The essay explores the intersection of the Theory of Mind (T.O.M.) and Artificial Intelligence (AI), emphasizing the potential for AI to emulate cognitive processes fundamental to human social interactions. T.O.M., a concept crucial for understanding and interpreting human behavior through attributed mental states, contrasts with AI's behaviorist approach, which is rooted in data-driven pattern analysis and predictions. By examining foundational insights from cognitive sciences and the operational models of AI, this analysis highlights the potential advancements and implications of (...) integrating T.O.M.-like capabilities into AI systems. The discussion pivots around three critical questions: whether AI should emulate T.O.M. to enhance human interactions if AI can maintain its data-driven model while integrating cognitive processes, and how AI can expand its capabilities in social contexts. The arguments suggest that incorporating T.O.M.-like processes could significantly improve AI's interaction quality without compromising its analytical strengths, pointing towards a future where AI not only predicts but also empathizes, offering more nuanced and culturally aware interactions. This synthesis of cognitive theories and computational strategies advocates for deeper integration of diverse datasets and advanced computing methodologies, aiming to transform AI into a more empathetic and effective participant in human social environments. -/- Keywords: Theory of Mind, Artificial Intelligence, Human-AI Interaction, Cognitive Processes, Data-Driven Analysis. (shrink)

In October 2016, the White House, the European Parliament, and the UK House of Commons each issued a report outlining their visions on how to prepare society for the widespread use of artificial intelligence. In this article, we provide a comparative assessment of these three reports in order to facilitate the design of policies favourable to the development of a ‘good AI society’. To do so, we examine how each report addresses the following three topics: the development of (...) a ‘good AI society’; the role and responsibility of the government, the private sector, and the research community in pursuing such a development; and where the recommendations to support such a development may be in need of improvement. Our analysis concludes that the reports address adequately various ethical, social, and economic topics, but come short of providing an overarching political vision and long-term strategy for the development of a ‘good AI society’. In order to contribute to fill this gap, in the conclusion we suggest a two-pronged approach. (shrink)

Technology firms are now purchasing access to research papers from academic publishers to train their artificial intelligence (AI) models. Using scientific content to train AI can come with multiple benefits, which help improve AI's capability to generate trustworthy outcomes, understand and process issues across a wide range of topics, as well as analyze information, make logical deductions, and draw conclusions. Journal articles are generally considered reliable because of the rigorous peer review system. However, the evaluation process is constrained (...) by several limitations, so a number of unreliable and invalid studies have been published. Retraction is often viewed as a crucial self-correction mechanism within science, allowing the academic community to identify and flag seriously flawed research that has been published. If retracted articles are used to train AI, it could lead to the spread of misinformation. Given the power of AI, this misinformation could be disseminated on a large scale and in a very short time, which might misinform and significantly increase the entropy (uncertainty) within society. Retracted notices can serve as a signal for AI developers to exclude seriously flawed articles from the training process. However, if the scientific content used to train AI is later discovered to be seriously distorted and retracted, it cannot be removed from the model’s knowledge base after the training is complete. As AI is increasingly applied in critical areas such as education and decision-making, training AI on seriously flawed scientific findings could lead to significant systematic consequences. Therefore, collaboration between the scientific community and AI developers to address these issues is crucial. (shrink)

Abstract: This research paper explores the transformative impact of artificial intelligence (AI) on digital media, examining both the opportunities it presents and the challenges it poses. The integration of AI into digital media has revolutionized content creation, distribution, and analytics, offering unprecedented levels of personalization, efficiency, and insight. Automated journalism, AI- driven recommendation systems, and advanced audience analytics are among the key areas where AI is making significant contributions. However, the adoption of AI also brings ethical considerations, including (...) concerns about bias, privacy, and transparency. This paper analyzes case studies of successful and unsuccessful AI implementations in digital media, highlighting lessons learned and best practices. Finally, it looks ahead to future trends and developments, providing a comprehensive overview of the current state and potential future of AI in digital media. Through this exploration, the paper aims to provide valuable insights for academics, industry professionals, and policymakers on harnessing the power of AI while addressing its challenges. (shrink)

This paper critically assesses the possibility of moral enhancement with ambient intelligence technologies and artificial intelligence presented in Savulescu and Maslen (2015). The main problem with their proposal is that it is not robust enough to play a normative role in users’ behavior. A more promising approach, and the one presented in the paper, relies on an artifi-cial moral reasoning engine, which is designed to present its users with moral arguments grounded in first-order normative theories, such as (...) Kantianism or utilitarianism, that reason-responsive people can be persuaded by. This proposal can play a normative role and it is also a more promising avenue towards moral enhancement. It is more promising because such a system can be designed to take advantage of the sometimes undue trust that people put in automated technologies. We could therefore expect a well-designed moral reasoner system to be able to persuade people that may not be persuaded by similar arguments from other people. So, all things considered, there is hope in artificial intelli-gence for moral enhancement, but not in artificial intelligence that relies solely on ambient intelligence technologies. (shrink)

