The landscape of cybersecurity is constantly evolving, with adversaries becoming increasingly sophisticated and persistent. This manuscript explores the utilization of artificial intelligence (AI) to address these evolving threats, focusing on the journey from threat detection to autonomous response. By examining AI-driven detection methodologies, advanced threat analytics, and the implementation of autonomous response systems, this paper provides insights into how organizations can leverage AI to strengthen their cybersecurity posture against modern threats. Key words: Ransomware, Anomaly Detection, (...) Advanced Persistent Threats (APTs), Automated Threat Response and Artificial 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)

Home management and controlling have seen a great introduction to network that enabled digital technology, especially in recent decades. For the purpose of home automation, this technique offers an exciting capability to enhance the connectivity of equipment within the home. Also, with the rapid expansion of the Internet, there are potentials that added to the remote control and monitoring of such network-enabled devices. In this paper, we had been designed and implemented a fully manageable and secure smart home automation system (...) based on a cloud computing system with an ESP Arduino system. The security of home had been improved by adding a complete camera system with a GSM communication technique to connect the Arduino output data to an external specified number if there is no internet provider. We used three sensors for temperature, gas, and motion measurements. The ESP8226 Wi-Fi device programmed the sensors to maintain the sensors measurements and transfer them to the cloud server database which is programmed to the web server via Appatshy and Mysql formats. The system implemented with high time response so that all readings updated and appeared spontaneously. The designed system should be effective, a secure, and rapid response real-time smart home system should be achieved. (shrink)

This article offers an overview of the main first-order ethical questions raised by robots and Artificial Intelligence (RAIs) under five broad rubrics: functionality, inherent significance, rights and responsibilities, side-effects, and threats. The first letter of each rubric taken together conveniently generates the acronym FIRST. Special attention is given to the rubrics of functionality and inherent significance given the centrality of the former and the tendency to neglect the latter in virtue of its somewhat nebulous and contested character. In addition (...) to exploring some illustrative issues arising under each rubric, the article also emphasizes a number of more general themes. These include: the multiplicity of interacting levels on which ethical questions about RAIs arise, the need to recognise that RAIs potentially implicate the full gamut of human values (rather than exclusively or primarily some readily identifiable sub-set of ethical or legal principles), and the need for practically salient ethical reflection on RAIs to be informed by a realistic appreciation of their existing and foreseeable capacities. -/- . (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)

Deepfakes pose a multi-faceted threat to the acquisition of knowledge. It is widely hoped that technological solutions—in the form of artificially intelligent systems for detecting deepfakes—will help to address this threat. I argue that the prospects for purely technological solutions to the problem of deepfakes are dim. Especially given the evolving nature of the threat, technological solutions cannot be expected to prevent deception at the hands of deepfakes, or to preserve the authority of video footage. Moreover, the (...) success of such technologies depends on institutional trust that is in short supply. Finally, outsourcing the discrimination between the real and the fake to automated, largely opaque systems runs the risk of undermining epistemic autonomy. (shrink)

As the aim of the responsible robotics initiative is to ensure that responsible practices are inculcated within each stage of design, development and use, this impetus is undergirded by the alignment of ethical and legal considerations towards socially beneficial ends. While every effort should be expended to ensure that issues of responsibility are addressed at each stage of technological progression, irresponsibility is inherent within the nature of robotics technologies from a theoretical perspective that threatens to thwart the endeavour. This is (...) because the concept of responsibility, despite being treated as such, is not monolithic: rather this seemingly unified concept consists of converging and confluent concepts that shape the idea of what we colloquially call responsibility. From a different perspective, robotics will be simultaneously responsible and irresponsible depending on the particular concept of responsibility that is foregrounded: an observation that cuts against the grain of the drive towards responsible robotics. This problem is further compounded by responsible design and development as contrasted to responsible use. From a different perspective, the difficulty in defining the concept of responsibility in robotics is because human responsibility is the main frame of reference. Robotic systems are increasingly expected to achieve the human-level performance, including the capacities associated with responsibility and other criteria which are necessary to act responsibly. This subsists within a larger phenomenon where the difference between humans and non-humans, be it animals or artificial systems, appears to be increasingly blurred, thereby disrupting orthodox understandings of responsibility. This paper seeks to supplement the responsible robotics impulse by proposing a complementary set of human rights directed specifically against the harms arising from robotic and artificial intelligence technologies. The relationship between responsibilities of the agent and the rights of the patient suggest that a rights regime is the other side of responsibility coin. The major distinction of this approach is to invert the power relationship: while human agents are perceived to control robotic patients, the prospect for this to become reversed is beginning. As robotic technologies become ever more sophisticated, and even genuinely complex, asserting human rights directly against robotic harms become increasingly important. Such an approach includes not only developing human rights that ‘protect’ humans but also ‘strengthen’ people against the challenges introduced by robotics and AI [This distinction parallels Berlin’s negative and positive concepts of liberty ], by emphasising the social and reflective character of the notion of humanness as well as the difference between the human and nonhuman. This will allow using the human frame of reference as constitutive of, rather than only subject to, the robotic and AI technologies, where it is human and not technology characteristics that shape the human rights framework in the first place. (shrink)

