This article analyzes the digitalization process in the Republic of Uzbekistan, a Central Asian country that currently holds a low position in the Government AI Readiness Index. The aim of the article is to provide an initial overview of the ethical norms required for public servants in the context of AI usage. To develop such a code, an exploratory foundation must first be established. The necessity for an AI Code of Ethics is also explicitly mentioned in the national strategy “Digital (...) Uzbekistan – 2030”. The research uses both theoretical and comparative legal analysis. The survey was also conducted which measures the digital and ethical literacy and readiness to adopt AI technologies. According to the author, the factors hindering the implementation of AI into the professional activities of civil servants are, firstly, the insufficient level of AI skills among Uzbek civil servants, and secondly, there is an urgent need to develop a national system for the ethical regulation of issues related to AI in general, which are currently being developed. Voluntary adherence to international ethical codes for AI and the development of its own model for AI ethical regulation can reduce the level of cyber fraud in the country. (shrink)

Public sector institutions are increasingly investing resources in data collection and data analytics to provide better public services at lower cost, to anticipate demand for services, to identify high-risk groups, and to develop targeted interventions. Prior research has shown that the media shape understanding of the possibilities of technology and creates related expectations. In this article we explore how artificial intelligence and emerging data-driven technologies are made familiar and by whose voices they are talked about in the media. Empirically, (...) we explore communication materials and media coverage from the joint AI experiment between the City of Espoo and Tieto Corporation in 2017–18. In this experiment, Tieto Corporation combined customer data from the City of Espoo’s social and health care and early childhood education from 2002–2016 and analysed this data using artificial intelligence methods. Theoretically, we draw on the tradition of the social construction of technology and especially its branch that focuses on the domestication of technologies. The results show that the means of narration used by the media – repetition and highlighting the voice of the representatives of the institutional actors involved in the AI experiment – strengthen the agency and interests of the parties involved as well as their visibility in the media, while reducing the space for possible critical discussion. We argue that this way, AI is made familiar and acceptable to citizens and in public services in Finland. (shrink)

Abstract:AI technologies mine past data to anticipate future events, and yet our world of environmental and political crisis ushers in unprecedented conditions. Mixing examples of operational environments (AI in the oil and gas industry) with insights from media, cultural, and environmental studies, this article explores this grappling with uncertainty. To manage uncertainty, companies strive to internalize the complexity and contingency of the real world, collecting more data, designing more accurate sensors, and developing more exhaustive models. And yet prediction is a (...) fraught exercise that struggles with correlation versus causation, the epistemological outside (the unknown), and the ontological outside (the open-endedness of the future). In addition, technology’s role in accelerating and intensifying the destructive logics of capital contributes to more volatile planetary conditions, undermining the stability and continuity that prediction requires. The article thus argues that, at a fundamental level, a highly fluid future will increasingly frustrate any meaningful degree of prediction. Keywords: prediction, knowledge, AI, machine learning, uncertainty, climate change. (shrink)

Increasingly, technology, the Internet and social media are playing a major part in our lives. What should we think about the ethical issues that arise, such as the changing role of intelligent machines in this Information Age? The impact of technology upon society is a perennial question, but the power of computing and artificial intelligence has ratcheted up the ethical implications of this relationship. It merits careful consideration. _Ethics in the AI, Technology, and Information Age_ brings together (...) a cohort of international scholars to explore the ethical ramifications of the latest technologies and their effects on our lives. This it does in three parts: (1) theoretical considerations, (2) practical applications, and (3) challenges. Beginning with theoretical essays, the book investigates the relationship between technology and nature, the limits of being “human” versus “machine,” and the moral implications of artificial intelligence. The book then examines key questions; such as ownership of technology, artificial intelligence’s replacement of human jobs and functions, privacy and cybersecurity, the ethics of self-driving cars, and the problematic aspects of drone warfare. With an appendix of films and documentaries to inspire further discussion on these topics, students and scholars will find _Ethics in the AI, Technology, and Information Age _an essential and engaging resource both in the classroom and in their daily technology-filled lives. (shrink)

