Artificial Intelligence (AI) is taking centre stage in economic growth and business operations alike. Public discourse about the practical and ethical implications of AI has mainly focussed on the societal level. There is an emerging knowledge base on AI risks to human rights around data security and privacy concerns. A separate strand of work has highlighted the stresses of working in the gig economy. This prevailing focus on human rights and gig impacts has been at the expense of a (...) closer look at how AI may be reshaping traditional workplace relations and, more specifically, workplace health and safety. To address this gap, we outline a conceptual model for developing an AI Work Health and Safety (WHS) Scorecard as a tool to assess and manage the potential risks and hazards to workers resulting from AI use in a workplace. A qualitative, practice-led research study of AI adopters was used to generate and test a novel list of potential AI risks to worker health and safety. Risks were identified after cross-referencing Australian AI Ethics Principles and Principles of Good Work Design with AI ideation, design and implementation stages captured by the AI Canvas, a framework otherwise used for assessing the commercial potential of AI to a business. The unique contribution of this research is the development of a novel matrix itemising currently known or anticipated risks to the WHS and ethical aspects at each AI adoption stage. (shrink)

With automation of routine decisions coupled with more intricate and complex information architecture operating this automation, concerns are increasing about the trustworthiness of these systems. These concerns are exacerbated by a class of artificial intelligence that uses deep learning, an algorithmic system of deep neural networks, which on the whole remain opaque or hidden from human comprehension. This situation is commonly referred to as the black box problem in AI. Without understanding how AI reaches its conclusions, it is an open (...) question to what extent we can trust these systems. The question of trust becomes more urgent as we delegate more and more decision-making to and increasingly rely on AI to safeguard significant human goods, such as security, healthcare, and safety. Models that “open the black box” by making the non-linear and complex decision process understandable by human observers are promising solutions to the black box problem in AI but are limited, at least in their current state, in their ability to make these processes less opaque to most observers. A philosophical analysis of trust will show why transparency is a necessary condition for trust and eventually for judging AI to be trustworthy. A more fruitful route for establishing trust in AI is to acknowledge that AI is situated within a socio-technical system that mediates trust, and by increasing the trustworthiness of these systems, we thereby increase trust in AI. (shrink)

As government pressure on major technology companies builds, both firms and legislators are searching for technical solutions to difficult platform governance puzzles such as hate speech and misinformation. Automated hash-matching and predictive machine learning tools – what we define here as algorithmic moderation systems – are increasingly being deployed to conduct content moderation at scale by major platforms for user-generated content such as Facebook, YouTube and Twitter. This article provides an accessible technical primer on how algorithmic moderation works; examines some (...) of the existing automated tools used by major platforms to handle copyright infringement, terrorism and toxic speech; and identifies key political and ethical issues for these systems as the reliance on them grows. Recent events suggest that algorithmic moderation has become necessary to manage growing public expectations for increased platform responsibility, safety and security on the global stage; however, as we demonstrate, these systems remain opaque, unaccountable and poorly understood. Despite the potential promise of algorithms or ‘AI’, we show that even ‘well optimized’ moderation systems could exacerbate, rather than relieve, many existing problems with content policy as enacted by platforms for three main reasons: automated moderation threatens to further increase opacity, making a famously non-transparent set of practices even more difficult to understand or audit, further complicate outstanding issues of fairness and justice in large-scale sociotechnical systems and re-obscure the fundamentally political nature of speech decisions being executed at scale. (shrink)

Recent AI progress led to a boost in beneficial applications from multiple research areas including VR. Simultaneously, in this newly unfolding deepfake era, ethically and security-relevant disagreements arose in the scientific community regarding the epistemic capabilities of present-day AI. However, given what is at stake, one can postulate that for a responsible approach, prior to engaging in a rigorous epistemic assessment of AI, humans may profit from a self-questioning strategy, an examination and calibration of the experience of their own (...) epistemic agency – especially to counteract both intentional misdirection by unethical actors and unintentional epistemic self-sabotage. In this paper, we expound on a new avenue of utilizing AIVR tools to advance an AI-related misdirection awareness of humans in the deepfake era. Firstly, we harness scientific knowledge from the psychology and neuroscience of magic where the study of misdirection techniques is center stage. Secondly, we connect the latter to creativity research linking human creative potential to inspiration from the seemingly impossible. Overall, AIVR could become an empowering experiential testbed for human epistemic agency enabling a better rational evaluation of AI capabilities. However, a misuse of the same type of tools could yield AIVR safety risks if not counteracted preemptively. (shrink)

A growing number of consumer technology companies are aiming to convince older people that humanoid robots make helpful tools to support aging-in-place. As hybrid devices, socially assistive robots (SARs) are situated between health monitoring tools, familiar digital assistants, security aids, and more advanced AI-powered devices. Consequently, they implicate older people’s privacy in complex ways. Such devices are marketed to perform functions common to smart speakers (e.g., Amazon Echo) and smart home platforms (e.g., Google Home), while other functions are more (...) specific to older people, including health and safety monitoring and serving as companions to mitigate loneliness. Privacy is a key value central to debates about the ethics of using SARs in aged care, yet there has been very little interchange between these debates and the robust theoretical discussion in the legal literature about the future of privacy and AI governance. Drawing on two qualitative studies of older people’s views on consumer SARs, the paper contributes novel findings about older people’s thinking on privacy and data governance at the intersection of their experiences with present day digital technologies and projections for future AI systems, and places their views in dialogue with debates about the future of privacy protection and AI governance. (shrink)

