Philosophy Of Artificial Intelligence Research Articles

Book review: Coeckelbergh, Mark (2022): The political philosophy of AI

Book review: Coeckelbergh, Mark (2022): The political philosophy of AI

The New Old Logic of AI: A Review of Mark Coeckelbergh’s The Political Philosophy of AI and Calvin Lawrence’s Hidden in White Sight

The New Old Logic of AI: A Review of Mark Coeckelbergh’s The Political Philosophy of AI and Calvin Lawrence’s Hidden in White Sight

Culturological reconstruction of ChatGPT's socio-cultural threats and information security of Russian citizens

The subject of the study is the socio-cultural threats to the information security of Russian citizens associated with ChatGPT technologies (Chat Generative Pre-trained Transformer, a machine-generated text response generator simulating a dialogue). The object of research − evaluation of the ratio of advantages and threats of generative language models based on "machine learning" in modern (2021-2023) scientific literature (journals HAC K1, K2 and Scopus Q1, Q2). The scientific novelty of the research lies in the culturological approach to the analysis of threats to the security of Russian citizens associated with the use of ChatGPT as one of the technologies of "artificial intelligence". The formulation of the problem of the classical Turing test "to distinguish a person from a machine" is characterized as a scholastic abstraction, instead a more correct and productive approach is proposed: a socio-cultural assessment of the value (based on cultural axiology) of new computer technologies. The starting point of the analysis is the determination of socio-cultural value (or, conversely, damage) as a result of the use of generative language models based on machine learning. Further, the contribution and responsibility of various socio-cultural subjects of its creation and application are revealed − user, creator and developer. The result of the application of the proposed approach is the deconstruction of the discourse of the "philosophy of artificial intelligence" in terms of uncritical translation of developer declarations intended for marketing and attracting financing. Hypertrophied perception, precariously balancing on the edge of utopia and dystopia, is assessed as a risk of incorrect identification and ranking of threats to information security. Assumptions about the hypothetical "superweapon of psychological warfare" mask modern incidents of cross-border leakage of confidential data, the risks of being held accountable for publishing deliberately false information and illegal content as a result of using ChatGPT. National security measures are recommended, including restrictive measures and increasing the general civil culture of information security of users, as well as the orientation of domestic developments of solutions of this type on traditional values, socio-cultural identity and interests of Russian citizens.

The Political Philosophy of ai: An Introduction, written by Mark Coeckelbergh

The Political Philosophy of ai: An Introduction, written by Mark Coeckelbergh

Artificial Intelligence and Service Quality of Telecommunication Firms in Nigeria

Globally, artificial intelligence (AI) technology spans various industries, but relatively little attention is given to the use of AI technologies by telecommunication industries. This study evaluated the effect of AI on the service quality of telecommunications companies in Nigeria, specifically the effect of data mining, machine learning, and chatbots on the service quality of these firms. The research employed a survey research design, and its population was heterogeneous. A sample size of 400 participants was chosen using Taro Yamane's formula, and the Cronbach alpha test yielded an average of 75%, confirming the reliability of the instrument. To analyze the data collected, descriptive and ordinary least squares regression methods were used. The study revealed that data mining and chatbots exhibited a significant positive effect while machine learning showed a negative relationship to the service quality of the telecommunications industry. Based on these findings, it is concluded that artificial intelligence affects service quality in Nigeria, with strong reference to data mining and chatbot, which enhance the quality of service to customers in Nigeria. It is therefore recommended that telecommunication firms in Nigeria should embrace the philosophy of AI to improve their quality of service.

