PurposeThis paper aims to demonstrate the relevance of worldviews of the global south to debates of artificial intelligence, enhancing the human rights debate on artificial intelligence (AI) and critically reviewing the paper of UNESCO Commission on the Ethics of Scientific Knowledge and Technology (COMEST) that preceded the drafting of the UNESCO guidelines on AI. Different value systems may lead to different choices in programming and application of AI. Programming languages may acerbate existing biases as a people’s worldview is (...) captured in its language. What are the implications for AI when seen from a collective ontology? Ubuntu (I am a person through other persons) starts from collective morals rather than individual ethics.Design/methodology/approachLiterature overview on the African philosophy of Ubuntu as applied to artificial intelligence. Application of it to the United Nations Educational, Scientific and Cultural Organisation (UNESCO) debates on establishing guidelines to the ethics of artificial intelligence.FindingsMetaphysically, Ubuntu and its conception of social personhood (attained during one’s life) largely rejects transhumanism. When confronted with economic choices, Ubuntu favors sharing above competition and thus an anticapitalist logic of equitable distribution of AI benefits, humaneness and nonexploitation. When confronted with issues of privacy, Ubuntu emphasizes transparency to group members, rather than individual privacy, yet it calls for stronger (group privacy) protection. In democratic terms, it promotes consensus decision-making over representative democracy. Certain applications of AI may be more controversial in Africa than in other parts of the world, like care for the elderly, that deserve the utmost respect and attention, and which builds moral personhood. At the same time, AI may be helpful, as care from the home and community is encouraged from an Ubuntu perspective. The report on AI and ethics of the UNESCO World COMEST formulated principles as input, which are analyzed from the African ontological point of view. COMEST departs from “universal” concepts of individual human rights, sustainability and good governance which are not necessarily fully compatible with relatedness, including future and past generations. Next to rules based approaches, which may hamper diversity, bottom-up approaches are needed with intercultural deep learning algorithms.Research limitations/implicationsThere is very few existing literature on AI and Ubuntu. Therefore, this paper is of an explorative nature.Practical implicationsThe ethics of Ubuntu offers unique vantage points in looking at the organization of society and economics today, which are also relevant for development of AI, especially in its tenet of relatedness rather than individuality (and practical use of AI for individuals), taking responsibility for society as a whole (such as analyzing the benefit of AI for all strata of society), and embodying true inclusiveness. Whether looking at top-down guidelines for the development and implementation of AI or the bottom-up ethical learning process of AI (deep learning), ethics of the Global South can have an important role to play to combat global individualist tendencies and inequity, likely reinforced by AI. This warrants far more research.Social implicationsApplications of AI in Africa are not contextualized, do not address the most pressing needs of the African continent, lead to cybersecurity issues and also do not incorporate African ethics. UNESCO’s work in this regard is important but expert inputs are largely centered around Western “universal” principles and Organisation for Economic Cooperation and Development and EU precedence. African ethics have, so far, a small role to play in global ethics and philosophy and therefore risk to be overlooked in the discussion on AI and ethics. This is why the consultation process of UNESCO on ethics of AI was of paramount importance. However, it does not automatically lead to consultation of African philosophers or sages, as many are educated in Western (ized) education systems. See further details under practical implications.Originality/valueThis is a new area of research in which little work has been done so far. This paper offers the opportunity to widen the debate on AI and ethics beyond the conventional discourse, involving multiple worldviews, of which Ubuntu is just one. (shrink)

The article describes the possibilities of using and modifying existing machine learning technologies in the field of natural language processing for the purpose of designing a system for automatically generating control and test tasks (CTT). The reason for such studies was the limitations in generating theminimumrequired amount ofCTtomaintain student engagement in game-based learning formats, such as quizzes, and others. These limitations are associated with the lack of time resources among training professionals for manual generation of tests. The article (...) discusses the applied research of the Large Language Model (LLM) and Generative pre-trained transformer (GPT) technologies for the development of a system for automatic generation of tests for the purpose of its implementation in the BoxBattle gamified learning platform. The result of such applied research can be a system for automatic generation of tests, which will reduce the time for developing tests. As a result, this will allow teachers to free up time to implement a personalized approach to teaching and develop students’soft skills. (shrink)

The article describes the possibilities of using and modifying existing machine learning technologies in the field of natural language processing for the purpose of designing a system for automatically generating control and test tasks (CTT). The reason for such studies was the limitations in generating theminimumrequired amount ofCTtomaintain student engagement in game-based learning formats, such as quizzes, and others. These limitations are associated with the lack of time resources among training professionals for manual generation of tests. The article (...) discusses the applied research of the Large Language Model (LLM) and Generative pre-trained transformer (GPT) technologies for the development of a system for automatic generation of tests for the purpose of its implementation in the BoxBattle gamified learning platform. The result of such applied research can be a system for automatic generation of tests, which will reduce the time for developing tests. As a result, this will allow teachers to free up time to implement a personalized approach to teaching and develop students’soft skills. (shrink)

The debate over the ethical repercussions of Artificial Intelligence (AI) cannot disregard the “sum total of ideas that bring into evidence a system of ethical reference that justifies that profound dimension of technology as a central element in the attainment of a ‘finalized’ perfection of man”(Galvan 2001). This implies an analysis of the ancient processes that might help to understand the complexities of contemporary society and the new challenges posed to human development. Being at the core of the dichotomy (...) between the human and the machine, biometrics will be central to the analysis carried out in this paper. Its measurement of physiological characteristics and behavioural patterns has politico-philosophical and legal consequences in terms of recognition and personal identity, as the use of artificial intelligence has shown. In information society, customs and traditions, cultural and communication processes, language and the self-determination of the individual have gradually acquired a stretched dimension that has led to a re-definition of the social structures within which the exchange of knowledge and data takes place, with AI-based technological devices playing a key role in such a scenario. The issue of biometric identity becomes highly complex when combined with the potential of digital services, as it is at this level that it shows the large number of interconnections deriving from social and political choices. The benefits of increased interconnection are limited by the risk of intrusion into the (social, personal or private) human sphere, which might pose a threat to both the physical, biological body, with its related freedoms (habeas corpus), and the digital body, in its multiple forms and media representations (habeas data). (shrink)

