyond Simon’s and follows four main steps: the interaction between scientific creativity and technological innovation as the philosophico-methodological setting for Artificial Intelligence and the Internet; artificial intelligence and human intelligence as epistemological basis for machines and minds, where the differences between artificial intelligence and human intelligence are made explicit and the analysis of minds and machines is made from the perspective of rationality ; intention and its difference with design of machine learning are considered to distinguish human intelligence from artificial intelligence; and the internal and external aspects of artificial designs in contemporary society are considered through the perspective of rationality, which leads to the transition from intelligence to rationality in the Internet as well as to the historicity of information. (shrink)

In nearly all aspects of life, humans are crossing lines of no return. Modern science is leading us into vast uncharted territory—far beyond the invention of nuclear weapons or taking us to the moon.Today, in labs all over the world, scientists are performing experiments that threaten to fundamentally alter the practical character and ethical color of our everyday lives. In The End of Life as We Know It, bestselling author Michael Guillen takes a penetrating look at how the scientific community (...) is pushing the boundaries of morality, including: • Scientists who detached the head of a Russian man from his crippled, diseased body, and stitching it onto a healthy new donated body. • Fertility experiments aimed at allowing designer babies to be conceived with the DNA from three or more biological parents. • The unprecedented politicization of science – for example, in the global discussion about climate change that is pitting “deniers” against “alarmists” and inspiring Draconian legislation, censorship, and legal prosecutions. • The integration of Artificial Intelligence into communications and the economy. The End of Life as We Know It takes us into labratories and boardrooms where these troubling advances are taking place and asks the question no scientists seem to be asking: What does this mean for the future of humanity? (shrink)

I claim that in order to pass the Turing Test over any period of extended time, it will necessary to embed the entity into society. This chapter discusses why this is, and how it might be brought about. I start by arguing that intelligence is better characterised by tests of social interaction, especially in open-ended and extended situations. I then argue that learning is an essential component of intelligence and hence that a universal intelligence is impossible. (...) These two arguments support the relevance of Turing Test as a particular but appropriate test of interactive intelligence. I look to the human case to argue that individual intelligence utilises society to a considerable extent for its development. Taking a lead from the human case I outline how a socially embedded artificial intelligence might be brought about in terms of four aspects: free-will, emotion, empathy and self-modelling. In each case I try to specify what social ‘hooks’ might be required in order for the full ability to develop during a considerable period of in situ acculturation. The chapter ends by speculating what it might be like to live with the result. (shrink)

The article examines the impact of contemporary intellectual technologies on human subjectivity through the lens of 20th-century philosophical reflection. It explores the transformation of the relationship between humans and technology in a context where technological systems transcend the traditional understanding of technology as merely an extension of human capabilities. Drawing on the conceptual framework of the philosophy of technology (M. Heidegger, J. Ortega y Gasset, J. Ellul, H. Marcuse), the author identifies three key aspects of this transformation. First, the article (...) considers the process by which various facets of human activity – cognitive processes, emotional reactions, social relationships, and creativity – are transformed into “standing-reserve” (Bestand) for technological systems. Second, it analyzes the phenomenon of the erosion of practices that reproduce and develop human experience, as evidenced by the standardization of cognitive processes, the emergence of intellectual dependency, and cultural homogenization. Third, it investigates the problem of technological determinism, which, in the context of intellectual technologies, takes on the character of not merely an external constraint but an active construction of human subjectivity, agency. Special attention is given to the mechanisms through which intellectual technologies transform processes of identity formation, decision-making, and social interaction. Furthermore, the article considers the intersubjective interaction between humans and intellectual technology, emphasizing that an imbalance in this relationship may lead to the erosion of human subjectivity. In closing, the article advocates for the development of new approaches to the legal regulation of intellectual technologies to preserve the balance between technological advancement and the maintenance of human autonomy. The author concludes that the relationship between humans and intellectual technologies has become a central issue in contemporary philosophical anthropology: preserving human subjectivity in the era of artificial intelligence will require a critical rethinking and partial transformation of traditional conceptions of human nature, values, and the normative foundations of human activity. (shrink)

