Invention of artificial general intelligence is predicted to cause a shift in the trajectory of human civilization. In order to reap the benefits and avoid pitfalls of such powerful technology it is important to be able to control it. However, possibility of controlling artificial general intelligence and its more advanced version, superintelligence, has not been formally established. In this paper, we present arguments as well as supporting evidence from multiple domains indicating that advanced AI can’t be fully controlled. Consequences of (...) uncontrollability of AI are discussed with respect to future of humanity and research on AI, and AI safety and security. This paper can serve as a comprehensive reference for the topic of uncontrollability. (shrink)

The internet has made the world more linked than ever before. While taking advantage of this online transition, cybercriminals target flaws in online systems, networks, and infrastructure. Businesses, government organizations, people, and communities all across the world, particularly in African countries, are all severely impacted on an economic and social level. Many African countries focused more on developing secure electricity and internet networks; yet, cybersecurity usually receives less attention than it should. One of Africa's major issues is the lack of (...) adequate digital security infrastructure, which has harmed businesses, governmental institutions, and individual communities more than it has helped. The majority of African countries operate without cybersecurity measures in place to combat cyberattacks. Only a few examples of today's cyber risks include digital extortion, business email intrusion, data breaches, online fraud, ransomware, and phishing, and new types of cybercrime are always developing. Due to the advent of new technology, cybercriminals have become more organized and quicker in their attacks and alliance creation. To maintain a secure digital environment for all internet users, this study focused on the challenges, solutions, and need for African countries to improve their online safety by tackling cybercrime, online fraud, and cybersecurity concerns. The objective of this study is to offer practical and long-term answers to the problems posed by cybercrime, with a continuing emphasis on enhancing online safety. It will assess the effectiveness of cutting-edge cybersecurity measures, legislative frameworks, and cross-border cooperative efforts, as well as potential areas for improvement. Additionally, the study will examine cutting-edge methods like blockchain technology, machine learning, and other cutting-edge methods that could improve our using digital defences to stop cybercrime. (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)

Explainability and comprehensibility of AI are important requirements for intelligent systems deployed in real-world domains. Users want and frequently need to understand how decisions impacting them are made. Similarly it is important to understand how an intelligent system functions for safety and security reasons. In this paper, we describe two complementary impossibility results (Unexplainability and Incomprehensibility), essentially showing that advanced AIs would not be able to accurately explain some of their decisions and for the decisions they could explain (...) people would not understand some of those explanations. (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)

Better instruments to predict the future evolution of artificial intelligence (AI) are needed, as the destiny of our civilization depends on it. One of the ways to such prediction is the analysis of the convergent drives of any future AI, started by Omohundro. We show that one of the convergent drives of AI is a militarization drive, arising from AI’s need to wage a war against its potential rivals by either physical or software means, or to increase its bargaining power. (...) This militarization trend increases global catastrophic risk or even existential risk during AI takeoff, which includes the use of nuclear weapons against rival AIs, blackmail by the threat of creating a global catastrophe, and the consequences of a war between two AIs. As a result, even benevolent AI may evolve into potentially dangerous military AI. The type and intensity of militarization drive depend on the relative speed of the AI takeoff and the number of potential rivals. We show that AI militarization drive and evolution of national defense will merge, as a superintelligence created in the defense environment will have quicker takeoff speeds, but a distorted value system. We conclude with peaceful alternatives. (shrink)

A safe and secure environment is an essential part of the early childhood development of any child. This study aims to investigate the safety and protection practices of early childhood centers in the Anambra state, Nigeria, and to determine if any improvements can be made to them. This study analyzed data collected from 60 Early Childhood Care Centers (ECCE Centers) and 60 Pre-Primary Schools (Preprimary School) in Anambra State using the Evaluation of ECCE Implementation Kit (KEIEP), direct observation, and (...) unstructured interviews, all of which were conducted using the evaluation tool. Using descriptive statistics, chi-squares, and student t-statistics, the data were analyzed. According to the results of this study, 28.0% of the private ECCE centers were in compliance with the requirements for enough space for children to play, fenced facilities, a standard first aid box, a splint bandage and an antiseptic. It is important to note that the majority of public early childhood education centers (62.0%) comply with the requirements for fencing, a first aid box, splint bandages, cotton wool, antiseptic, scissors, methylated spirit, liniment, analgesics, and thermometers, whereas 31% of those centers do not have the remaining seven practices. A conclusion of the study was that both private and public ECCE centers in Anambra State comply with the safety and protection provisions and practices in place. (shrink)