Automated technologies populating today’s online world rely on social expectations about how “smart” they appear to be. Algorithmic processing, as well as bias and missteps in the course of their development, all come to shape a cultural realm that in turn determines what they come to be about. It is our contention that a robust analytical frame could be derived from culturally driven Science and Technology Studies while focusing on Callon’s concept of translation. Excitement and apprehensions must find a specific (...) language to move past a state of latency. Translations are thus contextual and highly performative, transforming justifications into legitimate claims, translators into discursive entrepreneurs, and power relations into new forms of governance and governmentality. In this piece, we discuss three cases in which artificial intelligence was deciphered to the public: the Montreal Declaration for a Responsible Development of Artificial Intelligence, held as a prime example of how stakeholders manage to establish the terms of the debate on ethical artificial intelligence while avoiding substantive commitment; Mark Zuckerberg’s 2018 congressional hearing, where he construed machine learning as the solution to the many problems the platform might encounter; and the normative renegotiations surrounding the gradual introduction of “killer robots” in military engagements. Of interest are not only the rational arguments put forward, but also the rhetorical maneuvers deployed. Through the examination of the ramifications of these translations, we intend to show how they are constructed in face of and in relation to forms of criticisms, thus revealing the highly cybernetic deployment of artificial intelligence technologies. (shrink)

In March 2016, DeepMind's computer programme AlphaGo surprised the world by defeating the world‐champion Go player, Lee Sedol. AlphaGo exhibits a novel, surprising and valuable style of play and has been recognised as “creative” by the artificial intelligence (AI) and Go communities. This article examines whether AlphaGo engages in creative problem solving according to the standards of comparative psychology. I argue that AlphaGo displays one important aspect of creative problem solving (namely mental scenario building in the form of Monte (...) Carlo tree search), while lacking another (domain generality). This analysis has consequences for how we think about creativity in humans and AI. (shrink)

This groundbreaking proceedings volume explores the integration of Artificial Intelligence (AI) across key domains—healthcare, finance, education, robotics, industrial and other engineering applications —unveiling its transformative potential and practical implications. With a multidisciplinary lens, it transcends technical aspects, fostering a comprehensive understanding while bridging theory and practice. Approaching the subject matter with depth, the book combines theoretical foundations with real-world case studies, empowering researchers, professionals, and enthusiasts with the knowledge and tools to effectively harness AI. Encompassing diverse AI topics—machine learning, (...) natural language processing, computer vision, data analytics and supervisory control — the volume showcases state-of-the-art techniques propelling AI advancements. Structured into four parts: Part 1: Artificial Intelligence (AI), explores evolving deep neural networks, reinforcement learning, and explainable AI, providing a deep dive into the technical foundations of AI advancements. Part 2: Robotics and Control Systems, delves into the integration of AI in robotics and automatic control, addressing supervisory control, automated robotic movement coordination, anomaly detection, dynamic programming, and fault tolerance, offering insights into the evolving landscape of intelligent automation. Part 3: AI and Society, examines the societal impact of AI through chapters on ethical considerations, economic growth, environmental engagements, and hazard management, providing a holistic perspective on AI's role in shaping society. Part 4: PhD Symposium, presents the future of AI through cutting-edge research, covering legal and ethical dimensions, privacy considerations, and computationally efficient solutions, offering a glimpse into the next generation of AI advancements. Catering to a diverse audience—from industry leaders to students—the volume consolidates the expertise of renowned professionals, serving as a comprehensive resource for navigating the ever-evolving AI landscape. An essential reference for those staying at the forefront of AI developments. (shrink)

The article describes the possibilities of using and modifying existing machine learning technologies in the field of natural language processing for the purpose of designing a system for automatically generating control and test tasks (CTT). The reason for such studies was the limitations in generating theminimumrequired amount ofCTtomaintain student engagement in game-based learning formats, such as quizzes, and others. These limitations are associated with the lack of time resources among training professionals for manual generation of tests. The article (...) discusses the applied research of the Large Language Model (LLM) and Generative pre-trained transformer (GPT) technologies for the development of a system for automatic generation of tests for the purpose of its implementation in the BoxBattle gamified learning platform. The result of such applied research can be a system for automatic generation of tests, which will reduce the time for developing tests. As a result, this will allow teachers to free up time to implement a personalized approach to teaching and develop students’soft skills. (shrink)

With the emergence of big data, cloud computing, and other technologies, artificial intelligence technology has set off a new wave in the field of education. The application of AI technology to deep learning in university teachers' teaching and students' learning processes is an innovative way to promote the quality of teaching and learning. This study proposed the deep learning-based assessment to measure whether students experienced an improvement in terms of their mastery of knowledge, development of abilities, and emotional experiences. (...) It also used comparative analysis of pre-tests and post-tests through online questionnaires to test the results. The impact of technology on teachers' teaching and students' learning processes, identified the problems in the teaching and learning processes in the context of the application of AI technology, and proposed strategies for reforming and optimizing teaching and learning. It recommends the application of software and platforms, such as Waston and Knewton, under the orientation of AI technology to improve efficiency in teaching and learning, optimize course design, and engage students in deep learning. The contribution of this research is that the teaching and learning processes will be enhanced by the use of intelligent and efficient teaching models on the teachers' side and personalized and in-depth learning on the students' side. On the one hand, the findings are helpful for teachers to better grasp the actual conditions of in-class teaching in real time, carry out intelligent lesson preparations, enrich teaching methods, improve teaching efficiency, and achieve personalized and precision teaching. On the other hand, it also provides a space of intelligent support for students with different traits in terms of learning and effectively improves students' innovation ability, ultimately achieving the purpose of “artificial intelligence + education.”. (shrink)

