Artificial intelligence (AI) based clinical decision support systems (CDSS) are becoming ever more widespread in healthcare and could play an important role in diagnostic and treatment processes. For this reason, AI‐based CDSS has an impact on the doctor–patient relationship, shaping their decisions with its suggestions. We may be on the verge of a paradigm shift, where the doctor–patient relationship is no longer a dual relationship, but a triad. This paper analyses the role of AI‐based CDSS for shared decision‐making (...) to better comprehend its promises and associated ethical issues. Moreover, it investigates how certain AI implementations may instead foster the inappropriate paradigm of paternalism. Understanding how AI relates to doctors and influences doctor–patient communication is essential to promote more ethical medical practice. Both doctors' and patients' autonomy need to be considered in the light of AI. (shrink)

The application of Artificial Intelligence (AI) in healthcare and epidemiology undoubtedly has many benefits for the population. However, due to its environmental impact, the use of AI can produce social inequalities and long-term environmental damages that may not be thoroughly contemplated. In this paper, we propose to consider the impacts of AI applications in medical care from the One Health paradigm and long-term global health. From health and environmental justice, rather than settling for a short and fleeting green (...) honeymoon between health and sustainability caused by AI, it should aim for a lasting marriage. To this end, we conclude by proposing that, in the upcoming years, it could be valuable and necessary to promote more interconnected health, call for environmental cost transparency, and increase green responsibility. (shrink)

Begriffsanalyse und empirische Forschung auf dem Gebiet der künstlichen Intelligenz zeigen, daß momentan derart kontroverse Ansätze entwickelt werden, daß gemeinschaftliche Momente in Perspektiven und angewandten Methodologien nur schwer auszumachen sind.

The field of Artificial Intelligence (AI) has undergone many transformations, most recently the emergence of data-driven approaches centred on machine learning technology. The present article examines that paradigm shift by using the conceptual tools developed by Thomas Kuhn, and by analysing the contents of the longest running conference series in the field. A paradigm shift occurs when a new set of assumptions and values replaces the previous one within a given scientific community. These are often conveyed implicitly, by (...) the choice of success stories that exemplify and define what a given field of research is about, demonstrating what kind of questions and answers are appropriate. The replacement of these exemplar stories corresponds to a shift in goals, methods, and expectations. We discuss the most recent such transition in the field of Artificial Intelligence, as well as commenting on some earlier ones. (shrink)

The ethical review of research using methods of artificial intelligence and machine learning in health care contexts has become an important challenge for Research Ethics Boards (also refer...

In this paper we want to analyze some philosophical and epistemological connections between a new kind of technology recently developed within robotics, and the previous mechanical approach. A new paradigm about machine-design in robotics, currently defined as ‘Embodied Intelligence’, has recently been developed. Here we consider the debate on the relationship between the hand and the intellect, from the perspective of the history of philosophy, aiming at providing a more suitable understanding of this paradigm. The new bottom-up approach to (...) design is deeply rooted in a new kind of empiricism, which tries to overcome issues connected with the previous approach strongly committed with the Artificial Intelligence (AI) debate and its origin. Since Turing’s time, the AI debate showed a rationalistic bias which remained undisputed until now. The paradigm shift we are witnessing nowadays is a reply to that bias in order to achieve not only a better way to design robots, but also to understand some underlying epistemological remarks. (shrink)

The problem of epistemic opacity in Artificial Intelligence is often characterised as a problem of intransparent algorithms that give rise to intransparent models. However, the degrees of transparency of an AI model should not be taken as an absolute measure of the properties of its algorithms but of the model’s degree of intelligibility to human users. Its epistemically relevant elements are to be specified on various levels above and beyond the computational one. In order to elucidate this claim, (...) I first contrast computer models and their claims to algorithm-based universality with cybernetics-style analogue models and their claims to structural isomorphism between elements of model and target system. While analogue models aim at perceptually or conceptually accessible model-target relations, computer models give rise to a specific kind of underdetermination in these relations that needs to be addressed in specific ways. I then undertake a comparison between two contemporary AI approaches that, although related, distinctly align with the above modelling paradigms and represent distinct strategies towards model intelligibility: Deep Neural Networks and Predictive Processing. I conclude that their respective degrees of epistemic transparency primarily depend on the underlying purposes of modelling, not on their computational properties. (shrink)