This article examines how emerging technologies – particularly artificial intelligence – disrupt the moral and institutional foundations of contemporary military practice. While strategic documents from the United States, NATO, and other major actors anticipate profound institutional transformation driven by AI, their treatment of ethics largely confines itself to legal compliance and technical safeguards, leaving the ethical role of military leadership in managing disruptive change underexamined. Drawing on Seumas Miller’s distinction between social institutions that are merely instrumental to collective goods and (...) those whose defining ends are constitutive of such goods, the article argues that the military belongs to the latter category. Because the military’s core function – defending the sovereignty of a polity – is itself morally significant, technological disruption of its organizational structures simultaneously constitutes ethical disruption. The article thus reconceives change management during periods of technological transition as calling for a specific kind of military prudence, a practical wisdom exercised within and through the institution’s role-mediated ethical practices. By analyzing three concrete modes of techno-moral disruption, the article shows how AI may reshape ethical standards, redistribute professional knowledge, and alter organizational ethos, and why navigating these transformations responsibly is a central task of military virtue. (shrink)

Norms and values are not stable things. They change over time and in response to, among other things, the introduction of new technologies. This is particularly clear in the developing field of AI Governance, where the introduction of new technologies instigates and triggers renegotiations about the values and norms that these new technologies put under pressure. One element of Deborah Johnson’s more recent work is the focus on negotiations around values and norms as part of changing practices following the introduction (...) of computational technologies, like AI. This work aligns with the practice turn in philosophy and the social sciences, where scholars have argued that a focus on practices provides a promising perspective to think about human activity and social life. The focus on practices offers opportunities for empirical philosophical research on how interventions can be made in these negotiations and practices ‘in the making’. This paper explores the potential role empirical philosophers and computer ethicists can play in shaping the embedding and governance of AI technologies in practice. It examines this role in the context of AI governance clinics organized for municipalities to help smart city projects address ethical and social issues that go beyond the formal legal and policy questions. (shrink)

This paper discusses two opposing views about the relation between artificial intelligence (AI) and human intelligence: on the one hand, a worry that heavy reliance on AI technologies might make people less intelligent and, on the other, a hope that AI technologies might serve as a form of cognitive enhancement. The worry relates to the notion that if we hand over too many intelligence-requiring tasks to AI technologies, we might end up with fewer opportunities to train our own intelligence. Concerning (...) AI as a potential form of cognitive enhancement, the paper explores two possibilities: (1) AI as extending—and thereby enhancing—people’s minds, and (2) AI as enabling people to behave in artificially intelligent ways. That is, using AI technologies might enable people to behave as if they have been cognitively enhanced. The paper considers such enhancements both on the level of individuals and on the level of groups. (shrink)

As the Internet becomes more and more a worldwide phenomenon, prepaid card system, internet payment services, and mobile payment services are potentially subject to a wide range of vulnerabilities that can be exploited for money laundering. Numerous third-party payment service providers offer individuals the ability to make online purchases, funding accounts with wire transfers, money orders, and even cash. In most cases, the provider of this service will not have a face-to-face relationship with its customers and may even allow anonymous (...) accounts. As the development of new technologies of information and communication has created opportunities for criminals to misuse such technologies for the purposes of money laundering. On the other hand, new technology can also be applied to increasing anti-money laundering efficiency and quality. This chapter aims to demonstrate money laundering risks associated with new technology-based financial activities, to introduce enterprise-wide AML information solution, to explain basic principles of risk-based approach, and to demonstrate Chinese practice regarding on money laundering vulnerabilities related to new-tech payment system. (shrink)

Across the world, artificial intelligence (AI) technologies are being more widely employed in public sector decision-making and processes as a supposedly neutral and an efficient method for optimizing delivery of services. However, the deployment of these technologies has also prompted investigation into the potentially unanticipated consequences of their introduction, to both positive and negative ends. This paper chooses to focus specifically on the relationship between gender bias and AI, exploring claims of the neutrality of such technologies and how its understanding (...) of bias could influence policy and outcomes. Building on a rich seam of literature from both technological and sociological fields, this article constructs an original framework through which to analyse both the perpetuation and mitigation of gender biases, choosing to categorize AI technologies based on whether their input is text or images. Through the close analysis and pairing of four case studies, the paper thus unites two often disparate approaches to the investigation of bias in technology, revealing the large and varied potential for AI to echo and even amplify existing human bias, while acknowledging the important role AI itself can play in reducing or reversing these effects. The conclusion calls for further collaboration between scholars from the worlds of technology, gender studies and public policy in fully exploring algorithmic accountability as well as in accurately and transparently exploring the potential consequences of the introduction of AI technologies. (shrink)