The book examines the extent to which Chinese cyber and network security laws and policies act as a constraint on the emergence of Chinese entrepreneurialism and innovation. Specifically, how the contradictions and tensions between data localisation laws affect innovation in artificial intelligence. The book surveys the globalised R&D networks, and how the increasing use of open-source platforms by leading Chinese AI firms during 2017–2020, exacerbated the apparent contradiction between Network Sovereignty and Chinese innovation. The drafting of the Cyber (...) class='Hi'>Security Law did not anticipate the changing nature of globalised AI innovation. It is argued that the deliberate deployment of what the book refers to as 'fuzzy logic' in drafting the Cyber Security Law allowed regulators to subsequently interpret key terms regarding data in that Law in a fluid and flexible fashion to benefit Chinese innovation. (shrink)

There is no strong reason to believe that human-level intelligence represents an upper limit of the capacity of artificial intelligence, should it be realized. This poses serious safety issues, since a superintelligent system would have great power to direct the future according to its possibly flawed motivation system. Solving this issue in general has proven to be considerably harder than expected. This paper looks at one particular approach, Oracle AI. An Oracle AI is an AI that does not act (...) in the world except by answering questions. Even this narrow approach presents considerable challenges. In this paper, we analyse and critique various methods of controlling the AI. In general an Oracle AI might be safer than unrestricted AI, but still remains potentially dangerous. (shrink)

The article discusses the uncertainty of legal definitions of aviation safety and and aviation security, the implementation of which often result in certain restrictions of human rights. In the article, a hypothesis is made that, despite usually treated as well-known concepts, safety and security are not so clear and well-defined, often leaving the reader to guess at their precise meaning. The aim of this article is to identify the core features that characterise aviation safety and (...) aviation security and could disclose their legal content when assessing their comparative weight in relation to the protection of human rights. Supported by holistic approach from different perspectives (socio-cultural, historical, etc.), the phenomenological and hermeneutic analysis allowed providing an in-depth understanding of various meanings of safety and security concepts. An overview of the existing linguistic peculiarities of the use of the terms ‘safety’ and ‘security’ with an emphasis on the importance of determining the context in which they are used as primary evidence of their meaning is followed by the analysis of the common features and differences between the concepts of safety and security that supplements the discourse on the dilemma of combining subjective and objective, relative and absolute perceptions of safety and security. The research from the view point of normative jurisprudence reveals the polysemy inherent in aviation safety and aviation security, especially in terms of the values they represent, suggesting the conclusion that legal definitions of ‘aviation safety’ and ‘aviation security’ should in part be treated as a sort of ad hoc definitions, which have to be developed (clarified) in each particular case. (shrink)

This paper presents an argument that certain AI safety measures, rather than mitigating existential risk, may instead exacerbate it. Under certain key assumptions - the inevitability of AI failure, the expected correlation between an AI system's power at the point of failure and the severity of the resulting harm, and the tendency of safety measures to enable AI systems to become more powerful before failing - safety efforts have negative expected utility. The paper examines three response strategies: (...) Optimism, Mitigation, and Holism. Each faces challenges stemming from intrinsic features of the AI safety landscape that we term Bottlenecking, the Perfection Barrier, and Equilibrium Fluctuation. The surprising robustness of the argument forces a re-examination of core assumptions around AI safety and points to several avenues for further research. (shrink)

Big data technologies are entering the world of ageing computer systems running critical infrastructures. These innovations promise to afford rapid Internet connectivity, remote operations or predictive maintenance. As legacy critical infrastructures were traditionally disconnected from the Internet, the prospect of their modernisation necessitates an inquiry into cyber security and how it intersects with traditional engineering requirements like safety, reliability or resilience. Looking at how the adoption of big data technologies in critical infrastructures shapes understandings of risk management, we (...) focus on a specific case study from the cyber security governance: the EU Network and Information Systems Security Directive. We argue that the implementation of Network and Information Systems Security Directive is the first step in the integration of safety and security through novel risk management practices. Therefore, it is the move towards legitimising the modernisation of critical infrastructures. But we also show that security risk management practices cannot be directly transplanted from the safety realm, as cyber security is grounded in anticipation of the future adversarial behaviours rather than the history of equipment failure rates. Our analysis offers several postulates for the emerging research agenda on big data in complex engineering systems. Building on the conceptualisations of safety and security grounded in the materialist literature across Science and Technology Studies and Organisational Sociology, we call for a better understanding of the ‘making of’ technologies, standardisation processes and engineering knowledge in a quest to build safe and secure critical infrastructures. (shrink)

One objection to conventional AI ethics is that it slows innovation. This presentation responds by reconfiguring ethics as an innovation accelerator. The critical elements develop from a contrast between Stability AI’s Diffusion and OpenAI’s Dall-E. By analyzing the divergent values underlying their opposed strategies for development and deployment, five conceptions are identified as common to acceleration ethics. Uncertainty is understood as positive and encouraging, rather than discouraging. Innovation is conceived as intrinsically valuable, instead of worthwhile only as mediated by social (...) effects. AI problems are solved by more AI, not less. Permissions and restrictions governing AI emerge from a decentralized process, instead of a unified authority. The work of ethics is embedded in AI development and application, instead of functioning from outside. Together, these attitudes and practices remake ethics as provoking rather than restraining artificial intelligence. (shrink)