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

The idea that human cognitive capacities are explainable by computational models is often conjoined with the idea that, while the states postulated by such models are in fact realized by brain states, there are no type-type correlations between the states postulated by computational models and brain states (a corollary of token physicalism). I argue that these ideas are not jointly tenable. I discuss the kinds of empirical evidence available to cognitive scientists for (dis)confirming computational models of cognition and argue that (...) none of these kinds of evidence can be relevant to a choice among competing computational models unless there are in fact type-type correlations between the states postulated by computational models and brain states. Thus, I conclude, research into the computational procedures employed in human cognition must be conducted hand-in-hand with research into the brain processes which realize those procedures. (shrink)

Artificial Intelligence (AI) is set to bring changes to legal systems. These technologies may have positive practical implications when it comes to access, efficiency, and accuracy in Justice. However, there are still many uncertainties and challenges associated with the implementation of AI in the legal space. In this research, we surveyed Judges on critical challenges related to the Judging Profession in the AI paradigm; Automated Adjudication; and Legal Principles. Our results suggest that (i) Judges are hesitant about changes (...) in their profession. They signal the need for adequate training that fosters legal literacy in AI, but are less open to changes in legal writing or their social and institutional role; (ii) Judges believe higher levels of automation only lead to fair outcomes if used in earlier phases of adjudication; (iii) Judges believe and are concerned about AI leading to Techno-Legal Positivism; and (iv) Judges consider that Legal AI technologies may have a positive impact in some legal principles, as long as everyone has equal access to those technologies and cybersecurity and judge on the loop safeguards are in place; and (v) Judges are strongly concerned about the de-humanization of Justice. They consider that assessing evidence, analyzing arguments, and deciding on a legal case should be inherently human. By surveying these practitioners, we aim to foster a responsible, inclusive, and transparent innovation in Justice. (shrink)

The current paradigm of Artificial Intelligence emerged as the result of a series of cultural innovations, some technical and some social. Among them are apparently small design decisions, that led to a subtle reframing of the field’s original goals, and are by now accepted as standard. They correspond to technical shortcuts, aimed at bypassing problems that were otherwise too complicated or too expensive to solve, while still delivering a viable version of AI. Far from being a series of (...) separate problems, recent cases of unexpected effects of AI are the consequences of those very choices that enabled the field to succeed, and this is why it will be difficult to solve them. In this chapter we review three of these choices, investigating their connection to some of today’s challenges in AI, including those relative to bias, value alignment, privacy and explainability. We introduce the notion of “ethical debt” to describe the necessity to undertake expensive rework in the future in order to address ethical problems created by a technical system. (shrink)

A. M. Turing argued that there was "little point in trying to make a 'thinking machine' more human by dressing it up in ... artificial flesh." We should, instead, draw "a fairly sharp line between the physical and the intellectual capacities of a man." For over fifty years, drawing this line has meant disregarding the role flesh plays in our intellectual capacities. Correspondingly, intelligence has been defined in terms of the algorithms that both men and machines can perform. (...) I would like to raise some doubts about this paradigm in artificial intelligence research. Intelligence, I believe, does not just involve the working of algorithms. It is founded on flesh's ability to move itself, to feel itself, and to engage in the body projects that accompanied our learning a language. This implies that to copy intelligence -- i.e., to produce an artificial version of it -- the flesh that forms its basis must also be reproduced. (shrink)