Artificial intelligence (AI) companies and their rhetoric infringe on academia in harmful ways, mirroring past uncritical acceptance of industry logics, such as those of tobacco and petroleum. In this position piece, we tease apart and explain why phrases like 'generative AI' impede scholarly discussion because by design these expressions are used to dazzle and sidestep scrutiny. Furthermore, we contend with the AI industry's logics to enable rejecting frames such as: that we must embrace the future, that this hype cycle is (...) unique, that anthropomorphism and circular reasoning hold water when discussing AI systems, and that students are now all cheating or all need to use AI. To these ends, we expound on why universities must take their role seriously to a) counter the AI industry's marketing, hype, and harm; and to b) safeguard higher education, critical thinking, expertise, academic freedom, and scientific integrity. For each point we raise, we include pointers to relevant work to further inform and convince our colleagues. (shrink)

People often complain that AI is not developing as well as expected. They say, "Progress was quick in the early years of AI, but now it is not growing so fast." I find this funny, because people have been saying the same thing as long as I can remember. In fact we are still rapidly developing new useful systems for recognizing patterns and for supervising processes. Furthermore, modern hardware is so fast and reliable that we can employ almost any programs (...) we can create. Good new systems appear every year, for different "expert" applications. (shrink)

Responsible artificial intelligence (AI) requires integrating ethical awareness into the full process of designing and developing AI, including ethics-based auditing of AI technology. We claim the Capability Approach (CA) of Sen and Nussbaum grounds AI ethics in essential human freedoms and can increase awareness of the moral dimension in the technical decision making of developers and data scientists constructing data-centric AI systems. Our use of CA focuses awareness on the ethical impact that day-to-day technical decisions have on the freedom (...) of data subjects to make choices and live meaningful lives according to their own values. For internal auditing of AI technology development, we design and develop a light-weight ethical auditing tool (LEAT) that uses simple natural language processing (NLP) techniques to search design and development documents for relevant ethical characterizations. We describe how CA guides our design, demonstrate LEAT on both principle- and capabilities-based use cases, and characterize its limitations. (shrink)

Policymakers and researchers consistently call for greater human accountability for AI technologies. We should be clear about two distinct features of accountability.

Sam Altman has claimed that by the end of this year, OpenAI will be capable of "truly astonishing cognitive tasks." But what exactly does "cognition" mean in the context of artificial intelligence? As the sophistication of such technologies, our dependence on them, and the rhetoric used to sell them escalates, it's vital we grapple with this question. Earlier this year, Luciano Floridi, founding director of the Digital Ethics Center at Yale University, joined Alexandros Schismenos, post-doctoral researcher on the philosophy of (...) artificial intelligence at the Aristotle University of Thessaloniki, and Giannis Perperidis, adjunct lecturer on the philosophy of AI at the Ionian University in Corfu, for an online conversation about the present and future of AI technology-and why solving a puzzle is still not the same as understanding it. (shrink)

People often complain that AI is not developing as well as expected. They say, "Progress was quick in the early years of AI, but now it is not growing so fast." I find this funny, because people have been saying the same thing as long as I can remember. In fact we are still rapidly developing new useful systems for recognizing patterns and for supervising processes. Furthermore, modern hardware is so fast and reliable that we can employ almost any programs (...) we can create. Good new systems appear every year, for different "expert" applications. (shrink)

This study examines the influence of perceived intelligence, knowledge acquisition, and emotional responses on the utilization and word-of-mouth (WOM) promotion of AI technologies like ChatGPT, utilizing a sample size of 296 university students. Utilizing PLS-SEM, the analysis confirms that both perceived intelligence and knowledge acquisition significantly enhance perceived utilitarian benefits, supporting the extended Technology Acceptance Model. Notably, the presence of guilt feelings was found to diminish both utilitarian and hedonic benefits, indicating that emotional responses can significantly alter technology (...) engagement outcomes. Specifically, guilt feelings were associated with reduced utilization and WOM, except where the direct influence on usage was not supported. Additionally, the novelty and customization of the technology significantly increased hedonic benefits, which in turn positively influenced both usage and WOM recommendations. Multi-group analysis further differentiated the effects between male and female users, revealing gender differences in how these factors impact technology acceptance and use. (shrink)