Artificial Intelligence and the Problem of Judgment

AbstractWill existing forms of artificial intelligence (AI) lead to genuine intelligence? How is AI changing our society and politics? This essay examines the answers to these questions in Brian Cantwell Smith's The Promise of Artificial Intelligence and Mark Coeckelbergh's The Political Philosophy of AI with a focus on their central concern with judgment—whether AI can possess judgment and how developments in AI are affecting human judgment. First, I argue that the existentialist conception of judgment that Smith defends is highly idealized. While it may be an appropriate standard for intelligence, its implications for when and how AI should be deployed are not as clear as Smith suggests. Second, I point out that the concern with the displacement of judgment in favor of “reckoning” (or calculation) predates the rise of AI. The meaning and implications of this trend will become clearer if we move beyond ontology and metaphysics and into political philosophy, situating technological changes in their social context. Finally, I suggest that Coeckelbergh's distinctly political conception of judgment might offer a solution to the important boundary-drawing problem between tasks requiring judgment and those requiring reckoning, thus filling a gap in Smith's argument and clarifying its political stakes.

Cybernetic animism: Voice and AI in conversation

This Voicing explores the theoretical and material connections between Artificial Intelligence (AI) and voice. The Voicing is in three-parts encompassing: a theoretical introduction with a taxonomy for voice and AI, an extract from artist K. Allado-McDowell’s new work Air Age Blueprint and an interview based on such text. Allado-McDowell pioneered the field of human–artificial intelligence interaction and literature. With their book Pharmako-AI, written in collaboration with GPT-3, Allado-McDowell stretched the limits of language creation. Francesco Bentivegna worked as artist in the liminal space of cyborgean voices and recently completed their Ph.D. on voice, AI and synthetic personas. As an exercise in philosophy of AI, voice studies and artistic research, Allado-McDowell and Bentivegna move in conversation through biases, vibes and language, exploring narrative, science and theory.

Non-Stupidity Condition and Pragmatics in Artificial Intelligence

Symbol Grounding Problem (SGP) (Harnad 1990) is commonly considered one of the central challenges in the philosophy of artificial intelligence as its resolution is deemed necessary for bridging the gap between simple data processing and understanding of meaning and language. SGP has been addressed on numerous occasions with varying results, all resolution attempts having been severely, but for the most part justifiably, restricted by the Zero Semantic Commitment Condition (Taddeo and Floridi 2005). A further condition that demands explanatory power in terms of machine-to-human communication is the Non-Stupidity Condition (Bringsjord 2013) that demands an SG approach to be able to account for plausibility of higher-level language use and understanding, such as pragmatics. In this article, we undertake the endeavour of attempting to explain how merging certain early requirements for SG, such as embodiment, environmental interaction (Ziemke 1998), and compliance with the Z-Condition with symbol emergence (Sun 2000; Tangiuchi et al. 2016, etc.) rather than direct attempts at symbol grounding can help emulate human language acquisition (Vogt 2004; Cowley 2007). Along with the presumption that mind and language are both symbolic (Fodor 1980) and computational (Chomsky 2017), we argue that some rather abstract aspects of language can be logically formalised and finally, that this melange of approaches can yield the explanatory power necessary to satisfy the Non-Stupidity Condition without breaking any previous conditions.

Machines and Human Epistemology

Introduction. The article analyzes the structure of the epistemology of knowledge of weak artificial intelligence in comparison with the structure of human knowledge. The article was written within the framework of one of the most demanded branch sections of philosophy – the philosophy of artificial intelligence. The novelty of the research is based on the idea of applying the analysis of knowledge developed within the framework of analytical epistemology to the field of artificial intelligence.Methodology and sources. The article is written in the framework of analytical tradition in philosophy. We use conceptual analysis to analyze the most crucial aspects of knowledge. This method assumes that in order to explain a complex phenomenon, it is necessary to analyze its components. This method formed the basis of an analytical discussion about knowledge in the second half of the 20th century. The article also uses comparative analysis.Results and discussion. People's knowledge is characterized by three essential characteristics – the presence of information-bearing mental states, their reliability, and factuality. We analyzed to what extent the information-carrying internal states of a weak AI correspond to these qualities. The authors concluded that internal states can be considered beliefs if they are weakly interpreted, they can have a high degree of reliability under certain conditions, and they can have factuality if we accept that a weak AI has beliefs.Conclusion. A weak interpretation of the concept of belief allows us to argue that neural networks are capable of having beliefs. A more rigorous interpretation of the concept of belief also includes the requirement to understand the meaning. However, we do not have at our disposal a satisfactory theory of understanding meaning. In this case, the condition of reliability is the only criterion of knowledge to which the functional states of machines can correspond in the case of certain tasks, in connection with which the problem of generality arises especially acutely.