The present study focuses on the situation in which mind-reading machines will be connected, initially through the incorporation of weak AI, and then in conjunction to strong AI, an aspect that, ongoing, will no longer have a simple medical role, as is the case at present, but one of surveillance and monitoring of individuals—an aspect that is heading us towards a future techno-panoptic singularity. Thus, the general objective of this paper raises the problem of the ontological stability of human nature (...) which, within the limits of the technological singularity of mind-reading machines, leads to the loss of autonomy and a reduction in freedom when it comes to human thoughts. In this paradigm, the hypothesis of a future era of technological singularity is prefigured to be a cumulation of factors in which artificial intelligence holds a dominant position in relation to the human agent, in a techno-panoptic system of human supervision, in the form of a new world order of manifestation/imposition of power—that of a “singleton.” The theoretical objective analyzes the phenomenon of “deterritorrialization” of the Foucauldian panoptic mechanism —which is based on the “biopolitical” system of “biopower”—and its “reterritorialization” in the “territory” of the techno-panoptic singularity, where the scenario of a strong AI “singleton”, represents the alienation of the Being into a hard technological determinism. (shrink)

In this paper, I explore the fruitful relationship between science fiction and philosophy regarding the topic of artificial intelligence. I establish a connection between certain paradigms in the philosophy of mind and consciousness and the imagination of possible future scenarios in sci-fi, especially focusing on the different ways of conceiving the role of corporeality in constituting consciousness and cognition. Then, I establish a parallelism between these different conceptions of corporeality in the philosophy of mind and certain representations (...) of AI in sci-fi: from computers to robots and androids. I conclude by stressing the value of exchanging ideas between sci-fi and philosophy to foreshadow and evaluate some scenarios of high ethical relevance. (shrink)

We expose the implications of lexical innovation as supported by the ONOMATURGE knowledge-based paradigm, for policies intended to foster native or national languages. In certain cases, the survival of native cultures, as supported by their language, depends on their ability to fill lexical gaps due to the technological gap. In certain other cases, the native culture itself is not in crisis (e.g., in the case of the national language of a sovereign country), but the local technologists or translators participate in (...) lexical innovation in a specific technical domain, and can benefit from the ONOMATURGE paradigm. (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)

As the capabilities of artificial intelligence systems improve, it becomes important to constrain their actions to ensure their behaviour remains beneficial to humanity. A variety of ethical, legal and safety-based frameworks have been proposed as a basis for designing these constraints. Despite their variations, these frameworks share the common characteristic that decision-making must consider multiple potentially conflicting factors. We demonstrate that these alignment frameworks can be represented as utility functions, but that the widely used Maximum Expected Utility paradigm (...) provides insufficient support for such multiobjective decision-making. We show that a Multiobjective Maximum Expected Utility paradigm based on the combination of vector utilities and non-linear action–selection can overcome many of the issues which limit MEU’s effectiveness in implementing aligned AI. We examine existing approaches to multiobjective AI, and identify how these can contribute to the development of human-aligned intelligent agents. (shrink)

The article addresses the problem of identifying methods to develop the ability of artificial intelligence (AI) systems to provide explanations for their findings. This issue is not new, but, nowadays, the increasing complexity of AI systems is forcing scientists to intensify research in this direction. Modern neural networks contain hundreds of layers of neurons. The number of parameters of these networks reaches trillions, genetic algorithms generate thousands of generations of solutions, and the semantics of AI models become more (...) complicated, going to the quantum and non-local levels. The world’s leading companies are investing heavily in creating explainable AI (XAI). However, the result is still unsatisfactory: a person often cannot understand the “explanations” of AI because the latter makes decisions differently than a person, and perhaps because a good explanation is impossible within the framework of the classical AI paradigm. AI faced a similar problem 40 years ago when expert systems contained only a few hundred logical production rules. The problem was then solved by complicating the logic and building added knowledge bases to explain the conclusions given by AI. At present, other approaches are needed, primarily those that consider the external environment and the subjectivity of AI systems. This work focuses on solving this problem by immersing AI models in the social and economic environment, building ontologies of this environment, taking into account a user profile and creating conditions for purposeful convergence of AI solutions and conclusions to user-friendly goals. (shrink)

The realm of bioethics has long been underpinned by the foundational concept of "personhood," which delineates entities meriting moral and legal consideration on the basis of attributes such as con...