This book explores politics as a form of alchemy, understood as the transformation of entities through an alteration of their identities. Identifying this process as a common denominator of many political phenomena, such as communism, EU integration, mediatisation or globalisation, the author demonstrates not only the widespread presence of alchemical techniques in politics, but also the acceleration of their deployment. A study of the steady growth of power as it reaches a continuous and permanent stage, thus avoiding the inherent difficulties (...) connected with birth and death of political organisations and institutions, this volume reveals political alchemy to be a form of self-sustaining growth through sterile multiplication, devoid of meaning. Revealing both the integrative and disintegrative nature of a political process that, while appearing to work in the interests of all, in fact produces apathy, desperate mobilisation and despair by crushing concrete entities such as personality and tradition, Political Alchemy: Technology Unbounded will appeal to scholars of sociology and anthropology with interests in social theory and political thought. (shrink)

Ultrasonic excitation has been widely used in the detection of microcracks on metal surfaces, but there are problems such as poor excitation effect of ultrasonic pulse, long time to reach the best excitation, and difficult to find microcracks. In this paper, an adaptive ultrasonic pulse excitation device and infrared thermal imaging technology have been combined, as well as their control method, to solve the problem. The adaptive ultrasonic pulse excitation device adds intelligent modules to realize automatic adjustment of detection (...) parameters, which can quickly obtain reliable excitation; the multidegree-of-freedom base realizes the three-dimensional direction change of the ultrasonic gun to adapt to different excitation occasions. When the appropriate ultrasonic excitation makes microcracks in the resonance state, the microcracks can be frictionated, which produce heat rise with the temperature. Then, the microcrack defect can be detected by the infrared thermal instrument through the different surface temperatures with imaging recognition method. Our detection experiments of the titanium alloy plates and the aluminum alloy profiles of marine engineering show that the method can get reliable detection parameters in a short time and measure the crack length effectively. It can be used in many aspects such as crack detection in mechanical structures or complex equipment operating conditions and industrial production processes. (shrink)

Promoters of Artificial Intelligence (AI) innovations, such as OpenAI, DeepMind, and AlphaGo, often present ambitious promises of singular solutions capable of overcoming human knowledge limitations (Gehani, 2002). However, critics caution against over-reliance on unproven technologies, citing failures and shortcomings of Conventional AI systems, such as hallucinations and inaccuracies (Gehani, 2001). These limitations have motivated efforts to innovate advanced AI systems with human-like consciousness. This exploratory research investigates the early introductory stages of both Conventional AI and the nascent attempts to develop (...) Conscious AI within their technology life cycles (Gehani, 1995, 1998). The study critically examines AI innovations through the lens of four models: (1) the limitations of the Turing Thinking Machine model, (2) Gehani’s systems thinking and V8 piston engine value-adding model (1993, 1998), (3) the Open Innovation model (1992), and (4) Searle’s Chinese Room thought experiment. Drawing lessons from these frameworks, the research highlights key characteristics of human consciousness and proposes foundational building block capabilities for advancing Conscious AI technology (Gehani, 2013, 2016). The study concludes with future implications and critical lessons, emphasizing the importance of ethical, human-centric innovation during this pivotal period in AI development. (shrink)

Generative artificial intelligence (AI) has the potential to transform many aspects of scholarly publishing. Authors, peer reviewers, and editors might use AI in a variety of ways, and those uses might augment their existing work or might instead be intended to replace it. We are editors of bioethics and humanities journals who have been contemplating the implications of this ongoing transformation. We believe that generative AI may pose a threat to the goals that animate our work but could also be (...) valuable for achieving those goals. In the interests of fostering a wider conversation about how generative AI may be used, we have developed a preliminary set of recommendations for its use in scholarly publishing. We hope that the recommendations and rationales set out here will help the scholarly community navigate toward a deeper understanding of the strengths, limits, and challenges of AI for responsible scholarly work. (shrink)

This study analyses the linguistic interaction of human beings with Generative Artificial Intelligence (GAI) technologies in terms of Hans-Georg Gadamer’s philosophical hermeneutics. It can thus be concluded that: i) a distinction must be drawn between imitating a function and possessing a property when dealing with the ontology of GAI; ii) GAI technologies are capable of imitating certain human-like mental functions without necessarily possessing the human-like properties that underpin these functions; iii) the transformation of perception that has occurred in the postmodern (...) period, coupled with the perception that GAI possesses human-like properties, gives rise to an ontological illusion. (shrink)