Artificial Instinct: Lem’s Robots as a Model Case for AI

In the seventy years since AI became a field of study, the theoretical work of philosophers has played increasingly important roles in understanding many aspects of the AI project, from the metaphysics of mind and what kinds of systems can or cannot implement them, the epistemology of objectivity and algorithmic bias, the ethics of automation, drones, and specific implementations of AI, as well as analyses of AI embedded in social contexts (for example). Serious scholarship in AI ethics sometimes quotes Asimov’s speculative laws of robotics as if they were genuine proposals, and yet Lem remains historically undervalued as a theorist who uses fiction as his vehicle. Here, I argue that Lem’s fiction (in particular his fiction about robots) is overlooked but highly nuanced philosophy of AI, and that we should recognize the lessons he tried to offer us, which focused on the human and social failures rather than technological breakdowns. Stories like “How the World Was Saved” and “Upside Down Evolution” ask serious philosophical questions about AI metaphysics and ethics, and offer insightful answers that deserve more attention. Highlighting some of this work from The Cyberiad and the stories in Mortal Engines in particular, I argue that the time has never been more appropriate to attend to his philosophy in light of the widespread technological and social failures brought about by the quest for artificial intelligence. In service of this argument, I discuss some of the history and philosophical debates around AI in the last decades, as well as contemporary events that illustrate Lem’s strongest claims in critique of the human side of AI.

The Myth of Artificial Intelligence: Why Computers Can't Think the Way We Do

The Myth of Artificial Intelligence: Why Computers Can't Think the Way We Do

What’s Wrong with Automated Influence

AbstractAutomated Influence is the use of Artificial Intelligence (AI) to collect, integrate, and analyse people’s data in order to deliver targeted interventions that shape their behaviour. We consider three central objections against Automated Influence, focusing on privacy, exploitation, and manipulation, showing in each case how a structural version of that objection has more purchase than its interactional counterpart. By rejecting the interactional focus of “AI Ethics” in favour of a more structural, political philosophy of AI, we show that the real problem with Automated Influence is the crisis of legitimacy that it precipitates.

Neurophilosophy, Philosophy of Neuroscience, and Philosophy of Artificial Intelligence: The Problem of Distinguishing

Neurophilosophy is understood as different areas of philosophy, for example, the philosophy of neuroscience, the philosophy of artificial intelligence, or eliminative materialism. This excessive interpretation of the term is due to the fact that the understanding of the subject area of this discipline is still incomplete. For example, one of the earliest definitions of neurophilosophy given by P.S. Churchland stated reduction of psychology to neurosciences. In modern views, the idea of neurophilosophy as an attempt to justify eliminative materialism is outdated and does not correspond to reality. The article analyzes the terms “philosophy of neuroscience,” “neurophilosophy,” and “philosophy of artificial intelligence” and also offers a variant of their differentiation. The authors focus on the common and different features, using the example of G.M. Edelman's theory of consciousness and the concept of connectionism for weak artificial intelligence. It is concluded that integral use of the term “neurophilosophy” should be abandoned. As a result, the term “neurophilosophy” should be understood as a direction in philosophy of the early 21st century, applying neuroscientific concepts to solve traditional philosophical problems, while the philosophy of specific neurosciences can be considered primarily as a field in the philosophy of science that formulates and solves problems of specific neurosciences as well as of the entire neuroscientific direction. The philosophy of artificial intelligence is an area in philosophy that answers the question of what non-biological intelligence is and what makes it possible; in other words, it is a philosophical and methodological basis for the study of non-biological intelligence. In the formation of neurosciences and their scientific and philosophical basis, we are still at the first methodological stage of the analysis and differentiation of hypotheses. After some time, there will emerge a philosophy of neuroscience, as the basis of all existing neuroscientific theories, and then this term will acquire greater significance.