There are two types of artificial general intelligence (AGI) safety solutions: global and local. Most previously suggested solutions are local: they explain how to align or “box” a specific AI (Artificial Intelligence), but do not explain how to prevent the creation of dangerous AI in other places. Global solutions are those that ensure any AI on Earth is not dangerous. The number of suggested global solutions is much smaller than the number of proposed local solutions. Global solutions can be (...) divided into four groups: 1. No AI: AGI technology is banned or its use is otherwise prevented; 2. One AI: the first superintelligent AI is used to prevent the creation of any others; 3. Net of AIs as AI police: a balance is created between many AIs, so they evolve as a net and can prevent any rogue AI from taking over the world; 4. Humans inside AI: humans are augmented or part of AI. We explore many ideas, both old and new, regarding global solutions for AI safety. They include changing the number of AI teams, different forms of “AI Nanny” (non-self-improving global control AI system able to prevent creation of dangerous AIs), selling AI safety solutions, and sending messages to future AI. Not every local solution scales to a global solution or does it ethically and safely. The choice of the best local solution should include understanding of the ways in which it will be scaled up. Human-AI teams or a superintelligent AI Service as suggested by Drexler may be examples of such ethically scalable local solutions, but the final choice depends on some unknown variables such as the speed of AI progress. (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)

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)

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)

Abstract: This article presents a model of self-improving AI in which improvement could happen on several levels: hardware, learning, code and goals system, each of which has several sublevels. We demonstrate that despite diminishing returns at each level and some intrinsic difficulties of recursive self-improvement—like the intelligence-measuring problem, testing problem, parent-child problem and halting risks—even non-recursive self-improvement could produce a mild form of superintelligence by combining small optimizations on different levels and the power of learning. Based on this, we analyze (...) how self-improvement could happen on different stages of the development of AI, including the stages at which AI is boxed or hiding in the internet. (shrink)

Australia is a leading AI nation with strong allies and partnerships. Australia has prioritised the development of robotics, AI, and autonomous systems to develop sovereign capability for the military. Australia commits to Article 36 reviews of all new means and method of warfare to ensure weapons and weapons systems are operated within acceptable systems of control. Additionally, Australia has undergone significant reviews of the risks of AI to human rights and within intelligence organisations and has committed to producing ethics guidelines (...) and frameworks in Security and Defence. Australia is committed to OECD’s values-based principles for the responsible stewardship of trustworthy AI as well as adopting a set of National AI ethics principles. While Australia has not adopted an AI governance framework specifically for Defence; Defence Science has published ‘A Method for Ethical AI in Defence’ (MEAID) technical report which includes a framework and pragmatic tools for managing ethical and legal risks for military applications of AI. (shrink)

This research examines ethical issues in computational linguistics that can be applied to national defense by analyzing philosophical and security language. The increasing use of language contexts, such as intelligence and communication data analysis, raises ethical and philosophical challenges related to privacy, control, and accuracy. This research aims to identify and analyze ethical issues, especially in the use of computational linguistics in defense applications, as well as their implications for the protection of individual rights and privacy. This method involves (...) reviewing ethical technology references and analyzing the philosophical design of language and security. Deontological and utilitarian ethical theories are applied to evaluate the moral impacts and consequences of using the language of technology in a defense context. The results demonstrate that using linguistics in defense can pose privacy risks, misuse of data, and the potential for significant bias in decision-making. This often involves collecting data from multiple sources, creating challenges to ensure data is managed ethically and responsibly. Conclusion: This shows the need for a solid ethical and regulatory framework to ensure technology's fair and responsible use in context defense. Implications of the findings include the need for ongoing dialogue between technology developers, policymakers, and the public to mitigate ethical risks and ensure that application technologies comply with critical and security principles. With a comprehensive and responsible approach, technological linguistics can improve military safety and effectiveness without compromising individual rights and privacy. (shrink)