The article considers modern transformations of the ideas concerning subject’s cognitive abilities towards object because of the emergence and development of artificial intelligence (AI) technologies. The developments of scientists and engineers from National Research University of Electronic Technology (Moscow, Russia) in the field of artificial intelligence have been taken as a foundation and material of this research. Their analysis allows making a conclusion that the humanity is rather far from the realization of ‘strong artificial (...) class='Hi'>intelligence’. We need a qualitative breakthrough in AI material and technological basis for it. Applying ‘model-dependent realism’ by S. Hawking in the course of the speculations in the article, the author concludes that the purpose of cognition in modern science is not to describe an objective reality, but to organize its subjective perception by some definite way. So, the purpose of cognition is the perfection of cognition models permitting a subject ‘to capture’ the reality. This idea is completely confirmed by Maturana and Varela’s autopoiesis theory and von Foerster’s ‘second-order cybernetics’. The article drafts some prospects of moving away from post-nonclassical scientific thinking in its current understanding, because the development of AI technologies results in ‘blurring’ borders of subjectivity in the cognition process. The author concludes that the modern world is moving in another epistemological paradigm where a new scientific revolution is inevitable. (shrink)

Increasingly, innovation in artificial intelligence technologies portends the re-conceptualization of human existentiality along the paradigm of posthumanism. An exposition of this through a critical culturo-historical methodology uncloaks the Eurocentric genitive basis of the philosophical anthropology that underpins this technological posthumanism, as well as its dystopian possibilities. As a contribution to obviating the latter, an Africanist civilizational humanism proclaimed by Pixley ka Isaka Seme is proffered as a plausible alternative paradigm for humanity’s technological advancement. Seme, a pan-Africanist thinker of (...) the early twentieth century, proclaimed humanistic-spirituality as the indispensable gift African Civilisation-in-its-renaissance is yet to offer global humanity. His postulation is being provided as a contribution to the archive on cross-cultural ethics of artificial intelligence. (shrink)

Social machines are systems formed by material and human elements interacting in a structured way. The use of digital platforms as mediators allows large numbers of humans to participate in such machines, which have interconnected AI and human components operating as a single system capable of highly sophisticated behavior. Under certain conditions, such systems can be understood as autonomous goal-driven agents. Many popular online platforms can be regarded as instances of this class of agent. We argue that autonomous social machines (...) provide a new paradigm for the design of intelligent systems, marking a new phase in AI. After describing the characteristics of goal-driven social machines, we discuss the consequences of their adoption, for the practice of artificial intelligence as well as for its regulation. (shrink)

This article deals with the links between the enaction paradigm and artificial intelligence. Enaction is considered a metaphor for artificial intelligence, as a number of the notions which it deals with are deemed incompatible with the phenomenal field of the virtual. After explaining this stance, we shall review previous works regarding this issue in terms of artificial life and robotics. We shall focus on the lack of recognition of co-evolution at the heart of these approaches. (...) We propose to explicitly integrate the evolution of the environment into our approach in order to refine the ontogenesis of the artificial system, and to compare it with the enaction paradigm. The growing complexity of the ontogenetic mechanisms to be activated can therefore be compensated by an interactive guidance system emanating from the environment. This proposition does not however, resolve that of the relevance of the meaning created by the machine (sense-making). Such reflections lead us to integrate human interaction into this environment in order to construct relevant meaning in terms of participative artificial intelligence. This raises a number of questions with regards to setting up an enactive interaction. The article concludes by exploring a number of issues, thereby enabling us to associate current approaches with the principles of morphogenesis, guidance, the phenomenology of interactions and the use of minimal enactive interfaces in setting up experiments which will deal with the problem of artificial intelligence in a variety of enaction-based ways. (shrink)