This paper delves into the use of machine learning-based systems in decision-making processes and its implications for moral responsibility as traditionally defined. It focuses on the emergence of responsibility gaps and examines proposed strategies to address them. The paper aims to provide an introductory and comprehensive overview of the ongoing debate surrounding moral responsibility in automated decision-making. By thoroughly examining these issues, we seek to contribute to a deeper understanding of the implications of AI integration in society.

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)

In the case of AI, automated systems are making increasingly complex decisions with significant ethical implications, raising questions about who is responsible for decisions made by AI and how to ensure that these decisions align with society's ethical and moral values, both in India and the West. Jonathan Haidt has conducted research on moral and ethical decision-making. Today, solving problems like decision-making in autonomous vehicles can draw on the literature of the trolley dilemma in that it illustrates the complexity (...) of ethical decisions faced in emergency situations, as well as the moral implications of the decisions made. However, a series of moral principles must be understood and cited to avoid insufficient mechanistic explanations. Here we present a compilation of ethical positions both in India and the West. (shrink)

Rapid advances in AI-based automation have led to a number of existential and economic concerns. In particular, as automating technologies develop enhanced competency they seem to threaten the values associated with meaningful work. In this article, we focus on one such value: the value of achievement. We argue that achievement is a key part of what makes work meaningful and that advances in AI and automation give rise to a number achievement gaps in the workplace. This could limit people’s ability (...) to participate in meaningful forms of work. Achievement gaps are interesting, in part, because they are the inverse of the (negative) responsibility gaps already widely discussed in the literature on AI ethics. Having described and explained the problem of achievement gaps, the article concludes by identifying four possible policy responses to the problem. (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)

Concerns about threats to human autonomy feature prominently in the field of AI ethics. One aspect of this concern relates to the use of AI systems for problematically manipulative influence. In response to this, the European Union’s draft AI Act (AIA) includes a prohibition on AI systems deploying subliminal techniques that alter people’s behavior in ways that are reasonably likely to cause harm (Article 5(1)(a)). Critics have argued that the term ‘subliminal techniques’ is too narrow to capture the target (...) cases of AI-based manipulation. We propose a definition of ‘subliminal techniques’ that (a) is grounded on a plausible interpretation of the legal text; (b) addresses all or most of the underlying ethical concerns motivating the prohibition; (c) is defensible from a scientific and philosophical perspective; and (d) does not over-reach in ways that impose excessive administrative and regulatory burdens. The definition is meant to provide guidance for design teams seeking to pursue responsible and ethically aligned AI innovation. (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)

Whatever one makes of the relationship between free will and moral responsibility – e.g. whether it’s the case that we can have the latter without the former and, if so, what conditions must be met; whatever one thinks about whether artificially intelligent agents might ever meet such conditions, one still faces the following questions. What is the value of moral responsibility? If we take moral responsibility to be a matter of being a fitting target of moral blame or praise, what (...) are the goods attached to them? The debate concerning ‘machine morality’ is often hinged on whether artificial agents are or could ever be morally responsible, and it is generally taken for granted (following Matthias 2004) that if they cannot, they pose a threat to the moral responsibility system and associated goods. In this paper, I challenge this assumption by asking what the goods of this system, if any, are, and what happens to them in the face of artificially intelligent agents. I will argue that they neither introduce new problems for the moral responsibility system nor do they threaten what we really (ought to) care about. I conclude the paper with a proposal for how to secure this objective. (shrink)