In July 2017, China’s State Council released the country’s strategy for developing artificial intelligence, entitled ‘New Generation Artificial Intelligence Development Plan’. This strategy outlined China’s aims to become the world leader in AI by 2030, to monetise AI into a trillion-yuan industry, and to emerge as the driving force in defining ethical norms and standards for AI. Several reports have analysed specific aspects of China’s AI policies or have assessed the country’s technical capabilities. Instead, in this (...) article, we focus on the socio-political background and policy debates that are shaping China’s AI strategy. In particular, we analyse the main strategic areas in which China is investing in AI and the concurrent ethical debates that are delimiting its use. By focusing on the policy backdrop, we seek to provide a more comprehensive and critical understanding of China’s AI policy by bringing together debates and analyses of a wide array of policy documents. (shrink)

This paper argues that the Value Sensitive Design (VSD) methodology provides a principled approach to embedding common values in to AI systems both early and throughout the design process. To do so, it draws on an important case study: the evidence and final report of the UK Select Committee on Artificial Intelligence. This empirical investigation shows that the different and often disparate stakeholder groups that are implicated in AI design and use share some common values that can be (...) used to further strengthen design coordination efforts. VSD is shown to be both able to distill these common values as well as provide a framework for stakeholder coordination. (shrink)

Δ.Δακρότσης, «Τεχνητή νοημοσύνη και εκφραστικότητα: η αναγκαιότητα περάσματος της εννοιολογικής γνώσης από το μονοπάτι της αισθητικής εποπτείας» (Artificial Intelligence and expressiveness: The necessity for conceptual knowledge to go through the path of aesthetic perception), Days of Art in Greece, Τεύχος 18, Φθινόπωρο 2024, σς 26-39.

This paper explores the theological and philosophical implications of artificial intelligence (AI) and Neuroscience research on the Christian’s notion of the human person. The paschal mystery of Christ is the intuitive foundation of Christian anthropology. In the intellectual history of the Christianity, Platonism and Aristotelianism have been employed to articulate the Christian philosophical anthropology. The Aristotelian systematization has endured to this era. Since the modern period of the Western intellectual history, Aristotelianism has been supplanted by the positive sciences (...) as the standard scientific and philosophical interpretative framework for many. This paper argues that there is need for a new Christian anthropology based on the interpretation of the paschal mystery of Christ that is consistent with contemporary science and philosophy, especially as informed by research in AI and neuroscience. Christian anthropology today ought to be fully aware of the theological and philosophical implications of AI and neuroscience research. This paper denotes this new Christian anthropology as neuro-theological Christian anthropology. (shrink)

Abstract: Artificial Intelligence (AI) has rapidly evolved, offering transformative capabilities for business decision-making. This paper explores how AI can be leveraged to enhance strategic decision-making in business contexts. It examines the integration of AI-driven analytics, predictive modeling, and automation to improve decision accuracy and operational efficiency. By analyzing current applications and case studies, the paper highlights the opportunities AI presents, including enhanced data insights, risk management, and personalized customer experiences. Additionally, it addresses the challenges businesses face in adopting (...) AI, such as data privacy concerns, integration issues, and the need for skilled personnel. The paper concludes with recommendations for effectively implementing AI solutions to maximize their benefits while navigating potential pitfalls. (shrink)

Abstract: Artificial Intelligence (AI) is revolutionizing the agricultural sector by enhancing productivity and sustainability. This paper explores the transformative impact of AI technologies on agriculture, focusing on their applications in precision farming, predictive analytics, and automation. AI-driven tools enable more efficient management of crops and resources, leading to improved yields and reduced environmental impact. The paper examines key AI technologies, including machine learning algorithms for crop monitoring, robotics for automated planting and harvesting, and data analytics for optimizing resource (...) use. Additionally, it addresses challenges such as data privacy, technology adoption barriers, and the ethical implications of AI in farming. By integrating AI into agricultural practices, the industry can achieve greater efficiency and sustainability, paving the way for future advancements. (shrink)