Most workers report that they are alienated from their jobs and find their workplaces to be stifling and uninviting. Given this condition, the introduction of computer technology, including AI, will only make matters worse, unless a more humane organizational culture is created. The key point in this article is the need to produce a responsible technology, so that employees are not further overworked and manipulated. To achieve this end, phenomenology is invoked, particularly the life world, to provide (...) class='Hi'>technology with a human foundation. In practice, this shift in philosophy means that when AI is introduced into an organization, workers have a central role in the design, implementation, and evaluation of this technology. Computer technology can thus promote human flourishing instead of control and alienation in workplaces. (shrink)

While the concerns about media trust have historical roots, the dynamics have evolved with technological advancements, the rise of digital media, and the challenges posed by disinformation in the 21st century. Deepfake – the media content (text, images, videos) created by AI technology – is just another concern for journalists, politicians and society in the current media trust crisis. It is a tool that can be successfully applied in an information warfare. To be honest, face and voice spoofing has (...) always existed, but deepfake technology may now make fake videos faster, cheaper, with high quality and is accessible to anybody. Although deepfake videos have the potential to undermine trust in journalism, their actual impact on audiences remains limited due to information overload, increased suspicion and skeptical attitude, decreased trust in media and advanced audience adaptability for orientation in the information flow. (shrink)

In this paper I argue that Artificial Intelligence and the many data science methods associated with it, such as machine learning and large language models, are first and foremost epistemic technologies. In order to establish this claim, I first argue that epistemic technologies can be conceptually and practically distinguished from other technologies in virtue of what they are designed for, what they do and how they do it. I then proceed to show that unlike other kinds of technology (_including_ (...) other epistemic technologies) AI can be uniquely positioned as an epistemic technology in that it is primarily designed, developed and deployed to be used in _epistemic contexts_ such as inquiry, it is specifically designed, developed and deployed to manipulate _epistemic content_ such as data, _and_ it is designed, developed and deployed to do so particularly through _epistemic operations_ such as prediction and analysis. As has been shown in recent work in the philosophy and ethics of AI (Alvarado, AI and Ethics, 2022a), understanding AI as an epistemic technology will also have significant implications for important debates regarding our relationship to AI technologies. This paper includes a brief overview of such implications, particularly those pertaining to explainability, opacity, trust and even epistemic harms related to AI technologies. (shrink)

Generative artificial intelligence (AI) has the potential to transform many aspects of scholarly publishing. Authors, peer reviewers, and editors might use AI in a variety of ways, and those uses might augment their existing work or might instead be intended to replace it. We are editors of bioethics and humanities journals who have been contemplating the implications of this ongoing transformation. We believe that generative AI may pose a threat to the goals that animate our work but could also be (...) valuable for achieving those goals. In the interests of fostering a wider conversation about how generative AI may be used, we have developed a preliminary set of recommendations for its use in scholarly publishing. We hope that the recommendations and rationales set out here will help the scholarly community navigate toward a deeper understanding of the strengths, limits, and challenges of AI for responsible scholarly work. (shrink)

The new generative artificial intelligence (AI) tools, and especially the large language models (LLMs) of which ChatGPT is the most prominent example, have the potential to transform many aspects o...

Spence develops and applies a normative model based on rationalist and virtue ethics as well as stoic philosophy to assess the impact of technology on wellbeing. Through developing this model, Spence offers a novel and important examination of the benefit of technology to our society as a whole.

This article advances an explanatory model of the academic and policy debate on AI as legal persons. It argues that the scientific and regulatory debate on AI as legal persons undergoes periods of relative stability interrupted by rapid paradigm shifts. Three interrelated factors primarily influence these oscillations: (1) competing theories of legal personhood (clustered versus singularist), (2) capability, embodiment, and commercial reach of AI technology, and (3) AI's integration within socio-digital institutions. Two additional forces modulate the depth and durability (...) of any shift: (4) the overlap and internal consistency of cross‑domain legal regimes (data protection, agency, liability, cybersecurity); and (5) the body of judicial precedents (or their scarcity) on extending personhood. Specific convergences of these factors create pressure for status reconsideration; absent them, equilibrium returns. Current EU law and case practice are explained by partial convergence—capability/diffusion surges and some cluster‑theory uptake without sufficiently embedding AI in rights‑bearing institutional roles—and by the damping effect of dense, interlocking legal regimes, plus scarce and negative judicial precedents. Case law suggests that, without explicit legislation, courts are unlikely to grant AI legal personhood on their own. Prospective movement would require demonstrable de facto social personhood: sustained, role‑based participation within socio-digital institutions that creates governance gaps that existing doctrines cannot internalize. The article concludes by assessing near- and long‑term prospects — from generative AI, autonomous agents, social robots, and digital twins to brain–machine interface — highlighting conditional pathways rather than deterministic trajectories. (shrink)