Technology and Artificial Intelligence, both today and in the near future, are dominated by automated algorithms that combine optimization with models based on the human brain to learn, predict, and even influence the large-scale behavior of human users. Such applications can be understood to be outgrowths of historical trends in industry and academia, yet have far-reaching and even unintended consequences for social and political life around the world. Countries in different parts of the world take different regulatory views (...) for the role and protection of user data, and this will in turn determine the course of development for technology and AI in the near future. (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)

On the one hand, people have witnessed a lot of amazing technological inventions and innovations in the multifaceted performances of artificial intelligence systems ever since the earliest stages of their development. Activities previously done with a lot of manual and muscular efforts are now accomplished with no sweat and just at the tip of one’s finger. I would venture to say that artificial intelligence is among the highest scientific and technological achievements of humanity in the post-modern civilization. Yet (...) on the other hand, are we worried that humanity will soon be threatened by the dark side of AI systems when the truth of the matter is long before the advent of AI, humanity has always been threatened by the evil forces of totalitarian powers well-entrenched in governments and big capitalist empires in control of nations’ economies? Future AI systems employed and mobilized in the service of these political and economic powers will certainly heighten the degree of their oppressive domination and intensify the common people’s oppression. (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)

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)

The notion of computation has changed the world more than any previous expressions of knowledge. However, as know-how in its particular algorithmic embodiment, computation is closed to meaning. Therefore, computer-based data processing can only mimic life’s creative aspects, without being creative itself. AI’s current record of accomplishments shows that it automates tasks associated with intelligence, without being intelligent itself. Mistaking the abstract for the concrete has led to the religion of “everything is an output of computation”—even the humankind that conceived (...) the computer. The hypostatized role of computers explains the increased dependence on them. The convergence machine called deep learning is only the most recent form through which the deterministic theology of the machine claims more than what it actually is: extremely effective data processing. A proper understanding of complexity, as well as the need to distinguish between the reactive nature of the artificial and the anticipatory nature of the living are suggested as practical responses to the challenges posed by machine theology. (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)

Advances in AI are powering increasingly precise and widespread computational propaganda, posing serious threats to national security. The military and intelligence communities are starting to discuss ways to engage in this space, but the path forward is still unclear. These developments raise pressing ethical questions, about which existing ethics frameworks are silent. Understanding these challenges through the lens of “cognitive security,” we argue, offers a promising approach.

Since the Enlightenment, there have been advocates for the rationalizing efficiency of enlightened sovereigns, bureaucrats, and technocrats. Today these enthusiasms are joined by calls for replacing or augmenting government with algorithms and artificial intelligence, a process already substantially under way. Bureaucracies are in effect algorithms created by technocrats that systematize governance, and their automation simply removes bureaucrats and paper. The growth of algorithmic governance can already be seen in the automation of social services, regulatory oversight, policing, the justice system, (...) and the military. However, there have also always been justified democratic and economic criticisms of autocracy, bureaucracy, technocracy, and algorithmic governance. Bureaucrats, technocrats, and algorithms embody biases that tend to serve the interests of elites, and all require transparency and democratic accountability, oversight individual citizens are ill equipped to exercise. As state apparatuses are increasingly automated, mechanisms for collective action and democratic oversight also need to be automated. Algorithms and cyborg citizenry will enable a posthuman democracy. Democratically accountable algorithmic governance, enabled by artificial intelligence and human enhancement, can automate bottom-up citizen surveillance, inform debate, aggregate decision making, and ensure the efficient working of the gradually withering state. As paid work disappears and we transition to a postcapitalist economy with a universal basic income, market mechanisms can be replaced with democratic planning. Indeed, only algorithmic governance can secure our future against accelerating threats from technological innovation. (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)

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 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)

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)

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.