The article considers modern transformations of the ideas concerning subject’s cognitive abilities towards object because of the emergence and development of artificial intelligence (AI) technologies. The developments of scientists and engineers from National Research University of Electronic Technology (Moscow, Russia) in the field of artificial intelligence have been taken as a foundation and material of this research. Their analysis allows making a conclusion that the humanity is rather far from the realization of ‘strong artificial (...) class='Hi'>intelligence’. We need a qualitative breakthrough in AI material and technological basis for it. Applying ‘model-dependent realism’ by S. Hawking in the course of the speculations in the article, the author concludes that the purpose of cognition in modern science is not to describe an objective reality, but to organize its subjective perception by some definite way. So, the purpose of cognition is the perfection of cognition models permitting a subject ‘to capture’ the reality. This idea is completely confirmed by Maturana and Varela’s autopoiesis theory and von Foerster’s ‘second-order cybernetics’. The article drafts some prospects of moving away from post-nonclassical scientific thinking in its current understanding, because the development of AI technologies results in ‘blurring’ borders of subjectivity in the cognition process. The author concludes that the modern world is moving in another epistemological paradigm where a new scientific revolution is inevitable. (shrink)

Rapid advances in computer technology and what is termed ‘Artificial Intelligence’ in the past 70 years have led to speculation about the ultimate capabilities of electronic devices, including speculation about whether they will make humans obsolete at some future time. Zubiri’s distinction between sensible intelligence and sentient intelligence can be applied to understanding of the limitations of AI. Machines can only operate on the sensible intelligence paradigm, which entails limits. Sentient intelligence allows humans to (...) carry out functions that sensible intelligence-based devices can never do. Sensible intelligence-based devices, including AI, will therefore be restricted to amplifying human (i.e. sentient intelligence) capabilities, but never replacing them. Historically, extravagant claims for AI have not been borne out, despite many orders of magnitude increase in computation speed and memory capacity. Theoretical arguments, based on Godel’s Incompleteness Theorem, also confirm this. (shrink)

Real engines of the artificial intelligence revolution, machine learning models, and algorithms are embedded nowadays in many services and products around us. As a society, we argue it is now necessary to transition into a phronetic paradigm focused on the ethical dilemmas stemming from the conception and application of AIs to define actionable recommendations as well as normative solutions. However, both academic research and society-driven initiatives are still quite far from clearly defining a solid program of study and (...) intervention. In this contribution, we will focus on selected ethical investigations around AI by proposing an incremental model of trust that can be applied to both human-human and human-AI interactions. Starting with a quick overview of the existing accounts of trust, with special attention to Taddeo’s concept of “e-trust,” we will discuss all the components of the proposed model and the reasons to trust in human-AI interactions in an example of relevance for business organizations. We end this contribution with an analysis of the epistemic and pragmatic reasons of trust in human-AI interactions and with a discussion of kinds of normativity in trustworthiness of AIs. (shrink)

This article explores the challenges surrounding generative artificial intelligence (GenAI) in public administrations and its impact on human‒machine interactions within the public sector. First, it aims to deconstruct the reasons for distrust in GenAI in public administrations. The risks currently linked to GenAI in the public sector are often similar to those of conventional AI. However, while some risks remain pertinent, others are less so because GenAI has limited explainability, which, in return, limits its uses in public administrations. (...) Confidentiality, marking of GenAI outputs and errors are specific matters for which responses should be technical as well as cultural, as they are pushing the boundaries of our instrumental conceptions of machines. Second, this article proposes some paradigm shifts in the perspective of using GenAI in public administrations due to the radical change caused by its language-based nature. GenAI represents a profound break from the “numerical” nature of AI systems implemented in public administrations to date. The transformative impact of GenAI on the intellectual production of the state raises fears of the replacement, or rather enslavement, of civil servants to machines. The article argues for the development of critical thinking as a specific skill for civil servants who have become highly specialized and will have to think with a machine that is eclectic by nature. It anticipates a transformation in the political nature of public administrations, which should lead to more considerations for the strategic stake related to training corpus and for our conceptualization of the neutrality of AI. (shrink)

1. Artificial Intelligence is an ambiguous umbrella term. Until today there is no uniform definition of AI and the term carries several meanings. As exemplary, I will give two definitions of AI tha...