Artificial intelligence (AI) is increasingly expected to disrupt the ordinary functioning of society. From how we fight wars or govern society, to how we work and play, and from how we create to how we teach and learn, there is almost no field of human activity which is believed to be entirely immune from the impact of this emerging technology. This poses a multifaceted problem when it comes to designing and understanding regulatory responses to AI. This article aims (...) to: (i) defend the need for a novel conceptual model for understanding the systemic legal disruption caused by new technologies such as AI; (ii) to situate this model in relation to preceding debates about the interaction of regulation with new technologies (particularly the ‘cyberlaw’ and ‘robolaw’ debates); and (iii) to set out a detailed model for understanding the legal disruption precipitated by AI, examining both pathways stemming from new affordances that can give rise to a regulatory ‘disruptive moment’, as well as the Legal Development, Displacement or Destruction that can ensue. The article proposes that this model of legal disruption can be broadly generalisable to understanding the legal effects and challenges of other emerging technologies. (shrink)

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

The concept of artificial intelligence is not new nor is the notion that it should be granted legal protections given its influence on human activity. What is new, on a relative scale, is the notion that artificial intelligence can possess citizenship—a concept reserved only for humans, as it presupposes the idea of possessing civil duties and protections. Where there are several decades’ worth of writing on the concept of the legal status of computational artificial artefacts (...) in the USA and elsewhere, it is surprising that law makers internationally have come to a standstill to protect our silicon brainchildren. In this essay, it will be assumed that future artificial entities, such as Sophia the Robot, will be granted citizenship on an international scale. With this assumption, an analysis of rights will be made with respect to the needs of a non-biological intelligence possessing legal and civic duties akin to those possessed by humanity today. This essay does not present a full set of rights for artificial intelligence—instead, it aims to provide international jurisprudence evidence aliunde ab extra de lege lata for any future measures made to protect non-biological intelligence. (shrink)

Artificial intelligence research and regulation seek to balance the benefits of innovation against any potential harms and disruption. However, one unintended consequence of the recent surge in AI research is the potential re-orientation of AI technologies to facilitate criminal acts, term in this article AI-Crime. AIC is theoretically feasible thanks to published experiments in automating fraud targeted at social media users, as well as demonstrations of AI-driven manipulation of simulated markets. However, because AIC is still a relatively young (...) and inherently interdisciplinary area—spanning socio-legal studies to formal science—there is little certainty of what an AIC future might look like. This article offers the first systematic, interdisciplinary literature analysis of the foreseeable threats of AIC, providing ethicists, policy-makers, and law enforcement organisations with a synthesis of the current problems, and a possible solution space. (shrink)

Recent progress in artificial intelligence (AI) has drawn attention to the technology’s transformative potential, including what some see as its prospects for causing large-scale harm. We review two influential arguments purporting to show how AI could pose catastrophic risks. The first argument — the Problem of Power-Seeking — claims that, under certain assumptions, advanced AI systems are likely to engage in dangerous power-seeking behavior in pursuit of their goals. We review reasons for thinking that AI systems might seek (...) power, that they might obtain it, that this could lead to catastrophe, and that we might build and deploy such systems anyway. The second argument claims that the development of human-level AI will unlock rapid further progress, culminating in AI systems far more capable than any human — this is the Singularity Hypothesis. Power-seeking behavior on the part of such systems might be particularly dangerous. We discuss a variety of objections to both arguments and conclude by assessing the state of the debate. (shrink)

Advanced AI systems are rapidly making their way into medical research and practice, and, arguably, it is only a matter of time before they will surpass human practitioners in terms of accuracy, reliability, and knowledge. If this is true, practitioners will have a prima facie epistemic and professional obligation to align their medical verdicts with those of advanced AI systems. However, in light of their complexity, these AI systems will often function as black boxes: the details of their contents, calculations, (...) and procedures cannot be meaningfully understood by human practitioners. When AI systems reach this level of complexity, we can also speak of black-box medicine. In this paper, we want to argue that black-box medicine conflicts with core ideals of patient-centered medicine. In particular, we claim, black-box medicine is not conducive for supporting informed decision-making based on shared information, shared deliberation, and shared mind between practitioner and patient. (shrink)

As systems based on opaque Artificial Intelligence (AI) continue to flourish in diverse real-world applications, understanding these black box models has become paramount. In response, Explainable AI (XAI) has emerged as a field of research with practical and ethical benefits across various domains. This paper not only highlights the advancements in XAI and its application in real-world scenarios but also addresses the ongoing challenges within XAI, emphasizing the need for broader perspectives and collaborative efforts. We bring together experts (...) from diverse fields to identify open problems, striving to synchronize research agendas and accelerate XAI in practical applications. By fostering collaborative discussion and interdisciplinary cooperation, we aim to propel XAI forward, contributing to its continued success. Our goal is to put forward a comprehensive proposal for advancing XAI. To achieve this goal, we present a manifesto of 27 open problems categorized into nine categories. These challenges encapsulate the complexities and nuances of XAI and offer a road map for future research. For each problem, we provide promising research directions in the hope of harnessing the collective intelligence of interested stakeholders. (shrink)