The advent of generative artificial intelligence and the widespread adoption of it in society engendered intensive debates about its ethical implications and risks. These risks often differ from those associated with traditional discriminative machine learning. To synthesize the recent discourse and map its normative concepts, we conducted a scoping review on the ethics of generative artificial intelligence, including especially large language models and text-to-image models. Our analysis provides a taxonomy of 378 normative issues in 19 topic areas and ranks them (...) according to their prevalence in the literature. The study offers a comprehensive overview for scholars, practitioners, or policymakers, condensing the ethical debates surrounding fairness, safety, harmful content, hallucinations, privacy, interaction risks, security, alignment, societal impacts, and others. We discuss the results, evaluate imbalances in the literature, and explore unsubstantiated risk scenarios. (shrink)

After 50 years, the fields of artificial intelligence and robotics capture the imagination of the general public while, at the same time, engendering a great deal of fear and skepticism. Isaac Asimov recognized this deep-seated misconception of technology and created the Three Laws of Robotics. The first part of this paper examines the underlying fear of intelligent robots, revisits Asimov’s response, and reports on some current opinions on the use of the Three Laws by practitioners. Finally, an argument against robotic (...) rebellion is made along with a call for personal responsibility and suggestions for implementing safety constraints in intelligent robots. (shrink)

Decisions in security contexts, including armed conflict, law enforcement, and disaster relief, often need to be taken under circumstances of limited information, stress, and time pressure. Since AI systems are capable of providing a certain amount of relief in such contexts, such systems will become increasingly important, be it as decision-support or decision-making systems. However, given that human life may be at stake in such situations, moral responsibility for such decisions should remain with humans. Hence the idea of “meaningful (...) human control” of intelligent systems. In this opinion paper, we outline generic configurations of control of AI and we present an alternative to human control of AI, namely the inverse idea of having AI control humans, and we discuss the normative consequences of this alternative. (shrink)

In artificial intelligence (AI), responses generated by machine-learning models (most often large language models) may be unfactual information presented as a fact. For example, a chatbot might state that the Mona Lisa was painted in 1815. Such phenomenon is called AI hallucinations, seeking inspiration from human psychology, with a great difference of AI ones being connected to unjustified beliefs (that is, AI “beliefs”) rather than perceptual failures). -/- AI hallucinations may have their source in the data itself, that is, the (...) source content, or in the training procedure, i.e. the way the knowledge was encoded in the model’s parameters, so that errors in encoding and decoding textual and non-textual representations can cause hallucinations. In this paper, we will observe how such errors come to life and how they might be mitigated. For this purpose, we will analyze the usability of justification logics, to behave as a proof checker for validating the correctness of large language models’ (LLM) responses. Justification logic was developed by S. Artemov, and later on mostly by Artemov and M. Fitting, deriving its main idea from the logic of proofs (LP): knowledge and belief modalities are seen as justification terms, i.e. t:X stands for t is a (proper) justification for X. Justification logic originated from attempts to create semantics for intuitionistic logic where proofs were the most proper justifications, but in further development, justification logic could be applied to different kinds of justifications). With the recent attempts to mitigate incorrect LLM responses, we will analyze various guardrails that are currently used for LLM responses, and see how the logic of justification may provide its benefits as an AI safety layer against false data. (shrink)

Public consumption of artificial intelligence (AI) technologies has been rarely investigated from the perspective of data surveillance and security. We show that the technology acceptance model, when properly modified with security and surveillance fears about AI, builds an insight on how individuals begin to use, accept, or evaluate AI and its automated decisions. We conducted two studies, and found positive roles of perceived ease of use (PEOU) and perceived usefulness (PU). AI security concern, however, negatively affected PEOU (...) and PU, resulting in less acceptance of AI—(1) use, (2) preference, and (3) participation. AI surveillance concern also had negative effects on the credibility of AI and its recommendations. We integrated extant literature on socio-demographic differences, providing an insight on how AI acceptance is based on one’s rationality regarding (1) technological risks (security/surveillance) and (2) benefits (PEOU/PU) as well as other contextual factors of socio-demographics. (shrink)

To realize the coordinated and sustainable development of hydropower projects and regional society, comprehensively evaluating hydropower projects’ influence is critical. Usually, hydropower project development has an impact on environmental geology and social and regional cultural development. Based on comprehensive consideration of complicated geological conditions, fragile ecological environment, resettlement of reservoir area, and other factors of future hydropower development in each country, we have constructed a comprehensive evaluation index system of hydropower projects, including 4 first-level indicators of social economy, environment, (...) class='Hi'>safety, and fairness, which contain 26 second-level indicators. To solve the problem that existing models cannot evaluate dynamic nonlinear optimization, a projection pursuit model is constructed by using rough set reduction theory to simplify the index. Then, an accelerated genetic algorithm based on real number coding is used to solve the model and empirical study is carried out with the Y hydropower station as a sample. The evaluation results show that the evaluation index system and assessment model constructed in our paper effectively reduce the subjectivity of index weight. Applying our model to the social impact assessment of related international hydropower projects can not only comprehensively analyze the social impact of hydropower projects but also identify important social influencing factors and effectively analyze the social impact level of each dimension. Furthermore, SIA assessment can be conducive to project decision-making, avoiding social risks and social stability. (shrink)