Commonsense reasoning is one of the main open problems in the field of Artificial Intelligence (AI) while, on the other hand, seems to be a very intuitive and default reasoning mode in humans and other animals. In this talk, we discuss the different paradigms that have been developed in AI and Computational Cognitive Science to deal with this problem (ranging from logic-based methods, to diagrammatic-based ones). In particular, we discuss - via two different case studies concerning commonsense (...) categorization and knowledge invention tasks - how cognitively inspired heuristics can help (both in terms of efficiency and efficacy) in the realization of intelligent artificial systems able to reason in a human-like fashion, with results comparable to human-level performances. (shrink)

In the age of artificial intelligence, writing machines or robot authors have already begun to produce narrative texts in a variety of genres, including short stories and poetry, as well as journalistic articles. This article is based on the prospect that the narrative ecosystem is in a transitional period of decisive disconnection as it enters the era of artificial intelligence. The primary force driving this transition is the formidable execution of artificial intelligence algorithms, which (...) fully automate narrative communication and narrative works. This article attempts to lay the groundwork for building a new paradigm of post-narrativity through a critical examination of several detailed themes in narrative semiotics and non-anthropocentric narratology. The process of narrative creation based on artificial intelligence algorithms is a key condition that constitutes post-narrativity. This presupposes a non-anthropocentric view. In the landscape of post-narrativity, human writers, paper books, computer screens, and invisible narrative algorithms are all agents with equal influence. Automated narrative production by algorithms accelerates the repositioning of other existing media and actors, and changes the narrative ecosystem by incorporating new elements into activities such as production, distribution, and reception of narratives. (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)

This article deals with the links between the enaction paradigm and artificial intelligence. Enaction is considered a metaphor for artificial intelligence, as a number of the notions which it deals with are deemed incompatible with the phenomenal field of the virtual. After explaining this stance, we shall review previous works regarding this issue in terms of artificial life and robotics. We shall focus on the lack of recognition of co-evolution at the heart of these approaches. (...) We propose to explicitly integrate the evolution of the environment into our approach in order to refine the ontogenesis of the artificial system, and to compare it with the enaction paradigm. The growing complexity of the ontogenetic mechanisms to be activated can therefore be compensated by an interactive guidance system emanating from the environment. This proposition does not however, resolve that of the relevance of the meaning created by the machine (sense-making). Such reflections lead us to integrate human interaction into this environment in order to construct relevant meaning in terms of participative artificial intelligence. This raises a number of questions with regards to setting up an enactive interaction. The article concludes by exploring a number of issues, thereby enabling us to associate current approaches with the principles of morphogenesis, guidance, the phenomenology of interactions and the use of minimal enactive interfaces in setting up experiments which will deal with the problem of artificial intelligence in a variety of enaction-based ways. (shrink)

Neosentience, a potentially new branch of scientific inquiry related to artificial intelligence, was first suggested in a paper by Bill Seaman as part of a new embodied robotic paradigm, arising out of ongoing theoretical research with Otto E. Rossler. Seaman, artist-researcher, and Rossler, theoretical biologist and physicist, have been examining the potential of generating an intelligent, embodied, multimodal sensing and computational robotic system. Although related to artificial intelligence the goal of this system is the creation of (...) an entity exhibiting a new form of sentience. Its unique qualities will be discussed. Sentience is not yet used in the formal languages of either cognitive science or artificial intelligence. Two related approaches are (1) the generation of artificial minds via parallel processing, in a robotic system; (2) an alternative approach is the generation of an electrochemical computer as a robotic system. Biomimetics, along with state-of-the-art computer visualization is employed. The electrochemical paradigm has a complexity that exceeds standard computational means. The scientific and the poetic elements of the project are motivated by human sentience. The sentient entity is initially modelled on our functional definition of human sentience. The system involves synthetic drives as a new element. We seek to articulate the differences to living brains. This transdisciplinary approach necessitates different forms of inquiry to inform this project such as cognitive science including psychology, education/learning, neuroscience, linguistics, philosophy, anthropology, biology and the arts. We believe that this area of research to be of importance. (shrink)