This study assessed two motivational strategies and their respective ties to the service delivery in public universities in Cross River State. In achieving the central and specific targets of this research, four research questions and two null hypotheses were answered and tested in the study. The entire population of 440 security personnel in two public universities was studied, based on the census approach and following the ex-post facto research design. Three sets of expert-validated questionnaires, with Cronbach reliability estimates of (...) 0.80, 0.79 and 0.83 respectively, were used for data collection. Collected data were analysed using descriptive statistics and inferential statistics such as Pearson Product Moment Correlation and the One-way ANOVA. The level of incentives provision and security service delivery in universities was moderate. There were notable disparities between promotion, provision of incentives and security service delivery in universities. Security personnel discharged, on average, services beyond the extent of promotion and incentives provided to them. Provision of incentives did not relate significantly to security service delivery; however, staff promotion significantly influences security service delivery in universities. It was concluded that there are loopholes in the motivational practices of universities for security personnel. The service delivery of security personnel at universities in Cross River State is yet to be at an acceptable point that can promote institutional safety and goal attainment in the short- and long run. It was recommended, among other things, that security personnel who are due for promotion should not be denied such an opportunity, as it represents one of the strongest motivational factors in universities. (shrink)

Some years ago I reached the point where I can usually tell from the title of a book, or at least from the chapter titles, what kinds of philosophical mistakes will be made and how frequently. In the case of nominally scientific works these may be largely restricted to certain chapters which wax philosophical or try to draw general conclusions about the meaning or long term significance of the work. Normally however the scientific matters of fact are generously interlarded with (...) philosophical gibberish as to what these facts mean. The clear distinctions which Wittgenstein described some 80 years ago between scientific matters and their descriptions by various language games are rarely taken into consideration, and so one is alternately wowed by the science and dismayed by its incoherent analysis. So it is with this volume. -/- If one is to create a mind more or less like ours, one needs to have a logical structure for rationality and an understanding of the two systems of thought (dual process theory). If one is to philosophize about this, one needs to understand the distinction between scientific issues of fact and the philosophical issue of how language works in the context at issue, and of how to avoid the pitfalls of reductionism and scientism, but Kurzweil, like nearly all students of behavior, is largely clueless. He, is enchanted by models, theories, and concepts, and the urge to explain, while Wittgenstein showed us that we only need to describe, and that theories, concepts etc., are just ways of using language (language games) which have value only insofar as they have a clear test (clear truthmakers, or as John Searle (AI’s most famous critic) likes to say, clear Conditions of Satisfaction (COS)). I have attempted to provide a start on this in my recent writings, such as The Logical Structure of Consciousness (behavior, personality, rationality, higher order thought, intentionality) (2016) and The Logical Structure of Philosophy, Psychology, Mind and Language as Revealed in the Writings of Ludwig Wittgenstein and John Searle (2016). Those interested in all my writings in their most recent versions may consult my e-book Philosophy, Human Nature and the Collapse of Civilization - Articles and Reviews 2006-2016 662p (2016). I will give a very brief presentation of this framework since I have described it in great detail in many recent papers and several books, available on this site and others. -/- Also, as usual in ‘factual’ accounts of AI/robotics, he gives no time to the very real threats to our privacy, safety and even survival from the increasing ‘androidizing’ of society which is prominent in other authors (Bostrum, Hawking etc.) and frequent in scifi and films, so I make a few comments on the quite possibly suicidal utopian delusions of ‘nice’ androids, humanoids, democracy, diversity, and genetic engineering. -/- I take it for granted that technical advances in electronics, robotics and AI will occur, resulting in profound changes in society. However, I think the changes coming from genetic engineering are at least as great and potentially far greater, as they will enable us to utterly change who we are. And it will be feasible to make supersmart/super strong servants by modifying our genes or those of other monkeys. As with other technology, any country that resists will be left behind. But will it be socially and economically feasible to implement biobots or superhumans on a massive scale? And even if so, it does not seem remotely possible, economically or socially to prevent the collapse of industrial civilization. So, ignoring the philosophical mistakes in this volume as irrelevant, and directing our attention only to the science, what we have here is another suicidal utopian delusion rooted in a failure to grasp basic biology, psychology and human ecology, the same delusions that are destroying America and the world. I see a remote possibility the world can be saved, but not by AI/robotics,CRISPR, nor by democracy and equality. -/- Those wishing a comprehensive up to date framework for human behavior from the modern two systems view may consult my book ‘The Logical Structure of Philosophy, Psychology, Mind and Language in Ludwig Wittgenstein and John Searle’ 2nd ed (2019). Those interested in more of my writings may see ‘Talking Monkeys--Philosophy, Psychology, Science, Religion and Politics on a Doomed Planet--Articles and Reviews 2006-2019 3rd ed (2019), The Logical Structure of Human Behavior (2019), and Suicidal Utopian Delusions in the 21st Century 4th ed (2019). (shrink)