Strategies for improving the explainability of artificial agents are a key approach to support the understandability of artificial agents’ decision-making processes and their trustworthiness. However, since explanations are not inclined to standardization, finding solutions that fit the algorithmic-based decision-making processes of artificial agents poses a compelling challenge. This paper addresses the concept of trust in relation to complementary aspects that play a role in interpersonal and human–agent relationships, such as users’ confidence and their perception of artificial (...) agents’ reliability. Particularly, this paper focuses on non-expert users’ perspectives, since users with little technical knowledge are likely to benefit the most from “post-hoc”, everyday explanations. Drawing upon the explainable AI and social sciences literature, this paper investigates how artificial agent’s explainability and trust are interrelated at different stages of an interaction. Specifically, the possibility of implementing explainability as a trust building, trust maintenance and restoration strategy is investigated. To this extent, the paper identifies and discusses the intrinsic limits and fundamental features of explanations, such as structural qualities and communication strategies. Accordingly, this paper contributes to the debate by providing recommendations on how to maximize the effectiveness of explanations for supporting non-expert users’ understanding and trust. (shrink)

This article considers the relationship between Christian pastoral care and Artificial Intelligence systems. Four aspects are identified from definitions of pastoral care: the horizon of contingency in mortality, the role of wisdom rather than mere information, the oppressive and/or liberatory potential of AI and the importance of empathic presence. In rejecting a transhumanist argument that mental processes are substrate-independent, it is contended that pastoral carers embrace, rather than seeking to circumvent, their crucial finitude in being humans who care. (...) A distinction is drawn between probabilistic reasoning and judgement in retaining a vital place for decision-making that is social. Whilst not eschewing value in AI systems, this article argues for critical evaluation of technologically framed contributions to addressing barriers to people's participation. The importance of empathy is highlighted—in the light of claims not only of robotic mimicry but of interindividual models of emotion. It is concluded that the notion of artificial care be ruled out although the possibilities of AI-assisted care are not dismissed. Opportunities for humans to abdicate from the responsibilities to care, in favour of AI substitutes, are deemed to be best avoided. (shrink)

In 1980, the 85 year-old mystic and thinker Jiddu Krishnamurti (1895–1986), having been introduced to the subject of artificial intelligence by computer scientists, became engrossed in the challenge posed to the human mind by the prospect of the machine taking over its processes and faculties. What makes Krishnamurti’s angle worthy of separate discussion is that it accentuates not social and cultural ramifications, but a mostly overlooked potential philosophical and psychological crisis. As a thinker and mystic whose life (...) work entirely centred on the transformation of the human mind, Krishnamurti worried that an insufficiently cultivated mind that had been employed merely for material and mechanical purposes would be perfectly imitable and thus replaceable by computers and other machines. Thus, our main concern should not be machines attaining humanlike minds, but people having machinelike minds. I argue that the particular dimension of the AI–mind encounter elucidated by Krishnamurti can significantly broaden the field of the philosophy of artificial intelligence. Firstly, Krishnamurti’s investigation further problematizes the field by handing us the question: ‘If the machine can take over everything man can do, and do it still better than us, then what is a human being?’ Accordingly, he demonstrates, deploying phenomenological observations, various ways in which human thought is worryingly computational and machinelike. Secondly, since Krishnamurti’s approach is transformative and arguably soteriological, he offers intriguing ways in which we could consider the inherently nonmechanical yet unactualized faculties of the mind. Since Krishnamurti’s observations involve an insight into the present condition of the mind and a potential active response to this condition, they have some pertinence to both the primary discourse in the field – the interrelations between artificial intelligence and aspects of human cognition – and the emerging discussion of meaningfulness in life in the face of AI. (shrink)