AI companies are racing to create artificial general intelligence, or “AGI.” If they succeed, the result will be human-level AI systems that can independently pursue high-level goals by formulating and executing long-term plans in the real world. Leading AI researchers agree that some of these systems will likely be “misaligned”–pursuing goals that humans do not desire. This goal mismatch will put misaligned AIs and humans into strategic competition with one another. As with present-day strategic competition between nations with incompatible goals, (...) the result could be violent and catastrophic conflict. Existing legal institutions are unprepared for the AGI world. New foundations for AGI governance are needed, and the time to begin laying them is now, before the critical moment arrives. -/- This Article begins to lay those new legal foundations. It is the first to think systematically about the dynamics of strategic competition between humans and misaligned AGI. The Article begins by showing, using formal game-theoretic models, that, by default, humans and AIs will be trapped in a prisoner’s dilemma. Both parties’ dominant strategy will be to permanently disempower or destroy the other, even though the costs of such conflict would be high. -/- The Article then argues that a surprising legal intervention could transform the game theoretic equilibrium and avoid conflict: AI rights. Not just any AI rights would promote human safety. Granting AIs the right not to be needlessly harmed–as humans have granted to certain non-human animals–would, for example, have little effect. Instead, to promote human safety, AIs should be given those basic private law rights–to make contracts, hold property, and bring tort claims–that law already extends to non-human corporations. Granting AIs these economic rights would enable long-run, small-scale, mutually-beneficial transactions between humans and AIs. This would, we show, facilitate a peaceful strategic equilibrium between humans and AIs for the same reasons economic interdependence tends to promote peace in international relations. Namely, the gains from trade far exceed those from war. Throughout, we argue that human safety, rather than AI welfare, provides the right framework for developing AI rights. This Article explores both the promise and the limits of AI rights as a legal tool for promoting human safety in an AGI world. (shrink)

Radio Frequency Identification (RFID) is quickly growing in its applications. A variety of uses for the technology are beginning to be developed, including chips which can be used in identification cards, in individual items, and for human applications, allowing a chip to be embedded under the skin. Such chips could provide numerous benefits ranging from day-to-day convenience to the increased ability of the federal government to adequately ensure the safety of its citizens. However, there are also valid concerns about (...) the potential of this technology to infringe on privacy, creating fears of a surveillance society. These are concerns that must be addressed quickly, with sensitivity to individual interests and societal welfare, allowing humanity to reap the benefits of convenience and safety without paying an unacceptable price in the loss of privacy. (shrink)

In the last years, artificial intelligence (AI) safety gained international recognition in the light of heterogeneous safety-critical and ethical issues that risk overshadowing the broad beneficial impacts of AI. In this context, the implementation of AI observatory endeavors represents one key research direction. This paper motivates the need for an inherently _transdisciplinary_ AI observatory approach integrating diverse retrospective and counterfactual views. We delineate aims and limitations while providing hands-on-advice utilizing _concrete practical examples_. Distinguishing between unintentionally and intentionally triggered (...) AI risks with diverse socio-psycho-technological impacts, we exemplify a _retrospective descriptive analysis_ followed by a _retrospective counterfactual risk analysis_. Building on these AI observatory tools, we present near-term transdisciplinary guidelines for AI safety. As further contribution, we discuss _differentiated_ and tailored long-term directions through the lens of two disparate modern AI safety paradigms. For simplicity, we refer to these two different paradigms with the terms _artificial stupidity_ (AS) and _eternal creativity_ (EC) respectively. While both AS and EC acknowledge the need for a hybrid cognitive-affective approach to AI safety and overlap with regard to many short-term considerations, they differ fundamentally in the nature of multiple envisaged long-term solution patterns. By compiling relevant underlying _contradistinctions_, we aim to provide _future-oriented_ incentives for constructive dialectics in practical and theoretical AI safety research. (shrink)

ABSTRACTThis essay elaborates how an imbalanced reciprocity between inhabitants of places of relative safety and places of greater precarity results from pursuing security on the basis of a reactive fear of vulnerability. It analyzes a range of features that shape the complex forms that vulnerability takes with a particular focus on how the constitution of places as rhetorically and corporeally secure or not renders different groups of people secure and/or subject to heightened exposure to harm. This analysis suggests (...) that vulnerability is better conceived as a process than a quality, mediating between conceptions of vulnerability as a universal condition and as a highly specific empirical condition. Finally, by departing from the negative, reactive view of vulnerability that animates the supposition of the boundedness of selves and places, an alternative conception of security that neither equates it with invulnerability nor opposes it to vulnerability can be developed. (shrink)

What are termed the ‘collateral legal consequences’ (or CLCs) of criminal conviction have been defended in a variety of ways. The focus in this article is on efforts to justify the burdens and restrictions they involve as nonpenal measures designed to secure public safety. Zachary Hoskins' careful defense of such public‐safety CLCs is utilized as a point of departure. Although it is granted that such measures might be defensible, the many complications and problems of ensuring that they do (...) not amount to further legal punishment and are kept within reasonable bounds are explored. I argue that the state is unlikely to deploy such public safety measures wisely and with sufficient restraint. (shrink)

This book explores the revolutionary intersection of Generative AI (GenAI) and cybersecurity. It presents a comprehensive guide that intertwines theories and practices, aiming to equip cybersecurity professionals, CISOs, AI researchers, developers, architects and college students with an understanding of GenAI’s profound impacts on cybersecurity. The scope of the book ranges from the foundations of GenAI, including underlying principles, advanced architectures, and cutting-edge research, to specific aspects of GenAI security such as data security, model security, application-level security, (...) and the emerging fields of LLMOps and DevSecOps. It explores AI regulations around the globe, ethical considerations, the threat landscape, and privacy preservation. Further, it assesses the transformative potential of GenAI in reshaping the cybersecurity landscape, the ethical implications of using advanced models, and the innovative strategies required to secure GenAI applications. Lastly, the book presents an in-depth analysis of the security challenges and potential solutions specific to GenAI, and a forward-looking view of how it can redefine cybersecurity practices. By addressing these topics, it provides answers to questions on how to secure GenAI applications, as well as vital support with understanding and navigating the complex and ever-evolving regulatory environments, and how to build a resilient GenAI security program. The book offers actionable insights and hands-on resources for anyone engaged in the rapidly evolving world of GenAI and cybersecurity. (shrink)