Historically, scientific and engineering expertise has been key in shaping research and innovation policies, with benefits presumed to accrue to society more broadly over time. But there is persistent and growing concern about whether and how ethical and societal values are integrated into R&I policies and governance, as we confront public disbelief in science and political suspicion toward evidence-based policy-making. Erosion of such a social contract with science limits the ability of democratic societies to deal with challenges presented by new, (...) disruptive technologies, such as synthetic biology, nanotechnology, genetic engineering, automation and robotics, and artificial intelligence. Many policy efforts have emerged in response to such concerns, one prominent example being Europe's Eighth Framework Programme, Horizon 2020, whose focus on “Responsible Research and Innovation” provides a case study for the translation of such normative perspectives into concrete policy action and implementation. Our analysis of this H2020 RRI approach suggests a lack of consistent integration of elements such as ethics, open access, open innovation, and public engagement. On the basis of our evaluation, we suggest possible pathways for strengthening efforts to deliver R&I policies that deepen mutually beneficial science and society relationships. (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)

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)

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)

Electronic warfare is a critical component of modern military operations and has undergone significant advances in recent years. This book provides an overview of electronic warfare, its historical development, key components, and its role in contemporary conflict scenarios. It also discusses emerging trends and challenges in electronic warfare and its contemporary relevance in an era of advanced technology and cyber threats, emphasizing the need for continued research and development in this area. The book explores the burgeoning intersection of artificial (...) intelligence and electronic warfare, highlighting the evolving landscape of modern conflicts and the implications of integrating advanced technologies. The multifaceted roles of artificial intelligence in electronic warfare are highlighted, examining its potential advantages, ethical considerations, and challenges associated with its integration. (shrink)

Forms of Artificial Intelligence (AI) are already being deployed into clinical settings and research into its future healthcare uses is accelerating. Despite this trajectory, more research is needed regarding the impacts on patients of increasing AI decision making. In particular, the impersonal nature of AI means that its deployment in highly sensitive contexts-of-use, such as in healthcare, raises issues associated with patients’ perceptions of (un) dignified treatment. We explore this issue through an experimental vignette study comparing individuals’ perceptions of (...) being treated in a dignified and respectful way in various healthcare decision contexts. Participants were subject to a 2 (human or AI decision maker) x 2 (positive or negative decision outcome) x 2 (diagnostic or resource allocation healthcare scenario) factorial design. We found evidence of a “human bias” (i.e., a preference for human over AI decision makers) and an “outcome bias” (i.e., a preference for positive over negative outcomes). However, we found that for perceptions of respectful and dignified interpersonal treatment, it matters more who makes the decisions in diagnostic cases and it matters more what the outcomes are for resource allocation cases. We also found that humans were consistently viewed as appropriate decision makers and AI was viewed as dehumanizing, and that participants perceived they were treated better when subject to diagnostic as opposed to resource allocation decisions. Thematic coding of open-ended text responses supported these results. We also outline the theoretical and practical implications of these findings. (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)

Can nonhuman animals and artificial intelligence (AI) entities be attributed moral agency? The general assumption in the philosophical literature is that moral agency applies exclusively to humans since they alone possess free will or capacities required for deliberate reflection. Consequently, only humans have been taken to be eligible for ascriptions of moral responsibility in terms of, for instance, blame or praise, moral criticism, or attributions of vice and virtue. Animals and machines may cause harm, but they cannot be appropriately (...) ascribed moral responsibility for their behavior. This thesis challenges the conventional paradigm by proposing an alternative approach where moral agency is conceived as the competence to participate in moral responsibility practices. By shifting focus from intra-individual to contextual and socially situated features, this practice-focused approach appears to make the attribution of moral agency to nonhuman animals and AI entities more plausible than commonly assumed. Moreover, considering the current and potential future prevalence of nonhuman animals and AI entities in everyday settings and social contexts, a potential extension of moral agency to such entities could very well transform our social, moral, and legal practices. Hence, this thesis proposes that the attribution or withholding of moral agency to different entities should be carefully evaluated, considering the potential normative implications. (shrink)