AI, especially in the case of Deepfakes, has the capacity to undermine our confidence in the original, genuine, authentic nature of what we see and hear. And yet digital technologies, in the form of databases and other detection tools also make it easier to spot forgeries and to establish the authenticity of a work. Using the notion of ectypes, this paper discusses current conceptions of authenticity and reproduction and examines how, in the future, these might be adapted for use in (...) the digital sphere. (shrink)

The discussion of artificial intelligence (AI) as a newly emerging phenomenon in the present era has always been faced with various ethical challenges. The expansion of artificial intelligence is inevitable, and since this phenomenon is related to the human and social world, anything related to humans and society falls within the realm of morality and rights. In doing so, it must be understood whether the use of artificial intelligence is an ethical matter or not. (...) Furthermore, do humans have the right to use it or not? It seems that Al-Farabi's thought in the realm of practical wisdom can provide an answer to this issue. By reflecting on the theories of this prominent philosopher in civil philosophy, the theory of natural rights is obtained, and on the other hand, Al-Farabi's ethical opinions are also consistent with the theory of natural rights and, in general, with Al-Farabi's civil philosophy. It can, therefore, be argued that, one can consider and elucidate this issue through the lens of Al-Farabi's ethical and civil school of thought. -/- . (shrink)

Accountability is a cornerstone of the governance of artificial intelligence (AI). However, it is often defined too imprecisely because its multifaceted nature and the sociotechnical structure of AI systems imply a variety of values, practices, and measures to which accountability in AI can refer. We address this lack of clarity by defining accountability in terms of answerability, identifying three conditions of possibility (authority recognition, interrogation, and limitation of power), and an architecture of seven features (context, range, agent, forum, (...) standards, process, and implications). We analyse this architecture through four accountability goals (compliance, report, oversight, and enforcement). We argue that these goals are often complementary and that policy-makers emphasise or prioritise some over others depending on the proactive or reactive use of accountability and the missions of AI governance. (shrink)

Abstract: As the integration of Artificial Intelligence (AI) continues to permeate various sectors, the legal domain stands on the cusp of a transformative era. This research paper delves into the multifaceted relationship between AI and the law, scrutinizing the profound implications and innovative applications that emerge at the intersection of these two realms. The study commences with an examination of the current landscape, assessing the challenges and opportunities that AI presents within legal frameworks. With an emphasis on efficiency, (...) accuracy, and accessibility, AI technologies are reshaping traditional legal processes, ranging from document analysis and contract review to predictive legal analytics. Furthermore, the paper scrutinizes the ethical considerations and potential biases inherent in AI algorithms, exploring the delicate balance between technological advancements and the preservation of legal principles such as fairness, accountability, and transparency. The research also delves into the evolving role of legal professionals in navigating and overseeing AI applications, emphasizing the importance of responsible AI deployment. Drawing on case studies and real-world examples, this paper showcases instances where AI has already demonstrated its efficacy in legal contexts, highlighting successful implementations and identifying areas for improvement. The discussion extends to the evolving regulatory landscape, as legal systems grapple with the need to adapt and establish frameworks that ensure the responsible and ethical use of AI technologies. In conclusion, this research contributes to the growing discourse on the dynamic interplay between AI and the legal domain. By illuminating the potential benefits, ethical considerations, and regulatory challenges, it provides a comprehensive overview for legal practitioners, policymakers, and technologists alike, fostering a nuanced understanding of the evolving landscape where artificial intelligence intersects with the law. (shrink)

There is considerable enthusiasm about the prospect that artificial intelligence (AI) will help to improve the safety and efficacy of health services and the efficiency of health systems. To realize this potential, however, AI systems will have to overcome structural problems in the culture and practice of medicine and the organization of health systems that impact the data from which AI models are built, the environments into which they will be deployed, and the practices and incentives that structure (...) their development. This perspective elaborates on some of these structural challenges and provides recommendations to address potential shortcomings. (shrink)

This is the lightly revised text of my commentary/response to David Carr’s keynote address, “Phenomenology of Crisis,” at the 2024 meeting of the Husserl Circle.