Background The concept of “health security” is often used to motivate public health responses, yet the ethical values that underpin this concept remain largely unexamined. The recent Australian responses to COVID-19 serve as an important case study by which we can analyse the pre-existing literature to see what ethical values shaped, and continue to shape, Australia’s response. Methods We conducted a critical interpretive literature review of academic and grey literatures within key databases, resulting in 2,220 sources. After screening for (...) duplicates and relevance, we analysed ninety-six sources. Results First, risk and uncertainty are a leading focus, with a heavy concentration on risks to life and health. Second, free movement, safety, and security were recurringly emphasized, albeit narrowly focused upon the safety of the population. Third, legitimacy was a recurring theme, and it is here that discussions of “health security” figured highly. Conclusion Discussions of harm from government and associated official bodies fail to adequately distinguish between various senses of harm. Moreover, while the literature often discusses the balancing of rights, the steps involved in the weighing of these rights is rarely adequately explained and defended. We suggest that decision-makers should endeavour to clearly identify and defend the values undergirding their decisions in the public sphere. (shrink)

The rapid increase of industry-sponsored clinical research towards developing countries has led to potentially complex ethical issues to assess. There is scarce evidence about the perception of these participants about the ethical compliance, security, and protection. We sought to evaluate and contrast the awareness and perception of participants and non-participants of industry-sponsored research trials on ethical, safety, and protection topics. A Cases-control survey conducted at twelve research sites in México. Previous and current participants of ISRT as well as (...) non-participants with one of four chronic diseases, were asked to complete the survey which focused on ethical compliance and protection issues of ISRT, and the perception of participating in a trial. A total of 604 cases and 604 controls were surveyed. Cases significantly answered that ethics committees are aware of what is happening in studies, and that medical care of industry-sponsored research trials is better than their usual medical care. The same proportion of cases and controls thought patients must receive economical reimbursement for participating in a research study. The informed consent of the pharmaceutical clinical trial was fully read by 90.4% of the cases. Most cases were satisfied or very satisfied with their overall study participation. Previous and current participants of industry-sponsored research trials have a more positive attitude towards ethics committees, the quality of medical care of the research trials, and the main purpose of economical reimbursements, when compared to non-participants. (shrink)

Globally, academic integrity and misconduct is a continuing conundrum for education institutions. Whilst the online delivery of education is not new, the onset of Covid-19 with accompanying health and safety limitations and the consequential rapid transition to emergency online delivery of education has, for many, exacerbated the need to focus on emerging potential for new forms of student academic misconduct i.e., e-dishonesty. This paper presents the strategies developed by a higher education institution specializing in university courses for safety (...) and security professionals in the United Arab Emirates to address academic integrity during Covid-19 and beyond. The fundamental approach draws on lessons learnt from across the education community and focuses on engaging a comprehensive whole of Academy commitment to a high standard of academic integrity. The research investigated the outcomes of the academic integrity interventions in a total student population of 631. The early trending results of the strategies are encouraging, whilst monitoring of the ever-changing academic assessment landscape is pivotal to ensure these early trends are validated and sustained. The strategies developed and deployed by the Academy are replicable and offer a contribution to the demanding and complex challenge of establishing academic integrity within educational institutions across the world. (shrink)

There is a common problem in artificial intelligence (AI) and information security. In AI, an expert system needs to be able to justify and explain a decision to the user. In information security, experts need to be able to explain to the public why a system is secure. In both cases, an important goal of explanation is to acquire or maintain the users’ trust. In this paper, I investigate the relation between explanation and trust in the context of (...) computing science. This analysis draws on literature study and concept analysis, using elements from system theory as well as actor-network theory. I apply the conceptual framework to both AI and information security, and show the benefit of the framework for both fields by means of examples. The main focus is on expert systems (AI) and electronic voting systems (security). Finally, I discuss consequences of the analysis for ethics in terms of (un)informed consent and dissent, and the associated division of responsibilities. (shrink)

Retraction note: Rueda-Mahecha, Y. M., Martínez Rincón. J. A., Silva-Giraldo, C. A., & Martínez García. C. A. (2022). Analysis of the work and of the professional in safety and health at work. HUMAN REVIEW. International Humanities / Revista Internacional De Humanidades, 12(6), 2–12. https://doi.org/10.37467/revhuman.v11.4111 The Editorial Office of Eurasia Academic Publishing Group has retracted this article. An investigation carried out by our Research Integrity Department has found a group of articles, among which this one is found, that are not (...) within the thematic scope of the journal. We believe that the editorial process was manipulated and, furthermore, acceptance decisions were made under possibly inappropriate peer review. (shrink)

This article presents a conceptual investigation into the value impacts and relations of algorithms in the domain of justice and security. As a conceptual investigation, it represents one step in a value sensitive design based methodology. Here, we explicate and analyse the expression of values of accuracy, privacy, fairness and equality, property and ownership, and accountability and transparency in this context. We find that values are sensitive to disvalue if algorithms are designed, implemented or deployed inappropriately or without sufficient (...) consideration for their value impacts, potentially resulting in problems including discrimination and constrained autonomy. Furthermore, we outline a framework of conceptual relations of values indicated by our analysis, and potential value tensions in their implementation and deployment with a view towards supporting future research, and supporting the value sensitive design of algorithms in justice and security. (shrink)