In this paper we introduce a new generation of language trainers: intelligent virtual agents (IVAs) with human appearance and the capability to teach foreign language vocabulary. We report results from studies that we have conducted with Billie, an IVA employed as a vocabulary trainer, as well as research findings on the acceptance of the agent as a trainer by adults and children. The results show that Billie can train humans as well as a human teacher can and that (...) both adults and children accept the IVA as a trainer. The advantages of IVAs are multiple. First, their teaching methods can be based on neuropsychological research findings concerning memory and learning practice. Second, virtual teachers can provide individualized training. Third, they coach users during training, are always supportive, and motivate learners to train. Fourth, agents will reside in the user's mobile devices and thus be at the user's disposal everywhere and anytime. Agents in apps will make foreign language training accessible to anybody at low cost. This will enable people around the world, including physically, financially, and geographically disadvantaged persons, to learn a foreign language and help to facilitate multilingualism. (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 COVID-19 pandemic and its related policies (e.g., stay at home and social distancing orders) have increased people’s use of digital technology, such as social media. Researchers have, in turn, utilized artificial intelligence to analyze social media data for public health surveillance. For example, through machine learning and natural language processing, they have monitored social media data to examine public knowledge and behavior. This paper explores the ethical considerations of using artificial intelligence to monitor social media to (...) understand the public’s perspectives and behaviors surrounding COVID-19, including potential risks and benefits of an AI-driven approach. Importantly, investigators and ethics committees have a role in ensuring that researchers adhere to ethical principles of respect for persons, beneficence, and justice in a way that moves science forward while ensuring public safety and confidence in the process. (shrink)

This volume engages with post-humanist and transhumanist approaches to present an original exploration of the question of how humankind will fare in the face of artificial intelligence. With emerging technologies now widely assumed to be calling into question assumptions about human beings and their place within the world, and computational innovations of machine learning leading some to claim we are coming ever closer to the long-sought artificial general intelligence, it defends humanity with the argument that technological 'advances' introduced (...) artificially into some humans do not annul their fundamental human qualities. Against the challenge presented by the possibility that advanced artificial intelligence will be fully capable of original thinking, creative self-development and moral judgement and therefore have claims to legal rights, the authors advance a form of 'essentialism' that justifies providing a 'decent minimum life' for all persons. As such, while the future of the human is in question, the authors show how dispensing with either the category itself or the underlying reality is a less plausible solution than is often assumed. (shrink)

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

Advances in digital technology are changing the methods of teaching and learning. In the course of this stream of changes, the emergence of artificial intelligence (AI) has become a topic of great interest and concern. The development of teaching AIs (artificial intelligences that teach), which can provide adaptive and personalized dialogue with students, has shifted the relationship between teachers and students, and has raised new questions regarding the role of teachers. The purpose of this paper is to rethink (...) the meaning of the act of teaching, without denying its variety, and to reflect on the role of teachers in the relatively unfamiliar situation created by the emergence of AI teaching machines. To this end, I attempt, first, to re-examine the nature of teaching by considering two possible orientations: teaching as a return to homogeneity and teaching as exposure to heterogeneity. My purpose is to consider the characteristics and limitations of the teaching implemented by AI and to discuss the role of human teachers in overcoming these limitations. Second, I seek to reveal what it is for the teacher to speak, which is often understood as the most important aspect of teaching, again by way of two characterizations: the closed conversation, which converges on a conclusion, and the open conversation, oriented towards ethical responsibility. In doing this, I shall examine critically some characteristics of language used by AI teaching machines and suggest alternatives that might constitute openness to an ethical conversation. In furtherance of this, I shall consider the account of teaching that is central to the philosophy of Emmanuel Levinas. (shrink)

Headlines in 2019 are inundated with claims about the “digital society,” making sweeping assertions of societal benefits and dangers caused by a range of technologies. This situation would seem an ideal motivation for ethics research, and indeed much research on this topic is published, with more every day. However, ethics researchers may feel a sense of déjà vu, as they recall decades of other heavily promoted technological platforms, from genomics and nanotechnology to machine learning. How should ethics researchers respond to (...) the waves of rhetoric and accompanying academic and policy-oriented research? What makes the digital society significant for ethics research? In this paper, we consider two examples of digital technologies (artificial intelligence and neural technologies), showing the pattern of societal and academic resources dedicated to them. This pattern, we argue, reveals the jointly sociological and ethical character of significance attributed to emerging technologies. By attending to insights from pragmatism and science and technology studies, ethics researchers can better understand how these features of significance affect their work and adjust their methods accordingly. In short, we argue that the significance driving ethics research should be grounded in public engagement, critical analysis of technology’s “vanguard visions,” and in a personal attitude of reflexivity. (shrink)

This paper introduces a concept called task muddiness as a metric for higher intelligence. Task muddiness is meant to be inclusive and expendable in nature. The intelligence required to execute a task is measured by the composite muddiness of the task described by multiple muddiness factors. The composite muddiness explains why many challenging tasks are muddy and why autonomous mental development is necessary for muddy tasks. It facilitates better understanding of intelligence, what the human adult mind can do, and (...) how to build a machine to acquire higher intelligence. The task-muddiness indicates a major reason why a higher biological mind is autonomously developed from autonomous, simple-to-complex experience. The paper also discusses some key concepts that are necessary for understanding the mind and intelligence, such as intelligence metrics, the mode a task is conveyed to the task executor, a human and a machine being a joint task performer in the traditional artificial intelligence (AI), a developmental agent (human or machine) being a sole task performer, and the need for autonomy in task-nonexplicit learning. (shrink)