The increasing demand for transparency in AI has recently come under scrutiny. The question is often posted in terms of “epistemic double standards”, and whether the standards for transparency in AI ought to be higher than, or equivalent to, our standards for ordinary human reasoners. I agree that the push for increased transparency in AI deserves closer examination, and that comparing these standards to our standards of transparency for other opaque systems is an appropriate starting point. I suggest that a (...) more fruitful exploration of this question will involve a different comparison class. We routinely treat judgments made by highly trained experts in specialized fields as fair or well-grounded even though—by the nature of expert/layperson division of epistemic labor—an expert will not be able to provide an explanation of the reasoning behind these judgments that makes sense to most other people. Regardless, laypeople are thought to be acting reasonably—and ethically—in deferring to the judgments of experts that concern their areas of specialization. I suggest that we reframe our question regarding the appropriate standards of transparency in AI as one that asks when, why, and to what degree it would be ethical to accept opacity in AI. I argue that our epistemic relation to certain opaque AI technology may be relevantly similar to the layperson’s epistemic relation to the expert in certain respects, such that the successful expert/layperson division of epistemic labor can serve as a blueprint for the ethical use of opaque AI. (shrink)

In this paper, we ask how ‘cognitive extenders’, based on AI technology, affect their users’ status as moral agents and the moral evaluation of their actions. We study how ‘AI-extenders’ can either enhance or diminish their users’ moral agency. On the one hand, they can broaden the scope of agential features and on the other hand, they can undermine the agent’s autonomy and lead to decreased responsibility. Our focus is on moral agency and responsibility of the AI-extended human being (...) as a hybrid, coupled system. Assuming standard conditions for responsible agency, we will look at specific cases where the extender would make a difference to the agent’s moral status. The thought-experimental extenders we are dealing with are enabled by already existing technologies. The obvious motivation behind the exercise is that these devices might be useful for people suffering from psychiatric conditions complicating the expression of their moral agency. We analyze the moral status of AI-extended agents as coupled systems and argue that the functioning of an AI-extender can make a difference to an agent’s fitness to be held morally responsible. This should be considered in the responsible design and development of AI-extenders. (shrink)

The new generative artificial intelligence (AI) tools, and especially the large language models (LLMs) of which ChatGPT is the most prominent example, have the potential to transform many aspects o...

To accurately evaluate and improve college students’ English writing ability, this article proposes a dynamic evaluation method of college English writing ability based on artificial intelligence technology. First, a dynamic evaluation model of college English writing ability is constructed. Second, the index system of English writing dynamic evaluation model is established. Based on this, the dynamic evaluation of college English writing ability is realized. The experimental results show that the design method in this paper can effectively realize the dynamic (...) evaluation of the writing process. After the application of the design method, the number of students interested in writing has increased by 37.8%, and the enthusiasm of students to participate in writing has been improved, with a view to providing some help to improve students’ English writing ability through this research. (shrink)

Humans may not be Earth’s most intelligent beings for much longer: the world champions of chess, Go, and Jeopardy! are now all AIs. Given the rapid pace of progress in AI, many predict that it could advance to human-level intelligence within the next several decades. From there, it could quickly outpace human intelligence. What do these developments mean for the future of the mind? -/- In Artificial You, Susan Schneider says that it is inevitable that AI will take intelligence in (...) new directions, but urges that it is up to us to carve out a sensible path forward. As AI technology turns inward, reshaping the brain, as well as outward, potentially creating machine minds, it is crucial to beware. Homo sapiens, as mind designers, will be playing with “tools” they do not understand how to use: the self, the mind, and consciousness. Schneider argues that an insufficient grasp of the nature of these entities could undermine the use of AI and brain enhancement technology, bringing about the demise or suffering of conscious beings. To flourish, we must grasp the philosophical issues lying beneath the algorithms. -/- At the heart of her exploration is a sober-minded discussion of what AI can truly achieve: Can robots really be conscious? Can we merge with AI, as tech leaders like Elon Musk and Ray Kurzweil suggest? Is the mind just a program? Examining these thorny issues, Schneider proposes ways we can test for machine consciousness, questions whether consciousness is an unavoidable byproduct of sophisticated intelligence, and considers the overall dangers of creating machine minds. Will AI Become Conscious? A Conversation with Susan Schneider Smart books for humans on AI Awards and Recognition One of Forbes' Must-Read Brain Books of 2019 Finalist for the PROSE Award in Philosophy, Association of American Publishers . (shrink)