Algorithmic probability and friends: Proceedings of the Ray Solomonoff 85th memorial conference is a collection of original work and surveys. The Solomonoff 85th memorial conference was held at Monash University's Clayton campus in Melbourne, Australia as a tribute to pioneer, Ray Solomonoff, honouring his various pioneering works - most particularly, his revolutionary insight in the early 1960s that the universality of Universal Turing Machines could be used for universal Bayesian prediction and artificial intelligence. This work continues to increasingly (...) influence and under-pin statistics, econometrics, machine learning, data mining, inductive inference, search algorithms, data compression, theories of intelligence and philosophy of science - and applications of these areas. Ray not only envisioned this as the path to genuine artificial intelligence, but also, still in the 1960s, anticipated stages of progress in machine intelligence which would ultimately lead to machines surpassing human intelligence. Ray warned of the need to anticipate and discuss the potential consequences - and dangers - sooner rather than later. Possibly foremostly, Ray Solomonoff was a fine, happy, frugal and adventurous human being of gentle resolve who managed to fund himself while electing to conduct so much of his paradigm-changing research outside of the university system. The volume contains 35 papers pertaining to the abovementioned topics in tribute to Ray Solomonoff and his legacy. (shrink)

This article examines argument structures and strategies in pro and con argumentation about the possibility of human-level artificial intelligence (AI) in the near term future. It examines renewed controversy about strong AI that originated in a prominent 1999 book and continued at major conferences and in periodicals, media commentary, and Web-based discussions through 2002. It will be argued that the book made use of implicit, anticipatory refutation to reverse prevailing value hierarchies related to AI. Drawing on Perelman and (...) Olbrechts-Tyteca's (1969) study of refutational argument, this study considers points of contact between opposing arguments that emerged in opposing loci, dissociations, and casuistic reasoning. In particular, it shows how perceptions of AI were reframed and rehabilitated through metaphorical language, reversal of the philosophical pair artificial/natural, appeals to the paradigm case, and use of the loci of quantity and essence. Furthermore, examining responses to the book in subsequent arguments indicates the topoi characteristic of the rhetoric of technology advocacy. (shrink)

The aim of this paper is to investigate the relationship between AI urbanism and sustainability by drawing upon some key concepts of Bruno Latour’s philosophy. The idea of a sustainable AI urbanism - often understood as the juxtaposition of smart and eco urbanism - is here critiqued through a reconstruction of the conceptual sources of these two urban paradigms. Some key ideas of smart and eco urbanism are indicated as incompatible and therefore the fusion of these two paradigms (...) is assessed as an unstable basis for shaping sustainable AI urbanism. The concepts in question - modernity, science and nature – are subsequently redefined following Latour’s philosophical perspective, in an attempt to define a different theoretical basis for a sustainable AI urbanism in the Anthropocene. Finally, the principles of a design philosophy shaped by Latour are used to change the design culture that informs AI urbanism towards a more sustainable practice. This paper constructs and promotes a dialogue between the disciplines of philosophy and urban theory with urban design in the conviction that the principles produced by the former and the practices carried out by the latter must start a biunivocal relationship. The paper reveals that in order to change design culture in the field of AI urbanism, it is necessary to rethink some of the key ideas that inform the Western and modern worldview through novel philosophical reflections. (shrink)