In two experiments (total N=693) we explored whether people are willing to consider paintings made by AI-driven robots as art, and robots as artists. Across the two experiments, we manipulated three factors: (i) agent type (AI-driven robot v. human agent), (ii) behavior type (intentional creation of a painting v. accidental creation), and (iii) object type (abstract v. representational painting). We found that people judge robot paintings and human painting as art to roughly the same extent. However, people are much less (...) willing to consider robots as artists than humans, which is partially explained by the fact that they are less disposed to attribute artistic intentions to robots. (shrink)

Artificial intelligence (AI) and robotics are digital technologies that will have significant impact on the development of humanity in the near future. They have raised fundamental questions about what we should do with these systems, what the systems themselves should do, what risks they involve, and how we can control these. - After the Introduction to the field (§1), the main themes (§2) of this article are: Ethical issues that arise with AI systems as objects, i.e., tools made (...) and used by humans. This includes issues of privacy (§2.1) and manipulation (§2.2), opacity (§2.3) and bias (§2.4), human-robot interaction (§2.5), employment (§2.6), and the effects of autonomy (§2.7). Then AI systems as subjects, i.e., ethics for the AI systems themselves in machine ethics (§2.8) and artificial moral agency (§2.9). Finally, the problem of a possible future AI superintelligence leading to a “singularity” (§2.10). We close with a remark on the vision of AI (§3). - For each section within these themes, we provide a general explanation of the ethical issues, outline existing positions and arguments, then analyse how these play out with current technologies and finally, what policy consequences may be drawn. (shrink)

In his book “Minds and Computers: An Introduction to the Philosophy of Artificial Intelligence”, Matt Carter presents a comprehensive exploration of the philosophical questions surrounding artificial intelligence (AI). Carter argues that the development of AI is not merely a technological challenge but fundamentally a philosophical one. He delves into key issues like the nature of mental states, the limits of introspection, the implications of memory decay, and the functionalist framework that allows for the possibility of AI. (...) Carter contrasts functionalism with reductive materialism, highlighting how the former accommodates the concept of artificial minds. He also emphasizes the significance of computationalism, which combines functionalism with computational theory to provide a robust explanation for mental processes. The book further discusses formal systems, the role of register machines in computation, and the inherent challenges in AI research, particularly in developing natural language processing systems. Carter’s work underscores the limitations of current computational models of cognition while remaining hopeful that advances in neuroscience may lead to stronger AI systems in the future. (shrink)

Abstract: The integration of Artificial Intelligence (AI) into leadership practices is transforming organizational dynamics and This decision-making processes. paper explores how AI can enhance leadership effectiveness by providing data-driven insights, optimizing decision-making, and automating routine tasks. It also examines the challenges leaders face in adopting AI, including ethical considerations, potential biases in AI systems, and the need for upskilling. By analyzing current applications of AI in leadership and discussing future trends, this study aims to provide a comprehensive overview (...) of the opportunities AI presents for effective leadership and the strategies required to address its associated challenges. (shrink)

The tendency to idealise artificial intelligence as independent from human manipulators, combined with the growing ontological entanglement of humans and digital machines, has created an “anthrobotic” horizon, in which data analytics, statistics and probabilities throw our agential power into question. How can we avoid the consequences of a reified definition of intelligence as universal operation becoming imposed upon our destinies? It is here argued that the fantasised autonomy of automated intelligence presents a contradistinctive opportunity for philosophical (...) consciousness to understand itself anew as holistic and co-creative, beyond the recent “analytic” moment of the history of philosophy. Here we introduce the concept of “crealectic intelligence”, a meta-analytic and meta-dialectic aspect of consciousness. Intelligent behaviour may consist in distinguishing discrete familiar parts or reproducible functions in the midst of noise via an analytic process of segmentation; intelligence may also manifest itself in the constitution of larger wholes and dynamic unities through a dialectic process of association or assemblage. But, by contrast, crealectic intelligence co-creates realities in the image of an ideal or truth, taking into account the desiring agent imbued with a sense of possibility, in a relationship not only with the Real but also with the creative sublime or “Creal”. (shrink)

The present paper aims at contributing to the ethical debate on the impacts of artificial intelligence (AI) systems on human autonomy. More specifically, it intends to offer a clearer understanding of the design challenges to the effort of aligning driving automation technologies to this ethical value. After introducing the discussion on the ambiguous impacts that AI systems exert on human autonomy, the analysis zooms in on how the problem has been discussed in the literature on connected and automated (...) vehicles (CAVs). On this basis, it is claimed that the issue has been mainly tackled on a fairly general level, and mostly with reference to the controversial issue of crash-optimization algorithms, so that only limited design insights have been drawn. However, integrating ethical analysis and design practices is critical to pursue the implementation of such an important ethical value into CAV technologies. To this aim, it is argued, a more applied approach targeted at examining the impacts on human autonomy of current CAV functions should also be explored. As an example of the intricacy of this task, the case of automated route planning is discussed in some detail. (shrink)