This article demonstrates the extent to which prominent debates about the future of AI are best understood as subjective, philosophical disagreements over the history and future of technological change rather than as objective, material disagreements over the technologies themselves. It focuses on the deep disagreements over whether artificial general intelligence (AGI) will prove transformative for human society—a question that is analytically prior to that of whether this transformative effect will help or harm humanity. The article begins by distinguishing two fundamental (...) camps in this debate. The first of these can be identified as “transformationalists,” who argue that continued AI development will inevitably have a profound effect on society. Opposed to them are “skeptics,” a more eclectic group united by their disbelief that AI can or will live up to such high expectations. Each camp admits further “strong” and “weak” variants depending on their tolerance for epistemic risk. These stylized contrasts help identify a set of fundamental questions that shape the camps’ respective interpretations of the future of AI. Three questions in particular are focused on: the possibility of nonbiological intelligence, the appropriate time frame of technological predictions, and the assumed trajectory of technological development. In highlighting these specific points of nontechnical disagreement, this article demonstrates the wide range of different arguments used to justify either the transformationalist or skeptical position. At the same time, it highlights the strong argumentative burden of the transformationalist position, the way that belief in this position creates competitive pressures to achieve first-mover advantage, and the need to widen the concept of “expertise” in debates surrounding the future development of AI. (shrink)

One relatively neglected challenge in ethical artificial intelligence (AI) design is ensuring that AI systems invite a degree of emotional and moral concern appropriate to their moral standing. Although experts generally agree that current AI chatbots are not sentient to any meaningful degree, these systems can already provoke substantial attachment and sometimes intense emotional responses in users. Furthermore, rapid advances in AI technology could soon create AIs of plausibly debatable sentience and moral standing, at least by some relevant definitions. (...) Morally confusing AI systems create unfortunate ethical dilemmas for the owners and users of those systems, since it is unclear how those systems ethically should be treated. I argue here that, to the extent possible, we should avoid creating AI systems whose sentience or moral standing is unclear and that AI systems should be designed so as to invite appropriate emotional responses in ordinary users. (shrink)

In recent years, research in robotics and artificial intelligence (AI) has made rapid progress. It is expected that robots and AI will play a part in the field of nursing and their role might broaden in the future. However, there are areas of nursing practice that cannot or should not be entrusted to robots and AI, because nursing is a highly humane practice, and therefore, there would, perhaps, be some practices that should not be replicated by robots or AI. Therefore, (...) this paper focuses on several ethical concepts (advocacy, accountability, cooperation, and caring) that are considered important in nursing practice, and examines whether it is possible to implement these ethical concepts in robots and AI by analyzing the concepts and the current state of robotics and AI technology. Advocacy: Among the components of advocacy, safeguarding and apprising can be more easily implemented, while elements that require emotional communication with patients, such as valuing and mediating, are difficult to implement. Accountability: Robotic nurses with explainable AI have a certain level of accountability. However, the concept of explanation has problems of infinite regression and attribution of responsibility. Cooperation: If robot nurses are recognized as members of a community, they require the same cooperation as human nurses. Caring: More difficulties are expected in care-receiving than in caregiving. However, the concept of caring itself is ambiguous and should be explored further. Accordingly, our analysis suggests that, although some difficulties can be expected in each of these concepts, it cannot be said that it is impossible to implement them in robots and AI. However, even if it were possible to implement these functions in the future, further study is needed to determine whether such robots or AI should be used for nursing care. In such discussions, it will be necessary to involve not only ethicists and nurses but also an array of society members. (shrink)