Although the AI paradigm is useful for building knowledge-based systems for the applied natural sciences, there are dangers when it is extended into the domains of business, law and other social systems. It is misleading to treat knowledge as a commodity that can be separated from the context in which it is regularly used. Especially when it relates to social behaviour, knowledge should be treated as socially constructed, interpreted and maintained through its practical use in context. The meanings of terms (...) in a knowledge-base are assumed to be references to an objective reality whereas they are instruments for expressing values and exercising power. Expert systems that are not perspicuous to the expert community will lose their meanings and cease to contain genuine knowledge, as they will be divorced from the social processes essential for the maintenance of both meaning and knowledge. Perspicuity is usually sacrificed when knowledge is represented in a formalism, with the result that the original problem is compounded with a second problem of penetrating the representation language. Formalisms that make business and legal problems easier to understand are one essential research goal, not only in the quest for intelligent machines to replace intelligent human beings, but also in the wiser quest for computers to support collaborative work and other forms of social problem solving. (shrink)

As artificial intelligence (AI) integrates across social domains, prevailing technical paradigms often overlook human relational needs vital for cooperative resilience. Alternative pathways consciously supporting dignity and wisdom warrant consideration. Integrating seminal insights from virtue and care ethics, this article delineates the following four cardinal design principles prioritizing communal health: (1) affirming the sanctity of life; (2) nurturing healthy attachment; (3) facilitating communal wholeness; and (4) safeguarding societal resilience. Grounding my analysis in the rich traditions of moral philosophy, (...) I argue that these principles scaffold sustainable innovation trajectories that consciously center shared welfare advancement over detached technical capabilities or efficiency benchmarks alone. Elucidating connections with pioneering initiatives demonstrates fragments of this vision taking embryonic shape, yet pervasive adoption remains largely aspirational to date. Fulfilling dignity-based artificial intelligence demands ongoing collective commitment beyond firms’ profit motives or governance proceduralism. My conclusions urge technology policies and priorities directed toward empowering the vulnerability of people rather than controlling the optimization of systems. (shrink)

The article explores the transformative impact on human and social sciences in response to anticipated societal shifts driven by the forthcoming proliferation of artificial systems, whose intelligence will match human capabilities. Initially, it was posited that artificial intelligence (AI) would excel beyond human abilities in computational tasks and algorithmic operations, leaving creativity and humanities as uniquely human domains. However, recent advancements in large language models have significantly challenged these conventional beliefs about AI’s limitations and strengths. It (...) is projected that, in the near future, generative AI models will adeptly replicate individual qualities, desires, beliefs, opinions, and the essence of human identity and consciousness to a degree that is nearly indistinguishable from that of humans. This lends support to the connectionist approach to understanding consciousness, suggesting an inherent similarity between biological and artificial neural networks. The discussion posits two innovative areas of scientific inquiry: “mathematical anthropology” and “multi-dimensional calculus of value.” The former suggests that viewing human nature through a mathematical and calculative lens not only preserves but enriches our understanding of the complexity of anthropological experience and its perceived contradictions. The latter hypothesis explores how mathematical models could facilitate various social interactions. The advanced simulation capabilities of neural networks suggest that traditional social and political frameworks face a growing vulnerability to AI-driven manipulations. This trend underscores the urgency of developing social interaction models that incorporate explicitly defined calculative rules. In conclusion, the paper advocates for a paradigm shift in how mathematics is perceived – not merely as a tool for computation but as a foundational science for crafting sophisticated models. In conclusion, the article advocates for transitioning from perceiving mathematics solely as a science of computation to viewing it as a discipline dedicated to constructing various formalized models, thereby deepening our insight into the complexities of human and social phenomena. (shrink)

With the development of artificial intelligence, it is imperative to combine design methods with new technologies. From the perspective of the personalized design of derived images of art paintings, this study analyzes the new user demand generated by the current situation and background of personalized design, puts forward a new method of derivative design based on AI emotion analysis, verifies the feasibility of the new method by constructing a personalized design system of derived images of art paintings driven (...) by facial emotion features, and explores the method of combining AI emotion recognition, emotion analysis, and personalized design. This study provides new ideas for the design of art derivatives for the future with massive personalized demand. Thinking and practicing from the perspective of the development of new technology will promote the change of design paradigms in the digital age. (shrink)