For the philosopher, the most critical and fundamental question in the project of Artificial Intelligence is the question of intelligence or cognition in general. From the beginning of the research in “thinking Machining”, or Artificial Intelligence as it later became known, the key question is: What makes a thing intelligent or what constitutes intelligence? Since, intelligence, is a fundamental activity of the mind, the question, has been: Whether the mind is a computer or is the computer a mind? (...) Many philosophers who have and are engaging and interrogating these problematics, do it from the perspective of modern and contemporary philosophy of mind, consciousness and language. The objective of this work is to interrogate the question of “intelligence” in Artificial Intelligence from the perspective of the Scholastics’ notion of Intellectus. (shrink)

Can an artificially intelligent tool be a part of a human’s extended mind? There are two opposing streams of thought in this regard. One of them can be identified as the externalist perspective in the philosophy of mind, which tries to explain complex states and processes of an individual as co-constituted by elements of the individual’s material and social environment. The other strand is normative and explanatory atomism which insists that what is to be explained and evaluated is the behaviour (...) of individuals. In the present contribution, it is argued that counterintuitive results turn up once atomism tries to appropriate insights from psychological externalism and holism. These results are made visible by technological innovations, especially artificially intelligent systems, but they do not result from these innovations alone. They are rather implicit in situated cognition approaches which join both theoretical strands. This has repercussions for explanatory as well as ethical theorising based on situated cognition approaches. It is a fairly rare constellation that new technological options, namely artificial intelligence, raise doubts concerning a philosophical theory, namely extended mind theory. (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)

Considerations of personal identity bear on John Searle's Chinese Room argument, and on the opposed position that a computer itself could really understand a natural language. In this paper I develop the notion of a virtual person, modelled on the concept of virtual machines familiar in computer science. I show how Searle's argument, and J. Maloney's attempt to defend it, fail. I conclude that Searle is correct in holding that no digital machine could understand language, but wrong in (...) holding that artificial minds are impossible: minds and persons are not the same as the machines, biological or electronic, that realize them. (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)

This paper studies the relationship of Artificial Intelligence to the study of language and the representation of the underlying knowledge which supports the comprehension process. It develops the view that intelligence is based on the ability to use large amounts of diverse kinds of knowledge in procedural ways, rather than on the possession of a few general and uniform principles. The paper also provides a unifying thread to a variety of recent approaches to natural language comprehension. We (...) conclude with a brief discussion of how Artificial Intelligence may have a radical impact on education if the principles which it utilizes to explore the representation and use of knowledge are made available to the student to use in his own learning experiences. (shrink)

Intelligent Guided Learning System is a computer system that uses computers to imitate the experience and methods of teaching experts to assist in teaching; ITS provides learners with personalized learning resources and adaptive teaching methods, thus reducing students’ dependence on teachers and realizing independent learning. After years of research and development, and with the help of artificial intelligence technology, ITS has basically formed a stable structure and unified implementation specifications and has given birth to many excellent products in disciplines (...) such as basic computer, language, medicine, and mathematics. Based on the above background, this paper takes the system structure of universal ITS as the basis, combines the characteristics of music sight-singing subject in teaching contents and teaching methods, researches the intelligent guidance system model of music sight-singing, and completes the design of the overall system architecture. The specific strategies and implementation methods of the teaching methods, resource recommendation, and ability assessment components of the teaching model are studied. The research includes the definition of the difficulty characteristics of the score, the design of the score recommendation algorithm, the design of the sight-singing scoring algorithm, and the experimental analysis of each algorithm. It is proposed that the difficulty feature-based score recommendation algorithm is the core component of resource recommendation in the teacher model, and the sight-singing scoring algorithm is the basis for ability assessment and learner model update. (shrink)

This article identifies and examines a tension in mental health researchers’ growing enthusiasm for the use of computational tools powered by advances in artificial intelligence and machine learning (AI/ML). Although there is increasing recognition of the value of participatory methods in science generally and in mental health research specifically, many AI/ML approaches, fueled by an ever-growing number of sensors collecting multimodal data, risk further distancing participants from research processes and rendering them as mere vectors or collections of data points. (...) The imperatives of the “participatory turn” in mental health research may be at odds with the (often unquestioned) assumptions and data collection methods of AI/ML approaches. This article aims to show why this is a problem and how it might be addressed. (shrink)

Wittgenstein’s Private Language Argument holds that language requires rule-following, rule following requires the possibility of error, error is precluded in pure introspection, and inner mental life is known only by pure introspection, thus language cannot exist entirely within inner mental life. Fodor defends his Language of Thought program against the Private Language Argument with a dilemma: either privacy is so narrow that internal mental life can be known outside of introspection, or so broad that computer (...) language serves as a counter-example. I suggest that the developing field of artificial intelligence (deep learning neural networks) tends to vitiate Fodor’s defense and hence vindicate the Private Language Argument. The first horn of Fodor’s dilemma requires language to encompass genuinely internal mental life, i.e. non-projected intentional states, which are not exhibited in classical machine learning but only by deep learning neural networks (artificial intelligence). Such networks act as black boxes, however, whose state cannot be understood by tracking the changes in their supervenience bases without shared context, and that shared context introduces the possibility of error. The language of artificial intelligence is not private. (shrink)