It is the contention of this paper that ethics of work ought to be anthropological, and artificial intelligence (AI) research and development, which is the focus of work today, should be anthropological, that is, human-centered. This paper discusses the philosophical and theological implications of the development of AI research on the intrinsic nature of work and the nature of the human person. AI research and the implications of its development and advancement, being a relatively new phenomenon, have not (...) been comprehensively interrogated in the social and ethical teachings of the Catholic Church. This paper, therefore, proposes a path for this interrogation by expounding a discourse which is believed to be epistemically helpful in the developing discourse of AI in the ethical and social teachings of the Church. The advancement in the research on AI is not only redefining the meaning of work, but, even more so, it is questioning the metaphysical notion of the human person and the theological notion of work as an intrinsic part in the selfhood and dignity of the human person. (shrink)

This paper argues that to negate the ontological difference between the natural and the artificial, is not plausible; nor is the reduction of the natural to the artificial or vice versa possible. Except if one intends to empty the semantic content of the terms and notions: “natural” and “artificial.” Most philosophical discussions on Artificial Intelligence (AI) have always been in relation to the human person, especially as it relates to human intelligence, consciousness and/or mind (...) in general. This paper, intends to broaden the conversation, by discussing AI in relation to the notions of “nature” and the “artificial.” This intention is to more critically understand the artificiality in and of artificial intelligence. To achieve this, the notion of “nature” in Aristotle’s Philosophy of Nature, has been employed as an epistemological tool in interrogating the notion of the artificial and the objectives of the science and technology of Artificial Intelligence. (shrink)

In this paper, I provide an overview of today’s philosophical approaches to the problem of “intelligence” in the field of artificial intelligence by examining several important papers on phenomenology and the philosophy of biology such as those on Heideggerian AI, Jonas's metabolism model, and slime mold type intelligence.

The text "Artificial Intelligence and Analytic Pragmatism" was translated from the book by Robert B. Brand: Between Saying and Doing: Towards an Analytical Pragmatism. Chapter 3. Oxford University Press. pp. 69 - 92.

Cheating is a growing academic and ethical concern in higher education. This article examines the rise of artificial intelligence (AI) generative chatbots for use in education and provides a review of research literature and relevant scholarship concerning the cheating-related issues involved and their implications for pedagogy. The technological “arms race” that involves cheating-detection system developers versus technology savvy students is attracting increased attention to cheating. AI has added new dimensions to academic cheating challenges as students (as well as (...) faculty and staff) can easily access powerful systems for generating content that can be presented in assignments, exams, or published papers as their own. AI methodology is also providing some emerging anti-cheating approaches, including facial recognition and water- marking. This article provides an overview of human/AI collaboration approaches and frames some educational misuses of such AI generative systems as ChatGPT and Bard as forms of “misattributed co-authorship.” As with other kinds of collaborations, the work that students produce with AI assistance can be presented in transparent and straightforward modes or (unfortunately) in opaquer and ethically-problematic ways. However, rather than just for catching or entrapping students, the emerging varieties of technological cheating-detection strategies can be used to assist students in learning how to document and attribute properly their AI-empowered as well as human-human collaborations. Construing misuses of AI generative systems as misattributed co-authorship can recognize the growing capabilities of these tools and how stressing responsible and mindful usage by students can help prepare them for a highly collaborative, AI-saturated future. (shrink)

The aim of this exploratory paper is to review an under-appreciated parallel between group agency and artificial intelligence. As both phenomena involve non-human goal-directed agents that can make a difference to the social world, they raise some similar moral and regulatory challenges, which require us to rethink some of our anthropocentric moral assumptions. Are humans always responsible for those entities’ actions, or could the entities bear responsibility themselves? Could the entities engage in normative reasoning? Could they even have (...) rights and a moral status? I will tentatively defend the (increasingly widely held) view that, under certain conditions, artificial intelligent systems, like corporate entities, might qualify as responsible moral agents and as holders of limited rights and legal personhood. I will further suggest that regulators should permit the use of autonomous artificial systems in high-stakes settings only if they are engineered to function as moral (not just intentional) agents and/or there is some liability-transfer arrangement in place. I will finally raise the possibility that if artificial systems ever became phenomenally conscious, there might be a case for extending a stronger moral status to them, but argue that, as of now, this remains very hypothetical. (shrink)

The future rests under the sign of technology. Given the prevalence of technological neutrality and inevitabilism, most conceptualizations of the future tend to ignore moral problems. In this paper we argue that every choice about future technologies is a moral choice and even the most technology-dominated scenarios of the future are, in fact, moral provocations we have to imagine solutions to. We begin by explaining the intricate connection between morality and the future. After a short excursion into the history of (...) Artificial Intelligence, we analyse two possible scenarios, which show that building the future with technology is, first and foremost, a moral endeavor. (shrink)