Andy Clark and David Chalmers’s theory of extended mind can be reevaluated in today’s world to include computational and Artificial Intelligence (AI) technology. This paper argues that AI can be an extension of human mind, and that if we agree that AI can have mind, it too can be extended. It goes on to explore the example of Ganbreeder, an image-making AI which utilizes human input to direct behavior. Ganbreeder represents one way in which AI extended mind could be (...) achieved. The argument of this paper is that AI can utilize human input as a social extension of mind, allowing AI to access the external world that it would not otherwise be able to access. (shrink)

Speaking with conversational AIs, technologies whose interfaces enable human-like interaction based on natural language, has become a common phenomenon. During these interactions, people form their beliefs due to the say-so of conversational AIs. In this paper, I consider, and then reject, the concepts of testimony-based beliefs and instrument-based beliefs as suitable for analysis of beliefs acquired from these technologies. I argue that the concept of instrument-based beliefs acknowledges the non-human agency of the source of the belief. However, the analysis focuses (...) on perceiving signs and indicators rather than content expressed in natural language. At the same time, the concept of testimony-based beliefs does refer to natural language propositions, but there is an underlying assumption that the agency of the testifier is human. To fill the lacuna of analyzing belief acquisition from conversational AIs, I suggest a third concept: technology-based beliefs. It acknowledges the non-human agency-status of the originator of the belief. Concurrently, the focus of analysis is on the propositional content that forms the belief. Filling the lacuna enables analysis that considers epistemic, ethical, and social issues of conversational AIs without excluding propositional content or compromising accepted assumptions about the agency of technologies. (shrink)

Humans and AI systems are usually portrayed as separate sys- tems that we need to align in values and goals. However, there is a great deal of AI technology found in non-autonomous systems that are used as cognitive tools by humans. Under the extended mind thesis, the functional contributions of these tools become as essential to our cognition as our brains. But AI can take cognitive extension towards totally new capabil- ities, posing new philosophical, ethical and technical chal- lenges. (...) To analyse these challenges better, we define and place AI extenders in a continuum between fully-externalized systems, loosely coupled with humans, and fully-internalized processes, with operations ultimately performed by the brain, making the tool redundant. We dissect the landscape of cog- nitive capabilities that can foreseeably be extended by AI and examine their ethical implications. We suggest that cognitive extenders using AI be treated as distinct from other cognitive enhancers by all relevant stakeholders, including developers, policy makers, and human users. (shrink)

In 2017, Tom Gruber held a TED talk, in which he presented a vision of improving and enhancing humanity with AI technology. Specifically, Gruber suggested that an AI-improved personal memory (APM) would benefit people by improving their “mental gain”, making us more creative, improving our “social grace”, enabling us to do “science on our own data about what makes us feel good and stay healthy”, and, for people suffering from dementia, it “could make a difference between a life of (...) isolation and a life of dignity and connection”. -/- In this paper, Gruber’s idea will be critically assessed. Firstly, it will be argued that most of his pro-arguments for the APM are questionable. Secondly, the APM will also be criticized for other reasons, including the risks and affects to the users’ and other’s privacy and the users’ autonomy. (shrink)

Abstract:Artificial intelligence is profoundly transforming the world in various spheres and already finding its way into educational institutions. This essay aims to examine whether the Deweyan ideal of education can be achieved through such digital means. By analyzing how both the aims and means of education, as defined by Dewey, can be understood in the context of learning with artificial intelligence, the inherent differences of both educational approaches are brought out. It becomes apparent that important concepts that characterize successful education (...) for Dewey, such as intrinsic inquiry, experience-based schooling, and thinking as the method for learning, do not go hand in hand with intelligent teaching systems. (shrink)

As artificial intelligence technologies become increasingly prominent in our daily lives, media coverage of the ethical considerations of these technologies has followed suit. Since previous research has shown that media coverage can drive public discourse about novel technologies, studying how the ethical issues of AI are portrayed in the media may lead to greater insight into the potential ramifications of this public discourse, particularly with regard to development and regulation of AI. This paper expands upon previous research by systematically analyzing (...) and categorizing the media portrayal of the ethical issues of AI to better understand how media coverage of these issues may shape public debate about AI. Our results suggest that the media has a fairly realistic and practical focus in its coverage of the ethics of AI, but that the coverage is still shallow. A multifaceted approach to handling the social, ethical and policy issues of AI technology is needed, including increasing the accessibility of correct information to the public in the form of fact sheets and ethical value statements on trusted webpages, collaboration and inclusion of ethics and AI experts in both research and public debate, and consistent government policies or regulatory frameworks for AI technology. (shrink)