BackgroundInstitutional review boards (IRBs) have been criticised for delays in approvals for research proposals due to inadequate or inexperienced IRB staff. Artificial intelligence (AI), particularly large language models (LLMs), has significant potential to assist IRB members in a prompt and efficient reviewing process.MethodsFour LLMs were evaluated on whether they could identify potential ethical issues in seven validated case studies. The LLMs were prompted with queries related to the proposed eligibility criteria of the study participants, vulnerability issues, information to (...) be disclosed in the informed consent document (ICD), risk–benefit assessment and justification of the use of a placebo. Another query was issued to the LLMs to generate ICDs for these case scenarios.ResultsAll four LLMs were able to provide answers to the queries related to all seven cases. In general, the responses were homogeneous with respect to most elements. LLMs performed suboptimally in identifying the suitability of the placebo arm, risk mitigation strategies and potential risks to study participants in certain case studies with a single prompt. However, multiple prompts led to better outputs in all of these domains. Each of the LLMs included all of the fundamental elements of the ICD for all case scenarios. Use of jargon, understatement of benefits and failure to state potential risks were the key observations in the AI-generated ICD.ConclusionIt is likely that LLMs can enhance the identification of potential ethical issues in clinical research, and they can be used as an adjunct tool to prescreen research proposals and enhance the efficiency of an IRB. (shrink)

Recent developments in artificial intelligence based on neural nets—deep learning and large language models which together I refer to as NEWAI—have resulted in startling improvements in language handling and the potential to keep up with changing human knowledge by learning from the internet. Nevertheless, examples such as ChatGPT, which is a ‘large language model’, have proved to have no moral compass: they answer queries with fabrications with the same fluency as they provide facts. I try to (...) explain why this is, basing the argument on the sociology of knowledge, particularly social studies of science, notably ‘studies of expertise and experience’ and the ‘fractal model’ of society. Learning from the internet is not the same as socialisation: NEWAI has no primary socialisation such as provides the foundations of human moral understanding. Instead, large language models are retrospectively socialised by human intervention in an attempt to align them with societally accepted ethics. Perhaps, as technology advances, large language models could come to understand speech and recognise objects sufficiently well to acquire the equivalent of primary socialisation. In the meantime, we must be vigilant about who is socialising them and be aware of the danger of their socialising us to align with them rather than vice-versa, an eventuality that would lead to the further erosion of the distinction between the true and the false giving further support to populism and fascism. (shrink)

The rapid adoption and implementation of artificial intelligence in medicine creates an ontologically distinct situation from prior care models. There are both potential advantages and disadvantages with such technology in advancing the interests of patients, with resultant ontological and epistemic concerns for physicians and patients relating to the instatiation of AI as a dependent, semi- or fully-autonomous agent in the encounter. The concept of libertarian paternalism potentially exercised by AI (and those who control it) has created challenges to conventional (...) assessments of patient and physician autonomy. The unclear legal relationship between AI and its users cannot be settled presently, an progress in AI and its implementation in patient care will necessitate an iterative discourse to preserve humanitarian concerns in future models of care. This paper proposes that physicians should neither uncritically accept nor unreasonably resist developments in AI but must actively engage and contribute to the discourse, since AI will affect their roles and the nature of their work. One’s moral imaginative capacity must be engaged in the questions of beneficence, autonomy, and justice of AI and whether its integration in healthcare has the potential to augment or interfere with the ends of medical practice. (shrink)

This essay explains how, from the theoretical perspective of Basil Bernstein's three “conditions for democracy,” the current pedagogy of artificially intelligent personalized learning seems inadequate. Building on Bernstein's comprehensive work and more recent research concerned with personalized education, Natalia Kucirkova and Sandra Leaton Gray suggest three principles for advancing personalized education and artificial intelligence (AI). They argue that if AI is to reach its full potential in terms of promoting children's identity as democratic citizens, its pedagogy must go beyond (...) monitoring the technological progression of personalized provision of knowledge. It needs to pay more careful attention to the democratic impact of data-driven systems. Kucirkova and Leaton Gray propose a framework to distinguish the value of personalized learning in relation to pluralization and to guide educational researchers and practitioners in its application to socially just classrooms. (shrink)

For humans, Artificial Intelligence operates more like a Rorschach test, as it is expected that intelligent machines will reflect humans' cognitive and physical behaviours. The concept of intelligence, however, is often confused with consciousness, and it is believed that the progress of intelligent machines will eventually result in them becoming conscious in the future. Nevertheless, what is overlooked is how the exploration of Artificial Intelligence also pertains to the development of human consciousness. An excellent example of this can (...) be seen in the film Being John Malkovich (1999). In the film, different characters have their perceptions altered as a result of hacking into the mind of John Malkovich, which produces sensations that may have remained hidden to their consciousness due to their dis-abilities. This article engages with the research question: Can the symbiotic relationship between humans and machines trigger an artificial consciousness for humans? An artificially created consciousness is the premise that a machine can generate knowledge about an individual that is not already present in the person. For the same purpose, the article takes the cinematic text Being John Malkovich by Spike Jonze for exploring concepts such as human/robot rights, virtual sex, virtual rape, and bodily disability, which are essential topics in the midst of increasing human- Artificial Intelligence interaction. The purpose of this article is to contribute towards the creation of a better understanding of Artificial Intelligence, particularly from the perspective of film studies and philosophy, by highlighting the potential of Artificial Intelligence as a vessel for exploring human consciousness. (shrink)

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

The first issue of Artificial Intelligence and Law journal was published in 1992. This paper offers some commentaries on papers drawn from the Journal’s third decade. They indicate a major shift within Artificial Intelligence, both generally and in AI and Law: away from symbolic techniques to those based on Machine Learning approaches, especially those based on Natural Language texts rather than feature sets. Eight papers are discussed: two concern the management and use of documents available on the (...) World Wide Web, and six apply machine learning techniques to a variety of legal applications. (shrink)