Architectural Approach to Design of Emotional Intelligent Systems

Over the past decades, due to the course towards digitalization of all areas of life, interest in modeling and creating intelligent systems has increased significantly. However, there are now a stagnation in the industry, a lack of attention to analog and bionic approaches as alternatives to digital, numerous speculations on “neuro” issues for commercial and other purposes, and an increase in social and environmental risks. The article provides an overview of the development of artificial intelligence (AI) conceptions toward increasing the human likeness of machines: from the key ideas of A. Turing and J. von Neumann, who initiated the digitalization of society, to discussions about the definition of AI and the emergence of conceptions of strong and weak AI. Special attention is paid to the approach of A. Sloman, to ideas about the architecture and design of complex artificial systems are considered, which make it possible to “emotionally” expand the idea of weak/strong AI. In the article's section on the necessity and possibility of incorporating emotions into the architecture of AI, the authors reveal the goals and methodological limitations for creating an emotional artificial agent. In addition, the article briefly presents the main principles of the authors' architectural approach to the creation of emotional intellectual systems on the example of the cognitive-affective model of architecture, which allow modeling the impact of emotions on the cognitive processes involved in decision-making processes. The described architectural approach to modeling intelligent systems can be used as a conceptual basis for discussing and formulating a strategy for the development of neurocomputing, philosophy of artificial intelligence, and experimental philosophy, for developing innovative research programs, formulating and solving theoretical and methodological problems.

Artificial intelligence in nursing: Priorities and opportunities from an international invitational think-tank of the Nursing and Artificial Intelligence Leadership Collaborative.

AimTo develop a consensus paper on the central points of an international invitational think-tank on nursing and artificial intelligence (AI).MethodsWe established the Nursing and Artificial Intelligence Leadership (NAIL) Collaborative, comprising interdisciplinary experts in AI development, biomedical ethics, AI in primary care, AI legal aspects, philosophy of AI in health, nursing practice, implementation science, leaders in health informatics practice and international health informatics groups, a representative of patients and the public, and the Chair of the ITU/WHO Focus Group on Artificial Intelligence for Health. The NAIL Collaborative convened at a 3-day invitational think tank in autumn 2019. Activities included a pre-event survey, expert presentations and working sessions to identify priority areas for action, opportunities and recommendations to address these. In this paper, we summarize the key discussion points and notes from the aforementioned activities.Implications for nursingNursing's limited current engagement with discourses on AI and health posts a risk that the profession is not part of the conversations that have potentially significant impacts on nursing practice.ConclusionThere are numerous gaps and a timely need for the nursing profession to be among the leaders and drivers of conversations around AI in health systems.ImpactWe outline crucial gaps where focused effort is required for nursing to take a leadership role in shaping AI use in health systems. Three priorities were identified that need to be addressed in the near future: (a) Nurses must understand the relationship between the data they collect and AI technologies they use; (b) Nurses need to be meaningfully involved in all stages of AI: from development to implementation; and (c) There is a substantial untapped and an unexplored potential for nursing to contribute to the development of AI technologies for global health and humanitarian efforts.