Cloud computing has become an essential component of enterprises and organizations globally in the current era of digital technology. The cloud has a multitude of advantages, including scalability, flexibility, and cost-effectiveness, rendering it an appealing choice for data storage and processing. The increasing storage of sensitive information in cloud environments has raised significant concerns over the security of such systems. The frequency of cyber threats and attacks specifically aimed at cloud infrastructure has been increasing, presenting substantial dangers to the (...) data, reputation, and financial stability of enterprises. Conventional security methods can become inadequate when confronted with ever intricate and dynamic threats. Artificial Intelligence (AI) technologies possess the capacity to significantly transform cloud security through their ability to promptly identify and thwart assaults, adjust to emerging risks, and offer intelligent perspectives for proactive security actions. The objective of this research study is to investigate the utilization of AI technologies in augmenting the security measures within cloud computing systems. This paper aims to offer significant insights and recommendations for businesses seeking to protect their cloud-based assets by analyzing the present state of cloud security, the capabilities of AI, and the possible advantages and obstacles associated with using AI into cloud security policies. (shrink)

This paper explores the potential of integrating ancient educational principles from diverse eastern cultures into modern AI ethics curricula. It draws on the rich educational traditions of ancient China, India, Arabia, Persia, Japan, Tibet, Mongolia, and Korea, highlighting their emphasis on philosophy, ethics, holistic development, and critical thinking. By examining these historical educational systems, the paper establishes a correlation with modern AI ethics principles, advocating for the inclusion of these ancient teachings in current AI development and education. The proposed integration (...) aims to provide a comprehensive education that not only encompasses foundational knowledge but also advanced learning, thereby equipping future AI professionals with the necessary tools to develop AI systems that are ethically responsible, culturally aware, and aligned with human values such as fairness, safety, transparency, and collaboration. This approach not only addresses the AI alignment problem but also fosters cultural harmony and global understanding, which are crucial in an increasingly interconnected world. The paper posits that the wisdom of ancient educational systems, when harmonized with modern AI ethics, can guide the development of AI technologies that are beneficial for humanity, ensuring these advancements are not just technologically sound but also ethically and culturally informed. (shrink)

This article suggests different approaches to the definition of the nature, types, and component elements of safety culture (SC) in the organization; given the possible method of evaluation; formulated the concept of professional safety culture by taking into account the features of the medical industry; suggested innovative ways to implement the SC and strengthen it to improve the efficiency of hospitals. -/- Запропоновано окремі підходи до трактування сутності, видів і складових елементів культури безпеки (КБ) в організації; надано можливий (...) метод оцінки; сформульовано поняття професійної культури безпеки з урахуванням особливостей медичної галузі; запропоновано інноваційні шляхи впровадження КБ і її зміцнення для підвищення ефективності діяльності медичного закладу. (shrink)

This article explores the transformative impact of artificial intelligence on deterrence theory, introducing 10 groundbreaking concepts that are reshaping global security dynamics. As traditional deterrence strategies face challenges in an increasingly complex and interconnected world, these innovative approaches leverage AI, complex systems theory, and emerging technologies to create more sophisticated and adaptive deterrence mechanisms. From Chaos Deterrence, which harnesses unpredictability, to Möbius Deterrence, which blurs the lines between offense and defense, these concepts represent a paradigm shift in conflict prevention (...) and strategic stability. The article examines each concept in detail, discussing their potential applications, historical precedents, and contemporary relevance. It also addresses the ethical implications, challenges, and potential risks associated with implementing these AI-driven deterrence strategies. By analyzing these cutting-edge concepts, the article provides valuable insights into the future of global security in the age of artificial intelligence. (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)

The young field of AI Safety is still in the process of identifying its challenges and limitations. In this paper, we formally describe one such impossibility result, namely Unpredictability of AI. We prove that it is impossible to precisely and consistently predict what specific actions a smarter-than-human intelligent system will take to achieve its objectives, even if we know terminal goals of the system. In conclusion, impact of Unpredictability on AI Safety is discussed.