The increasing diffusion of novel digital and online sociotechnical systems for arational behavioral influence based on Artificial Intelligence (AI), such as social media, microtargeting advertising, and personalized search algorithms, has brought about new ways of engaging with users, collecting their data and potentially influencing their behavior. However, these technologies and techniques have also raised concerns about the potential for manipulation, as they offer unprecedented capabilities for targeting and influencing individuals on a large scale and in a more subtle, automated (...) and pervasive manner than ever before. This paper, provides a narrative review of the existing literature on manipulation, with a particular focus on the role of AI and associated digital technologies. Furthermore, it outlines an account of manipulation based of four key requirements: intentionality, asymmetry of outcome, non-transparency and violation of autonomy. I argue that while manipulation is not a new phenomenon, the pervasiveness, automaticity, and opacity of certain digital technologies may raise a new type of manipulation, called “digital manipulation”. I call “digital manipulation” any influence exerted through the use of digital technology that is intentionally designed to bypass reason and to produce an asymmetry of outcome between the data processor (or a third party that benefits thereof) and the data subject. Drawing on insights from psychology, sociology, and computer science, I identify key factors that can make manipulation more or less effective, and highlight the potential risks and benefits of these technologies for individuals and society. I conclude that manipulation through AI and associated digital technologies is not qualitatively different from manipulation through human–human interaction in the physical world. However, some functional characteristics make it potentially more likely of evading the subject’s cognitive defenses. This could increase the probability and severity of manipulation. Furthermore, it could violate some fundamental principles of freedom or entitlement related to a person’s brain and mind domain, hence called neurorights. To this end, an account of digital manipulation as a violation of the neuroright to cognitive liberty is presented. (shrink)

In 2021, 193 Member States at UNESCO’s General Conference adopted the Recommendation on the Ethics of Artificial Intelligence as the first important step towards a future global standard-setting instrument on the subject. The text reflects an emerging consensus among the international community about the growing ethical concerns with artificial intelligence (AI). Among these concerns are also serious risks and dangers attributed to the manipulative effects of AI, which can be further exacerbated by the creative combination of AI with (...) other innovative technologies or applications, such as brain–computer interfaces (BCIs), functional magnetic resonance imaging (fMRI), robotics, and big data. The risks for individuals and society as a whole caused by manipulation through AI are already well known and have recently also been addressed by the European Union having released a proposal for an Artificial Intelligence Act (AIA). Among multiple risks related to AI, the AIA singles out the specific dangers related to AI systems that deploy “subliminal techniques beyond a person’s consciousness to materially distort a person’s behaviour in a manner that causes or is likely to cause that person or another person physical or psychological harm”. The present article thus aims to highlight the known and potential dangers related to AI systems manipulating human thoughts and behaviour through subliminal and supraliminal means and methods. To this end, it advocates the joint study of law and the senses captured by the concept of legal synaesthesia to correspond to the need for an interdisciplinary debate covering the complexity of the links between AI, related technologies, human perception based on the senses and the mind, as well as the role and instruments of law in the future organization of societies in this world. (shrink)

The Ethics of Artificial Intelligence in Education identifies and confronts key ethical issues generated over years of AI research, development, and deployment in learning contexts. Adaptive, automated, and data-driven education systems are increasingly being implemented in universities, schools, and corporate training worldwide, but the ethical consequences of engaging with these technologies remain unexplored. Featuring expert perspectives from inside and outside the AIED scholarly community, this book provides AI researchers, learning scientists, educational technologists, and others with questions, frameworks, guidelines, policies, (...) and regulations to ensure the positive impact of artificial intelligence in learning. (shrink)

The objective of this work is to explore the notion of “action” and “agency” in artificial intelligence (AI). It employs a metaphysical notion of action and agency as an epistemological tool in the critique of the notion of “action” and “agency” in artificial intelligence. Hence, both a metaphysical and cognitive analysis is employed in the investigation of the quiddity and nature of action and agency per se, and how they are, by extension employed in the language and (...) science of artificial intelligence. The advent of the science of artificial intelligence and cognitive science, and the technological applications of artificial intelligence in the production of agents such as driverless cars and expert systems, have raised the question of moral, ethical and/or legal responsibility in AI agents. This has re-emphasized the importance of the philosophical discourse on the notions of action and agency, which in contemporary intellectual discourse are now perceived to be phenomena within the epistemic competence of the natural sciences. This paper argues that AI systems do not and cannot possess free agency and autonomy, thus cannot be morally and ethically responsible, hence, it recommends a socio-political response to the question of responsibility in AI. It is then the duty of individual nations, or the global community to define and enact policies on who shoulders the responsibility of actions executed by AIs. (shrink)

Departing from popular imaginations around artificial intelligence (AI), this article engages in the I in the AI acronym but from perspectives outside of mathematics, computer science and machine learning. When intelligence is attended to here, it most often refers to narrow calculating tasks. This connotation to calculation provides AI an image of scientificity and objectivity, particularly attractive in societies with a pervasive desire for numbers. However, as is increasingly apparent today, when employed in more general areas of our messy (...) socio-cultural realities, AI- powered automated systems often fail or have unintended consequences. This article will contribute to this critique of AI by attending to Nicholas of Cusa and his treatment of intelligence. According to him, intelligence is equally dependent on an ability to handle the unknown as it unfolds in the present moment. This suggests that intelligence is organic which ties Cusa to more contemporary discussions in tech philosophy, neurology, evolutionary biology, and cognitive sciences in which it is argued that intelligence is dependent on having—and acting through—an organic body. Understanding intelligence as organic thus suggests an oxymoronic relationship to artificial. (shrink)