AI urbanism: a design framework for governance, program, and platform cognition

Historically, the dynamic between philosophy of artificial intelligence and its practical application has been essential for the development of both, and thus the encounter between theory of AI and architectural/urban theory should be a site of considerable productivity. However, in many ways, it is not. This is due to two primary factors, one arising from each side of this encounter. First, legacies of overly-anthropomorphic models of AI permeate design discourses, where issues of how well AI can be constrained to social issues of philosophy of mind exclude more foundational and cross-cultural questions about artificial intelligence as material process in the physical world that could inform new philosophical insights. Concurrently, the mobilization of investment in “Smart Cities” discourses dominates the space of application of AI at urban scale in ways that prematurely fixes solutions in the skeuomorphic image of architectural and urban conventions. To break this impasse, we held a series of think-tanks, workshops, and design charettes that brought together leading figures in philosophy of artificial intelligence, urban design, and commercial AI platforms. The goal was to re-think from first principles how alternative philosophical models of AI as a distributed, discontinuous, landscape-scale technology in a direct encounter with the applications in contexts of ecological sensing, automation’s impact on urban form, and issues of algorithmic governance. The design brief for this research establishes a generative framework for conceiving how embedded machine sensing and intelligence is already changing urban form (but unrecognized) and could change it in the future (based on more appropriate design projections). The framework focuses on issues of urban zoning and architectural programming, data modeling and governance, platform cognition and design, and how these inform shifts in dynamics of public and private institutions.

Blockchain, black magic and event ontology Interview with Alexander Boldachev

Alexander Boldachev is a Russian philosopher, futurologist (member of the Association of Futurologists of Russia), author of books and articles on universal evolutionism, biological evolution, philosophy of artificial intelligence, temporal ontology, epistemology, and logic. System architect and analyst of blockchain applications, author of articles on the problems of trust technologies, eGovernment, web 3.0, semantic modeling of complex systems, speaker of many specialized conferences.

THE PROBLEM OF SYNTHESIS OF CONNECTIONISM AND SYMBOLISM IN MODELS OF WEAK ARTIFICIAL INTELLIGENCE

The idea of conceptual mutual exclusion of the approaches of connectionism and symbolism in the philosophy of artificial intelligence is proposed. It is shown that the basic concepts of both concepts are complementary in the philosophical and methodological terms. The key idea of the study is the assumption of the need to find ways to consistently synthesis the approaches of connectionism and symbolism.

Philosophy of Artificial Intelligence

In the article, the author substantiates the thesis that the development of artificial intelligence technology is closely related not only to discoveries in the field of natural science, anthropology and medicine, but also achievements in the field of philosophy of knowledge and cognitive sciences. The author conducted a philosophico-epistemological analysis of the problems of improving the neural network as the core of modern artificial intelligence led to the conclusion that the principles of functioning of the neural network corresponding to such principles of the cognitive process discovered and studied in the philosophical concepts of New Time, such as J. Locke’s apriorism, I. Kant’s apriorism other. The results of the comparative study allowed the author to come to the following conclusion: the improvement of the abilities of the neural network studied by S. Haikin, S. Russell, P. Norvig (“evidence of the answer”, “classification of images” and “reliability of the decision”) is possible when relying on the epistemological ideas of J. Locke, using Kant’s principles (“synthetic unity of apperception”, “I think”) and searching for the algorithm of neural network formation of the ability to create antinomies in artificial intelligence. Further development of artificial intelligence based on the neural network can also be based on the theory of cognition of T. Hobbes, R. Descartes, B. Spinoza, G. V. F. Hegel and the results of modern cognitive sciences.

On the origin of mental representations

The symbol grounding problem raises its head in the fields of the philosophy of AI, philosophy of psychology and philosophy of cognitive sciences. The solution to the symbol grounding problem must account for the genesis of mental representations in the world. It has to offer a strategy for grounding mental representations in the objective domain. Orthodox representationalist theories do not provide a satisfactory reply to the symbol grounding problem. On the other hand, there are embodied-enactivist approaches that dissolve the problem but only at the cost of representations and internal phenomenal states. The code model of biosemiotics provides a biologically viable (i.e., mechanistic) venue for developing a new solution to the problem. For the same reason, it could reconcile representationalism to the embodied approach.