There are calls from various sectors, including the popular press, industry, and academia, to incorporate artificial intelligence (AI)-based technologies in general, and large language models (LLMs) (such as ChatGPT and Gemini) in particular, into various spheres of the South African higher education sector. Nonetheless, the implementation of such technologies is not without ethical risks, notably those related to bias, unfairness, privacy violations, misinformation, lack of transparency, and threats to autonomy. This paper gives an overview of the more pertinent (...) ethical concerns that may result from the deployment of various current AI technologies in the South African higher education context. It provides a broad overview of the relevant AI ethics literature and distills a few general AI-ethics principles that can serve as guidelines for the ethical development, adoption, and use of AI systems. Suggestions are made as to how these might be applied to mitigate the ethical concerns in the South African higher education context. Overall, it is argued that AI technologies should only be adopted if they offer demonstrable benefits to stakeholders affected by them and that care should be taken to ensure that any potential harms are adequately addressed. (shrink)

Artificial intelligence (AI) is a digital technology that will be of major importance for the development of humanity in the near future. AI has raised fundamental questions about what we should do with such systems, what the systems themselves should do, what risks they involve and how we can control these. - After the background to the field (1), this article introduces the main debates (2), first on ethical issues that arise with AI systems as objects, i.e. tools (...) made and used by humans; here, the main sections are privacy (2.1), manipulation (2.2), opacity (2.3), bias (2.4), autonomy & responsibility (2.6) and the singularity (2.7). Then we look at AI systems as subjects, i.e. when ethics is for the AI systems themselves in machine ethics (2.8.) and artificial moral agency (2.9). Finally we look at future developments and the concept of AI (3). For each section within these themes, we provide a general explanation of the ethical issues, we outline existing positions and arguments, then we analyse how this plays out with current technologies and finally what policy conse-quences may be drawn. (shrink)

Suicide is a complex act whose meanings, while sometimes tragic, vary widely. This chapter surveys the ethical landscape surrounding algorithmic methods of suicide prevention especially as it pertains to social media activity and to the moderation of online suicide communities. We begin with a typology of suicide, distinguishing between varied goals in which suicide may factor as a means. Suicides should be understood as an act with varied eliciting desires, meanings, consequences, and ethics. Further,while many suicides may be grounded on (...) irrational desire, we argue that a desire to suicide may nonetheless be rational in some cases. We then offer a survey of the attempts by social media corporations to create suicide prediction algorithms and launch interventions aimed at preventing suicide as well as an overview of the current ethical debate. We argue that the values embedded within algorithmic suicide prevention nudges are “thick” in a substantive sense and deserving of scrutiny. Given that debates about the rationality, meaning, and permissibility of suicide are common and subject to intracultural and cross-cultural differences, we maintain that the task of suicide prediction is ill-suited to algorithmic approaches. Despite an algorithm’s ability to quantify a complex phenomenon like suicide risk and its appearance of objectivity, any suicide prediction algorithm is thoroughly subjective and involves moral judgments all the way down. Any such algorithm would necessarily impose a normative stance on suicide onto its user base that is subject to reasonable intra and cross-cultural disagreement. (shrink)

There is, in some quarters, concern about high–level machine intelligence and superintelligent AI coming up in a few decades, bringing with it significant risks for humanity. In other quarters, these issues are ignored or considered science fiction. We wanted to clarify what the distribution of opinions actually is, what probability the best experts currently assign to high–level machine intelligence coming up within a particular time–frame, which risks they see with that development, and how fast they see these developing. (...) We thus designed a brief questionnaire and distributed it to four groups of experts in 2012/2013. The median estimate of respondents was for a one in two chance that high-level machine intelligence will be developed around 2040-2050, rising to a nine in ten chance by 2075. Experts expect that systems will move on to superintelligence in less than 30 years thereafter. They estimate the chance is about one in three that this development turns out to be ‘bad’ or ‘extremely bad’ for humanity. (shrink)

This paper argues that there is an urgent need for an international doctrine for cyberspace skirmishes before they escalate into conventional warfare.