Since the launch of applications such as DALL-E, Midjourney, and Stable Diffusion, generative artificial intelligence has been controversial as a tool for creating artwork. While some have presented longtermist worries about these technologies as harbingers of fully automated futures to come, more pressing is the impact of generative AI on creative labour in the present. Already, business leaders have begun replacing human artistic labour with AI-generated images. In response, the artistic community has launched a protest movement, which (...) argues that AI image generation is a kind of theft. This paper analyzes, substantiates, and critiques these arguments, concluding that AI image generators involve an unethical kind of labour theft. If correct, many other AI applications also rely upon theft. (shrink)

This book is a collection of all the papers published in the special issue “Artificial Intelligence, Robots, and Philosophy,” Journal of Philosophy of Life, Vol.13, No.1, 2023, pp.1-146. The authors discuss a variety of topics such as science fiction and space ethics, the philosophy of artificial intelligence, the ethics of autonomous agents, and virtuous robots. Through their discussions, readers are able to think deeply about the essence of modern technology and the future of humanity. All papers were invited (...) and completed in spring 2020, though because of the Covid-19 pandemic and other problems, the publication was delayed until this year. I apologize to the authors and potential readers for the delay. I hope that readers will enjoy these arguments on digital technology and its relationship with philosophy. *** -/- Contents*** -/- Introduction : Descartes and Artificial Intelligence; Masahiro Morioka*** -/- Isaac Asimov and the Current State of Space Science Fiction : In the Light of Space Ethics; Shin-ichiro Inaba*** -/- Artificial Intelligence and Contemporary Philosophy : Heidegger, Jonas, and Slime Mold; Masahiro Morioka*** -/- Implications of Automating Science : The Possibility of Artificial Creativity and the Future of Science; Makoto Kureha*** -/- Why Autonomous Agents Should Not Be Built for War; István Zoltán Zárdai*** -/- Wheat and Pepper : Interactions Between Technology and Humans; Minao Kukita*** -/- Clockwork Courage : A Defense of Virtuous Robots; Shimpei Okamoto*** -/- Reconstructing Agency from Choice; Yuko Murakami*** -/- Gushing Prose : Will Machines Ever be Able to Translate as Badly as Humans?; Rossa Ó Muireartaigh***. (shrink)

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

Alan Turing, one of the fathers of computing, warned that Artificial Intelligence (AI) could one day pose an existential risk to humanity. Today, recent advancements in the field AI have been accompanied by a renewed set of existential warnings. But what exactly constitutes an existential risk? And how exactly does AI pose such a threat? In this chapter we aim to answer these questions. In particular, we will critically explore three commonly cited reasons for thinking that AI poses (...) an existential threat to humanity: the control problem, the possibility of global disruption from an AI race dynamic, and the weaponization of AI. (shrink)

Machine-based automation has long been a key factor in the modern era. However, lately, many people have been shocked by artificial intelligence (AI) applications, such as ChatGPT (OpenAI), that can perform tasks previously thought to be human-exclusive. With recent advances in natural language processing (NLP) technologies, AI can generate written content that is similar to human-made products, and this ability has a variety of applications. As the technology of large language models continues to progress by making use of colossal (...) reservoirs of digital information, AI is becoming more capable of recognizing patterns and associations within given contexts, making it especially helpful in assisting with various professional writing tasks [1]. In this paper, we will discuss several key points regarding the current state and future of AI in academia. Furthermore, since in certain aspects, acts can speak louder than words, we will also present some of our hands-on experiences of working with ChatGPT. (shrink)

This book explores the use of artificial intelligence by intelligence services around the world and its critical role in intelligence analysis, defense, and national security. Intelligence services play a crucial role in national security, and the adoption of artificial intelligence technologies has had a significant impact on their operations. It also examines the various applications of artificial intelligence in intelligence services, the implications, challenges and ethical considerations associated with its use. The book emphasizes the need for continued (...) research and development in the field of artificial intelligence to ensure that intelligence services. and overall national defense and security can effectively adapt to emerging threats. -/- CONTENTS: -/- Abstract Introduction The evolution of AI Uses and applications Implications and advantages Strategies and implementation - A successful example: SABLE SPEAR Challenges and limitations Conclusion Bibliography -/- DOI: 10.58679/MM72104. (shrink)