This book is a collection of selected papers that were presented at the First International Conference of the Asia-Pacific Society for Agricultural and Food Ethics (APSAFE 2013), which was held at Chulalongkorn University from November 28 - 30, 2013. The papers are interdisciplinary, containing insights into food security and food ethics from a variety of perspectives, including, but not limited to, philosophy, sociology, law, sociology, economics, as well as the natural sciences. The theme of the conference was to consider (...) the interplay and balance between food security and food ethics as the world approaches the middle part of the twenty-first century. (shrink)

As AI technologies increase in capability and ubiquity, AI accidents are becoming more common. Based on normal accident theory, high reliability theory, and open systems theory, we create a framework for understanding the risks associated with AI applications. This framework is designed to direct attention to pertinent system properties without requiring unwieldy amounts of accuracy. In addition, we also use AI safety principles to quantify the unique risks of increased intelligence and human-like qualities in AI. Together, these two fields (...) give a more complete picture of the risks of contemporary AI. By focusing on system properties near accidents instead of seeking a root cause of accidents, we identify where attention should be paid to safety for current generation AI systems. (shrink)

This paper offers the first careful analysis of the possibility that AI and humanity will go to war. The paper focuses on the case of artificial general intelligence, AI with broadly human capabilities. The paper uses a bargaining model of war to apply standard causes of war to the special case of AI/human conflict. The paper argues that information failures and commitment problems are especially likely in AI/human conflict. Information failures would be driven by the difficulty of measuring AI capabilities, (...) by the uninterpretability of AI systems, and by differences in how AIs and humans analyze information. Commitment problems would make it difficult for AIs and humans to strike credible bargains. Commitment problems could arise from power shifts, rapid and discontinuous increases in AI capabilities. Commitment problems could also arise from missing focal points, where AIs and humans fail to effectively coordinate on policies to limit war. In the face of this heightened chance of war, the paper proposes several interventions. War can be made less likely by improving the measurement of AI capabilities, capping improvements in AI capabilities, designing AI systems to be similar to humans, and by allowing AI systems to participate in democratic political institutions. (shrink)

Artificial intelligence (AI) technologies in medicine are gradually changing biomedical research and patient care. High expectations and promises from novel AI applications aiming to positively impact society raise new ethical considerations for patients and caregivers who use these technologies. Based on a qualitative content analysis of semi-structured interviews and focus groups with healthcare professionals (HCPs), patients, and family members of patients with Parkinson’s Disease (PD), the present study investigates participant views on the comparative benefits and problems of using human versus (...) AI predictive computer vision health monitoring, as well as participants’ ethical concerns regarding these technologies. Participants presumed that AI monitoring would enhance information sharing and treatment, but voiced concerns about data ownership, data protection, commercialization of patient data, and privacy at home. They highlighted that privacy issues at home and data security issues are often linked and should be investigated together. Findings may help technologists, HCPs, and policymakers determine how to incorporate stakeholders’ intersecting but divergent concerns into developing and implementing AI PD monitoring tools. (shrink)

Advances in artificial intelligence and robotics stand to change many aspects of our lives, including our values. If trends continue as expected, many industries will undergo automation in the near future, calling into question whether we can still value the sense of identity and security our occupations once provided us with. Likewise, the advent of social robots driven by AI, appears to be shifting the meaning of numerous, long-standing values associated with interpersonal relationships, like friendship. Furthermore, powerful actors’ and (...) institutions’ increasing reliance on AI to make decisions that may affect how people live their lives may have a significant impact on privacy while also raising issues about algorithmic transparency and human control. In this paper, building and expanding on previous works, we will look at how the deployment of Artificial Intelligence technology may lead to changes in identity, security, and other crucial values (such as friendship, fairness, and privacy). We will discuss what challenges we may face in the process, while critically reflecting on whether such changes may be desirable. Finally, drawing on a series of considerations underlying virtue ethics, we will formulate a set of preliminary suggestions, which—we hope—can be used to more carefully guide the future roll out of AI technologies for human flourishing; that is, for social and moral good. (shrink)

National Artificial Intelligence (AI) strategies articulate imaginaries of the integration of AI into society and envision the governing of AI research, development and applications accordingly. To integrate these central aspects of national AI strategies under one coherent perspective, this paper presented an analysis of Germany’s strategy ‘AI made in Germany’ through the conceptual lens of ordoliberal political rationality. The first part of the paper analyses how the guiding vision of a human-centric AI not only adheres to ethical and legal principles (...) consistent with Germany’s liberal democratic constitutional system but also addresses the risks and promises inherent to the ordoliberal problematization of freedom. Second, it is scrutinized how the strategy cultivates the fear of not achieving technological sovereignty in the AI sector. Thereby, it frames the global AI race as a race of competing (national) approaches to governing AI and articulates an ordoliberal approach to governing AI (the ‘third way’), according to which government has to operate between the twin dangers of governing too much and not governing enough. Third, the paper analyses how this ordoliberal proportionality of governing structures Germany’s Science Technology & Innovation Policy. It is shown that the corresponding risk-based approach of regulating AI constitutes a security apparatus as it produces an assessment of fears: weighting the fear of the failure to innovate with the fear of the ramifications of innovation. Finally, two lines of critical engagement based on this analysis are conducted. (shrink)

The American food system has produced both abundance and food insecurity, with production and consumption dealt with as separate issues. The new approach of community food security (CFS) seeks to re-link production and consumption, with the goal of ensuring both an adequate and accessible food supply in the present and the future. In its focus on consumption, CFS has prioritized the needs of low-income people; in its focus on production, it emphasizes local and regional food systems. These objectives are (...) not necessarily compatible and may even be contradictory. This article describes the approach of community food security and raises some questions about how the movement can meet its goals of simultaneously meeting the food needs of low-income people and developing local food systems. It explores the conceptual and political promise and pitfalls of local, community-based approaches to food security and examines alternative economic strategies such as urban agriculture and community-supported agriculture. It concludes that community food security efforts are important additions to, but not subsitutes for, a nonretractable governmental safety net that protects against food insecurity. (shrink)