Artificial Intelligence (AI) is a technology that makes machines smart and capable of doing things that usually require human intelligence. AI works by training machines to learn from data and experiences. Such devices can recognize patterns, understand spoken language, see and understand images, and even make predictions based on their learning. Voice assistants like Siri or Alexa can understand our voice commands, answer questions, and perform tasks for us. AI-based self-driving cars can sense their surroundings, make decisions, (...) and drive safely without a human driver. AI also helps doctors diagnose diseases, detect fraud in financial transactions, and recommend movies or songs based on one’s preferences. Furthermore, AI has started to make its presence felt in Punjabi culture through various avenues. (shrink)

This paper investigates the claim that artificial Intelligence Systems cannot be held morally responsible because they do not have an ability for agential self-awareness e.g. they cannot be aware that they are the agents of an action. The main suggestion is that if agential self-awareness and related first person representations presuppose an awareness of a self, the possibility of responsible artificial intelligence systems cannot be evaluated independently of research conducted on the nature of the self. Focusing (...) on a specific account of the self from the phenomenological tradition, this paper suggests that a minimal necessary condition that artificial intelligence systems must satisfy so that they have a capability for self-awareness, is having a minimal self defined as ‘a sense of ownership’. As this sense of ownership is usually associated with having a living body, one suggestion is that artificial intelligence systems must have similar living bodies so they can have a sense of self. Discussing cases of robotic animals as examples of the possibility of artificial intelligence systems having a sense of self, the paper concludes that the possibility of artificial intelligence systems having a ‘sense of ownership’ or a sense of self may be a necessary condition for having responsibility. (shrink)

Artificial intelligence has arrived. In the online world it is already a part of everyday life, sitting invisibly behind a wide range of search engines and online commerce sites. It offers huge potential to enable more efficient and effective business and government but the use of artificial intelligence brings with it important questions about governance, accountability and ethics. Realising the full potential of artificial intelligence and avoiding possible adverse consequences requires societies to find satisfactory (...) answers to these questions. This report sets out some possible approaches, and describes some of the ways government is already engaging with these issues. (shrink)

Artificial Intelligence (AI) is a technology that makes machines smart and capable of doing things that usually require human intelligence. It is a rapidly evolving field with ongoing research and development to advance its capabilities and address its limitations. AI has permeated various aspects of our daily lives, and its applications can be found in numerous products and services. The integration of AI continues to expand across multiple sectors, providing convenience, personalization, and efficiency in our daily lives. (...) While Punjabi culture is rich and diverse, characterized by several distinctive traits that define its identity, AI has started to make its presence felt in Punjabi culture through various avenues. Though AI is gradually enriching Punjabi culture, it is still in its early stages, and there is room for further exploration and integration. However, it is essential to ensure that AI's influence aligns with the values and aspirations of Punjabi culture while preserving its authenticity and uniqueness. (shrink)

Artificial intelligence systems have been widely applied to various contexts, including high-stake decision processes in healthcare, banking, and judicial systems. Some developed AI models fail to offer a fair output for specific minority groups, sparking comprehensive discussions about AI fairness. We argue that the development of AI systems is marked by a central paradox: the less participation one stakeholder has within the AI system’s life cycle, the more influence they have over the way the system will function. This (...) means that the impact on the fairness of the system is in the hands of those who are less impacted by it. However, most of the existing works ignore how different aspects of AI fairness are dynamically and adaptively affected by different stages of AI system development. To this end, we present a use case to discuss fairness in the development of corporate wellness programs using smart wearables and AI algorithms to analyze data. The four key stakeholders throughout this type of AI system development process are presented. These stakeholders are called service designer, algorithm designer, system deployer, and end-user. We identify three core aspects of AI fairness, namely, contextual fairness, model fairness, and device fairness. We propose a relative contribution of the four stakeholders to the three aspects of fairness. Furthermore, we propose the boundaries and interactions between the four roles, from which we make our conclusion about the possible unfairness in such an AI developing process. (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 partial data collection, rare updates, and significant resource demands. To address these issues, the article suggests that specific data management and Machine Learning techniques, such as natural language processing and sentiment analysis, can (...) improve the measurement and practice of IPD. (shrink)

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

Abstract: Artificial Intelligence (AI) is rapidly becoming a cornerstone of modern healthcare, offering unprecedented capabilities in diagnostics, treatment planning, patient care, and healthcare management. This paper explores the transformative impact of AI on the healthcare sector, examining how it enhances patient outcomes, improves the efficiency of medical practices, and introduces new ethical and operational challenges. By analyzing current applications such as AI-driven diagnostic tools, personalized medicine, and hospital management systems, this paper highlights the significant advancements AI has brought (...) to the field. However, the integration of AI also raises concerns related to data privacy, algorithmic bias, and the displacement of healthcare professionals. This study provides a comprehensive overview of these developments, offering insights into the future potential of AI in revolutionizing healthcare while addressing the ethical considerations that must accompany its adoption. The findings suggest that while AI holds the promise of transforming healthcare delivery, careful consideration of its implications is essential to ensure equitable and effective implementation. (shrink)