There is an underappreciated respect in which the widespread availability of generative artificial intelligence (AI) models poses a threat to human connection. The central contention is that human creativity is especially capable of helping us connect to others in a valuable way, but the widespread availability of generative AI models reduces our incentives to engage in various sorts of creative work in the arts and sciences. I argue that creative endeavors must be motivated by curiosity, and so they (...) must disclose the creative agent’s inquisitive self. It is through self-disclosure, including the disclosure of the inquisitive self, that we put ourselves in a position to be seen by and connect with others through our creative pursuits. Because relying on AI for certain generative tasks is less self-disclosive than the creative work such technologies supplant, this reliance threatens to weaken our connections to one another. (shrink)

As artificial intelligence becomes more sophisticated and robots approach autonomous decision-making, debates about how to assign moral responsibility have gained importance, urgency, and sophistication. Answering Stenseke’s (2022a) call for scaffolds that can help us classify views and commitments, we think the current debate space can be represented hierarchically, as answers to key questions. We use the resulting taxonomy of five stances to differentiate—and defend—what is known as the “blank check” proposal. According to this proposal, a person activating a robot (...) could willingly make themselves answerable for whatever events ensue, even if those events stem from the robot’s autonomous decision(s). This blank check solution was originally proposed in the context of automated warfare (Champagne & Tonkens, 2015), but we extend it to cover all robots. We argue that, because moral answerability in the blank check is accepted voluntarily and before bad outcomes are known, it proves superior to alternative ways of assigning blame. We end by highlighting how, in addition to being just, this self-initiated and prospective moral answerability for robot harm provides deterrence that the four other stances cannot match. (shrink)

The article presents the grounds for defining the fetish of artificial intelligence (AI). The fundamental differences of AI from all previous technological innovations are highlighted, as primarily related to the introduction into the human cognitive sphere and fundamentally new uncontrolled consequences for society. Convincing arguments are presented that the leaders of the globalist project are the main beneficiaries of the AI fetish. This is clearly manifested in the works of philosophers close to big technology corporations and their mega-projects. It (...) is proposed to consider the problem of how to use the capabilities of AI to overcome the growing international conflicts and the global crisis in general. The focus is on the problem of subjectness, the solution of which from the standpoint of an anthropomorphic approach to AI is fraught with serious negative consequences. When endowing AI with subjectness, responsibility is implicitly removed from the person who uses this technology, and the established legislative practice is also destroyed. The presentation of AI as an agent endowed with a set of invariant simplified qualities that natural subjects have is proposed. These qualities include: the ability to purposefulness, a kind of reflexivity, communication and simplified elements of sociality. Such a representation of AI as an agent (pseudo-subject) is consistent with the principle of distributed control in biology and psychology, which was called the principle of a dual subject. In combination with the systems of principles and ontologies specified in the concept of post-nonclassical cybernetics of self-developing environments, this will allow the use of AI as a means of social innovation, while maintaining control over AI technologies. And also to pose and solve the problem of integrating the formations of artificial and natural intelligence while maintaining the basic qualities of carriers of natural intelligence. (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)

Abstract: The integration of Artificial Intelligence (AI) into Human Resource Management (HRM) is fundamentally transforming how organizations approach recruitment, performance management, and employee engagement. This paper explores the multifaceted impact of AI on HR practices, highlighting its role in enhancing efficiency, reducing bias, and driving strategic decision-making. Through an in-depth analysis of AI-driven recruitment tools, performance management systems, and personalized employee engagement strategies, this study examines both the opportunities and challenges associated with AI in HRM. Ethical considerations, including data (...) privacy, algorithmic bias, and the potential displacement of human jobs, are critically discussed to provide a balanced perspective on the adoption of AI technologies in the HR domain. By presenting case studies of organizations successfully leveraging AI, this paper offers insights into the future trajectory of HRM in an increasingly AI-driven world. Ultimately, the findings underscore the need for HR professionals to adapt and innovate in response to the growing influence of AI, ensuring a harmonious balance between technological advancement and the human element in the workplace. (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)