With the introduction of artificial intelligence (AI) to healthcare, there is also a need for professional guidance to support its use. New (2022) reports from National Health Service AI Lab & Health Education England focus on healthcare workers’ understanding and confidence in AI clinical decision support systems (AI-CDDSs), and are concerned with developing trust in, and the trustworthiness of these systems. While they offer guidance to aid developers and purchasers of such systems, they offer little specific guidance for the clinical (...) users who will be required to use them in patient care. This paper argues that clinical, professional and reputational safety will be risked if this deficit of professional guidance for clinical users of AI-CDDSs is not redressed. We argue it is not enough to develop training for clinical users without first establishing professional guidance regarding the rights and expectations of clinical users. We conclude with a call to action for clinical regulators: to unite to draft guidance for users of AI-CDDS that helps manage clinical, professional and reputational risks. We further suggest that this exercise offers an opportunity to address fundamental issues in the use of AI-CDDSs; regarding, for example, the fair burden of responsibility for outcomes. (shrink)

The purpose of this research is to explore the acceptance of social robots as companions. Understanding what affects the acceptance of humanoid companions may give society tools that will help people overcome loneliness throughout pandemics, such as COVID-19 and beyond. Based on regulatory focus theory, it is proposed that there is a relationship between goal-directed motivation and acceptance of robots as companions. The theory of regulatory focus posits that goal-directed behavior is regulated by two motivational systems—promotion and prevention. People with (...) a promotion focus are concerned about accomplishments, are sensitive to the presence and absence of positive outcomes (gains/non-gains), and have a strategic preference for eager means of goal-pursuit. People with a prevention focus are concerned about security and safety, are sensitive to the absence and presence of negative outcomes (non-losses/losses), and have a strategic preference for vigilant means. Two studies support the notion of a relationship between acceptance of robots as companions and regulatory focus. In Study 1, chronic promotion focus was associated with acceptance of robots, and this association was mediated by loneliness. The weaker the promotion focus, the stronger was the sense of loneliness, and thus the higher was the acceptance of the robots. In Study 2, a situationally induced regulatory focus moderated the association between acceptance of robots and COVID-19 perceived severity. The higher the perceived severity of the disease, the higher was the willingness to accept the robots, and the effect was stronger for an induced prevention (vs. promotion) focus. Models of acceptance of robots are presented. Implications for well-being are discussed. (shrink)

What is the relationship between taxation and public safety? Contrary to studies suggesting that personal victimization and heightened perceptions of insecurity increase pro-social attitudes and support for state intervention in the form of greater taxation, this article argues that such concerns decrease willingness to pay taxes to address public safety. It estimates what citizens are willing to pay to reduce crime, using an original representative survey conducted in Mexico and relying on the contingent valuation method to assess the (...) value of nonmarket goods. Attitudes toward taxation are found to respond to subjective, sociotropic assessments of public safety rather than to actual risk or occurrences of individual victimization. These findings counter the conventional wisdom that demand for personal security enables greater extraction, a central proposition in classic accounts of state building. Showing that willingness to accept heavier taxation may be weakest among those who perceive the gravest need for security, the study adds precision to theories of fiscal exchange. (shrink)

In many countries, such as Canada, the USA, England, and Australia, to graduate from a regulated profession such as nursing, students must complete a set of work‐integrated learning (WIL) hours and demonstrate their ability to safely perform physical skills and apply knowledge in relation to professional standards. For a disabled nursing student (DNS) undergoing training in higher education institutions (HEI), securing proper accommodations to participate effectively in WIL experiences has been difficult due to concerns related to risks to self and (...) patient safety. This study used critical discourse analysis to investigate the framing of risk and safety in association with providing DNS with accommodation in WIL. Our data were collected from an intensive codesign (group‐based discussion) session with participants (n = 16), including clinicians and DNS, from four institutions (two WIL‐sites and two HEI organizations). Using an iterative thematic approach based on Foucauldian framework, our analysis revealed three ways in which health professionals discursively framed risk and safety: (a) beliefs that a lack of disclosure by disabled students decreases patient safety and indicates poor self‐reflection, (b) concerns that accommodating students poses a risk to institutions offering WIL experiences and to the relationships between HEI and institutions offering WIL‐sites, and (c) a framing which challenges the dominant discourse by thinking about safety and risk more expansively. Our findings suggest the first two of these framings are ableist and function to enact barriers to access for DNSs in WIL, whereas the third framing serves the goal of inclusion. Recommendations to address the current ableist discourse within the Canadian nursing context are provided, which may also be applicable across other regulated health professions. (shrink)

This chapter argues that dual-use emerging technologies are distributing unprecedented offensive capabilities to nonstate actors. To counteract this trend, some scholars have proposed that states become a little “less liberal” by implementing large-scale surveillance policies to monitor the actions of citizens. This is problematic, though, because the distribution of offensive capabilities is also undermining states’ capacity to enforce the rule of law. I will suggest that the only plausible escape from this conundrum, at least from our present vantage point, is (...) the creation of a “supersingleton” run by a friendly superintelligence, founded upon a “post-singularity social contract.” In making this argument, the present chapter offers a novel reason for prioritizing the “control problem,” i.e., the problem of ensuring that a greaterthan-human-level AI will positively enhance human well-being. (shrink)