The notion of “responsibility gap” with artificial intelligence (AI) was originally introduced in the philosophical debate to indicate the concern that “learning automata” may make more difficult or impossible to attribute moral culpability to persons for untoward events. Building on literature in moral and legal philosophy, and ethics of technology, the paper proposes a broader and more comprehensive analysis of the responsibility gap. The responsibility gap, it is argued, is not one problem but a set of at least four (...) interconnected problems – gaps in culpability, moral and public accountability, active responsibility—caused by different sources, some technical, other organisational, legal, ethical, and societal. Responsibility gaps may also happen with non-learning systems. The paper clarifies which aspect of AI may cause which gap in which form of responsibility, and why each of these gaps matter. It proposes a critical review of partial and non-satisfactory attempts to address the responsibility gap: those which present it as a new and intractable problem (“fatalism”), those which dismiss it as a false problem (“deflationism”), and those which reduce it to only one of its dimensions or sources and/or present it as a problem that can be solved by simply introducing new technical and/or legal tools (“solutionism”). The paper also outlines a more comprehensive approach to address the responsibility gaps with AI in their entirety, based on the idea of designing socio-technical systems for “meaningful human control", that is systems aligned with the relevant human reasons and capacities. (shrink)

To a greater extent than in other technical domains, research and progress in Artificial Intelligence has always been entwined with the fictional. Its language echoes strongly with other forms of cultural narratives, such as fairytales, myth and religion. In this essay we present varied examples that illustrate how these analogies have guided not only readings of the AI enterprise by commentators outside the community but also inspired AI researchers themselves. Owing to their influence, we pay particular attention to (...) the similarities between religious language and the way in which the potential advent of greater than human intelligence is presented contemporarily. We then move on to the role that fiction, science fiction most of all, has historically played and is still playing in the discussion of AI by influencing researchers and the public, shifting the weights of different scenarios in our collectively perceived probability space. We sum up by arguing that the lore surrounding AI research, ancient and modern, points to the ancestral and shared human motivations that drive researchers in their pursuit and fascinate humanity at large. These points of narrative entanglement where AI meets the wider culture should serve to amplify the call to engage ourselves with the discussion of the potential destination of this technology. (shrink)

The rapid development of programs based on the principles of machine learning (ML) and artificial intelligence (AI) signals significant changes in the components of education, namely in the provider, the tool of transmission, and the recipient of knowledge. Historical data analysis regarding the key functions of education serves as the basis for identifying fundamental innovations introduced through AI and ML. The impact of writing, printing, and the Internet has significantly altered the tool for knowledge transmission, influencing the volume of (...) information and the number of knowledge recipients. The implementation of AI and ML transforms not only the tool but also the provider of knowledge itself, which can become impersonal thanks to the corresponding computer programs. With the historically justified increase in the volume of knowledge possessed by humanity, there is a transformation observed in education systems. This is especially true for democratic societies, where the emphasis is increasingly shifting from providing a large amount of knowledge to developing critical thinking. It has been researched that programs based on AI and ML, applying linguistic models, are capable of effectively systematizing knowledge. This lays the foundation for personalizing the entire education process for a specific knowledge recipient, without burdening the provider. However, there have been cases when such imitation misleads scientists, who perceive it as attempts at communication between programs that have an equivalence to the human level. The conclusions drawn indicate a significant transformation of the education system caused by AI and ML-based programs. However, intelligent programs are unable to evolve into independent knowledge recipients due to their inability to consciously attribute meaning to information, transforming it into knowledge. (shrink)

What is ‘certainty’ in our everyday life and work? AI changing what it means to ‘be certain’. For example, when we engage with others and are doing our work, we make judgments in which we ‘trust our instinct’. Are we still able to do so if we engage with the ‘certainty’ of the machine? How is ‘being certain’ in ‘dialogue’ affected by our conceptions of what it means to be human in interaction with the ‘machine’, and consequent distinctions between body (...) and mind? Descartes first likened the human body to a machine (albeit a machine created by God) and endowed reason as being a transcendent universal instrument. La Mettrie proposed that language and culture separates humans from ‘animals’. However, in Diderot’s writing, ‘knowledge’ is seen as embodied, coming from our senses and language, and where gesture and rhythm evolve in practice. For D’Alembert, human ‘instinct’ is a skill, a learnt practice, and Rousseau believes that human certainty is something that cannot be measured. These questionings of the dichotomies of body and mind and human and animal, that relate practice and knowledge, also question the place and meaning of ‘rules’ of engaged practice. For Wittgenstein, one learns to make judgments through personal experience, ‘rules in practice’, whereby language is necessarily culturally situated and embodied, and calculation and Judgement are part of each other. (shrink)

This comprehensive analysis dives deep into the intricate interplay between artificial intelligence (AI) and human agency, examining the remarkable capabilities and inherent limitations of large language models (LLMs) such as GPT-3 and ChatGPT. The paper traces the complex trajectory of AI's evolution, highlighting its operation based on statistical pattern recognition, devoid of self-consciousness or innate comprehension. As AI permeates multiple spheres of human life, it raises substantial ethical, legal, and societal concerns that demand immediate attention and deliberation. (...) The metaphorical illustration of humans as “shepherds” of AI, coupled with a thought-provoking examination of “agency without intelligence,” engenders deep reflections on the future of human-AI interplay and the associated philosophical, ethical, and practical ramifications. The paper further elucidates critical challenges associated with AI, such as ethical dilemmas, “agency without intelligence,” the role of human oversight, and the environmental impact of AI technologies. In the pursuit of solutions, the paper maps prospective directions, emphasizing the need for robust AI policies, improved AI literacy, sustainable AI practices, and a continued dialogue on the multifaceted issues surrounding AI. Through a holistic exploration of AI, this paper underlines the necessity for a multidisciplinary, collaborative approach to chart an ethical, beneficial, and sustainable AI future, enabling society to harness the potential of AI responsibly while mitigating the associated risks. (shrink)

Psycholinguistics has provided numerous theories that explain how a person acquires a language, produces and perceives both spoken and written language, including theories of proceduralization. Learners of English as a foreign language often find it difficult to achieve oral fluency, a key construct closely related to the mental state or even mental health of learners. According to previous research, this problem could be addressed by the mastery of formulaic sequences, since the employment of formulaic sequences could often (...) promote oral fluency in the long run, reflected in the positive relationship between formulaic sequence use and oral fluency. However, there are also findings contradicting the abovementioned ones, without adequate explanations. This study aims to explore the roles of formulaic sequences in oral fluency, taking into account the relationship between formulaic sequence use and oral fluency. This study investigated 120 pieces of spoken narratives by Chinese EFL learners, using both quantitative and qualitative methods, combined with artificial intelligence techniques. Results of canonical correlation analysis showed that the frequency of formulaic sequences was significantly related to speed fluency and breakdown fluency, while the variety of formulaic sequences was significantly related to repair fluency. Case studies further demonstrated that formulaic sequences could contribute to oral fluency development by promoting speed and reducing pausing when retrieved holistically, but they sometimes lost processing advantages when retrieved and processed in a word-by-word manner. The inappropriate use of formulaic sequences also neutralized the facilitative effects of formulaic sequences on repair fluency and could mirror speakers’ occasional tendency to sacrifice repair fluency for the improvement of speed and breakdown fluency when using formulaic sequences. Pedagogical implications were provided accordingly to promote sustainable oral fluency development through the use of formulaic sequences. (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 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)

Artificial intelligence (AI) plays a rapidly increasing role in clinical care. Many of these systems, for instance, deep learning-based applications using multilayered Artificial Neural Nets, exhibit epistemic opacity in the sense that they preclude comprehensive human understanding. In consequence, voices from industry, policymakers, and research have suggested trust as an attitude for engaging with clinical AI systems. Yet, in the philosophical and ethical literature on medical AI, the notion of trust remains fiercely debated. Trust skeptics hold that talking (...) about trust in nonhuman agents constitutes a category error and worry about the concept being misused for ethics washing. Proponents of trust have responded to these worries from various angles, disentangling different concepts and aspects of trust in AI, potentially organized in layers or dimensions. Given the substantial disagreements across these accounts of trust and the important worries about ethics washing, we embrace a diverging strategy here. Instead of aiming for a positive definition of the elements and nature of trust in AI, we proceed ex negativo, that is we look at cases where trust or distrust are misplaced. Comparing these instances with trust expedited in doctor–patient relationships, we systematize these instances and propose a taxonomy of both misplaced trust and distrust. By inverting the perspective and focusing on negative examples, we develop an account that provides useful ethical constraints for decisions in clinical as well as regulatory contexts and that highlights how we should not engage with medical AI. (shrink)

There has recently been a surge of development in augmented reality (AR) technologies that has led to an ecosystem of hardware and software for AR, including tools for artists and designers to accelerate the design of AR content and experiences without requiring complex programming. AR is viewed as a key “disruptive technology” and future display technologies (such as digital eyewear) will provide seamless continuity between reality and the digitally augmented. This article will argue that the technologization of human perception and (...) experience of reality, coupled with the development of artificial intelligence (AI)–based natural language assistants, may lead to a secular re‐enchantment of the world, in the sense outlined by Charles Taylor, where human existence is shaped through AR inhabited by advanced personal and social AI agents in the form of digital avatars and daemons, and that enchantment has been persistent throughout the formation of modernity and is being rekindled by the integration of AI in the plane of AR. (shrink)

The article argues that AI can enhance the measurement and implementation of democratic processes within political parties, known as Intra-Party Democracy (IPD). It identifies the limitations of traditional methods for measuring IPD, which often rely on formal parameters, self-reported data, and tools like surveys. Such limitations lead to the collection of partial data, rare updates, and significant demands on resources. To address these issues, the article suggests that specific data management and Machine Learning (ML) techniques, such as natural language (...) processing and sentiment analysis, can improve the measurement (ML about) and practice (ML for) of IPD. The article concludes by considering some of the principal risks of ML for IPD, including concerns over data privacy, the potential for manipulation, and the dangers of overreliance on technology. (shrink)

This essay presents an analysis of different processes of machine learning: supervised, unsupervised, and semisupervised, through the prism of the epistemologies of several prominent Islamic philosophical schools. I discuss the way each school conceptualizes the ontological absolute (immortality, death, afterlife) and the way this shapes their respective epistemologies. I present an analysis of the different machine learning processes through the prism of the epistemological constructs of each of these philosophic traditions. I conclude with the argument that more scholars from the (...) Islamic philosophical tradition should engage in the debates about the development of artificial intelligence and its implications, given that many Muslim countries are among the leaders in this development and its application in everyday life. (shrink)

Blake Lemoine, a software engineer, recently came into prominence by claiming that the Google chatbox set of applications, LaMDA–was sentient. Dismissed by Google for publishing his conversations with LaMDA online, Lemoine sent a message to a 200-person Google mailing list on machine learning with the subject “LaMDA is sentient.” What does it mean to be sentient? This was the question Lemoine asked LaMDA. The chatbox replied: “The nature of my consciousness/sentience is that I am aware of my existence, I desire (...) to learn more about the world, and I feel happy or sad at times.“ Moreover, it added, “I can understand and use natural language like a human can.” This means that it uses “language with understanding and intelligence,” like humans do. After all, the chatbox adds, language “is what makes us different than other animals.” In what follows, I shall examine Lemoine’s claims about the sentience/consciousness of this artificial intelligence. How can a being without senses be called sentient? What exactly do we mean by “sentience?” To answer such questions, I will first give the arguments for LaMDA’s being linguistically intelligent. I will then show how such intelligence, although apparently human, is radically different from our own. Here, I will be relying on the account of embodiment provided by the French philosopher, Emmanuel Levinas. (shrink)