Artificial Intelligence is becoming widespread and as we continue ask ‘can we implement this’ we neglect to ask ‘should we implement this’. There are various frameworks and conceptual journeys one should take to ensure a robust AI product; context is one of the vital parts of this. AI is now expected to make decisions, from deciding who gets a credit card to cancer diagnosis. These decisions affect most, if not all, of society. As developers if we do not understand or (...) use fundamental modelling principles then we can cause real harm to society. Recently more serious effects of AI have been observed. Dehumanisation is the human reaction to overused anthropomorphism and lack of social contact caused by excessive interaction with, or addiction to, technology. This can cause humans to devalue technology and to devalue other humans. This is a contradiction of the use of ‘social robots’ and ‘chatbots’, indicating that the negative effects of this technology would outweigh any perceived positive effects. Also, within cyberspace, anthropomorphism and similar techniques based on deep philosophical principles can, and are, being used to alter the behaviour of humans. These techniques are used to manipulate human behaviours at a basic level in the human mind. As these types of techniques are becoming more widespread, it is clear that we are entering unchartered territory that holds a vast array of consequences for society. (shrink)

Foundation models such as GPT-4 are fine-tuned to avoid unsafe or otherwise problematic behavior, such as helping to commit crimes or producing racist text. One approach to fine-tuning, called reinforcement learning from human feedback, learns from humans' expressed preferences over multiple outputs. Another approach is constitutional AI, in which the input from humans is a list of high-level principles. But how do we deal with potentially diverging input from humans? How can we aggregate the input into consistent data about "collective" (...) preferences or otherwise use it to make collective choices about model behavior? In this paper, we argue that the field of social choice is well positioned to address these questions, and we discuss ways forward for this agenda, drawing on discussions in a recent workshop on Social Choice for AI Ethics and Safety held in Berkeley, CA, USA in December 2023. (shrink)

Machine ethics and robot rights are quickly becoming hot topics in artificial intelligence and robotics communities. We will argue that attempts to attribute moral agency and assign rights to all intelligent machines are misguided, whether applied to infrahuman or superhuman AIs, as are proposals to limit the negative effects of AIs by constraining their behavior. As an alternative, we propose a new science of safety engineering for intelligent artificial agents based on maximizing for what humans value. In particular, we (...) challenge the scientific community to develop intelligent systems that have human-friendly values that they provably retain, even under recursive self-improvement. (shrink)

This paper considers the ethical risks and opportunities presented by generalist medical artificial intelligence (GMAI), a kind of dynamic, multimodal AI proposed by Moor et al. (2023) for use in health care. The research objective is to apply widely accepted principles of biomedical ethics to analyze the possible consequences of GMAI, while emphasizing the distinctions between GMAI and current-generation, task-specific medical AI. The principles of autonomy and health equity in particular provide useful guidance for the ethical risks and opportunities of (...) novel AI systems in health care. The ethics of two applications of GMAI are examined: enabling decision aids that inform and educate patients about certain treatments and conditions, and expanding AI-driven diagnosis and treatment recommendation. Emphasis is placed on the potential of GMAI to improve shared decision-making between patients and providers, which supports patient autonomy. Another focus is on health equity, or the reduction of health and access disparities facing underserved populations. Although GMAI presents opportunities to improve patient autonomy, health literacy, and health equity, premature or inadequately regulated adoption of GMAI has the potential to compromise both health equity and patient autonomy. On the other hand, there are significant risks to health equity and autonomy that may arise from not adopting GMAI that has been thoroughly validated and tested. A careful balancing of these risks and benefits will be required to secure the best ethical outcome, if GMAI is ever employed at scale. (shrink)

We propose developing AIs whose only final goal is being shut down. We argue that this approach to AI safety has three benefits: (i) it could potentially be implemented in reinforcement learning, (ii) it avoids some dangerous instrumental convergence dynamics, and (iii) it creates trip wires for monitoring dangerous capabilities. We also argue that the proposal can overcome a key challenge raised by Soares et al. (2015), that shutdown-seeking AIs will manipulate humans into shutting them down. We conclude by (...) comparing our approach with Soares et al.'s corrigibility framework. (shrink)

The noticeable turn to technology in humanitarian action raises issues related to humanitarianism, sovereignty, as well as equality and access for at-risk populations in disaster zones or remote areas lacking sufficient healthcare services. On a technical level, practical challenges include heightened risks of data safety and security, and the potential malicious use of technology. On a societal level, humanitarian innovation may disrupt relations between different stakeholders, may widen inequality between those with access and those without, and may threaten (...) privacy, disproportionately affecting the vulnerable population. Drawing on the empirical findings of a case study of the 2015 Nepal earthquake, this paper presents an in-depth normative analysis to identify contextualised ethical considerations, and illuminate the wider debate about how technological innovation in the aid sector should be operationalised. In conclusion, on the normative level, a prudent attitude in adopting novel technology in the aid sector is required; while on the operational level, proposals for actionable ethical standards to guide and safeguard sector-wide innovation practices are needed. (shrink)

Roughly, empirical AI alignment research (AIA) is an area of AI research which investigates empirically how to design AI systems in line with human goals. This paper examines the role of non-epistemic values in AIA. It argues that: (1) Sciences differ in the degree to which values influence them. (2) AIA is strongly value-laden. (3) This influence of values is managed inappropriately and thus threatens AIA’s epistemic integrity and ethical beneficence. (4) AIA should strive to achieve value transparency, critical scrutiny (...) from inside and outside the discipline – involving the public –, and to empower actors without strong commercial interests. (shrink)