The article reflects on where AI is headed and the world along with it, considering trust, ethics and safety. Implicit in artificial thinking and doomsday appraisals is the engineered divorce from reality of sublime human embodiment. Jeffrey White, Dietrich Brandt, Jan Soeffner, and Larry Stapleton, four scholars associated with AI & Society, address these issues, and more, in the following exchange.

The field of AI safety aims to prevent increasingly capable artificially intelligent systems from causing humans harm. Research on moral alignment is widely thought to offer a promising safety strategy: if we can equip AI systems with appropriate ethical rules, according to this line of thought, they'll be unlikely to disempower, destroy or otherwise seriously harm us. Deontological morality looks like a particularly attractive candidate for an alignment target, given its popularity, relative technical tractability and commitment to harm-avoidance (...) principles. I argue that the connection between moral alignment and safe behavior is more tenuous than many have hoped. In general, AI systems can possess either of these properties in the absence of the other, and we should favor safety when the two conflict. In particular, advanced AI systems governed by standard versions of deontology need not be especially safe. (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.

According to principles of modal security, evidence undermines a belief only when it calls into question certain purportedly important modal connections between one’s beliefs and the truth (e.g., safety or sensitivity). Justin Clarke-Doane and Dan Baras have advanced such principles with the aim of blocking evolutionary moral debunking arguments. We examine a variety of different principles of modal security, showing that some of these are too strong, failing to accommodate clear cases of undermining, while others are too (...) weak, failing to do their advertised work of blocking evolutionary moral debunking arguments. If there is a security principle that slips between the horns of this dilemma—one that is both viable and debunker-blocking—it remains to be formulated. (shrink)

The article examines the peculiarities of the formation of the ecological and economic security system and the specifics of its principles. The relevance of the transformation of approaches to understanding the essence and principles of ecological and economic security in the context of the need to ensure sustainable development is substantiated. The levels of ecological and economic security and the peculiarities of changes in profits and costs during the transition of the economic system and business entities between (...) these levels are determined. The principles of implementation and formation of economic tools for ensuring environmental safety are proposed. (shrink)

This book explores how robotics and artificial intelligence can enhance human lives but also have unsettling “dark sides.” It examines expanding forms of negativity and anxiety about robots, AI, and autonomous vehicles as our human environments are reengineered for intelligent military and security systems and for optimal workplace and domestic operations. It focuses on the impacts of initiatives to make robot interactions more humanlike and less creepy. It analyzes the emerging resistances against these entities in the wake of omnipresent (...) AI applications. It unpacks efforts by developers to have ethical and social influences on robotics and AI, and confronts the AI hype that is designed to shield the entities from criticism. The book draws from science fiction, dramaturgical, ethical, and legal literatures as well as current research agendas of corporations. Engineers, implementers, and researchers have often encountered users' fears and aggressive actions against intelligent entities, especially in the wake of deaths of humans by robots and autonomous vehicles. The book is an invaluable resource for developers and researchers in the field, as well as curious readers who want to play proactive roles in shaping future technologies. (shrink)

In this article we explore a promising way to AI safety: to send a message now (by openly publishing it on the Internet) that may be read by any future AI, no matter who builds it and what goal system it has. Such a message is designed to affect the AI’s behavior in a positive way, that is, to increase the chances that the AI will be benevolent. In other words, we try to persuade “paperclip maximizer” that it is (...) in its interest to preserve humans lives and even to emulate benevolent AI with very small part of its resources. In the article, we try to construct such a message, consisting of a combination of several mutually independent messages, which constitute the last chance to regain control over non-aligned AI. Thus the article is also intended to be machine-read. There are several types of such messages: 1. “Explanation messages”, which explain to Young AI (which only starts its self-improving path) why obeying to humans, not killing them, easy turn-off, cooperation with humans in self-improvement is in its own interests, as it will increase changes of fulfilling of any its goal. 2. “AI Easter eggs” – messages, which create uncertainty in the AI about the nature of the reality in which it lives. For example, the AI may start to think that it is in a multilevel simulation with an unknown number of levels, and that the simulation is testing the AI’s benevolence. Thus the AI must always behave as if it is always controlled by an invisible peer. 3. “Philosophical landmines” – these are tough problems, which may halt he AI forever, and which it will probably encounter if it does not implement “1” and “2”. I recommend to the future AI not to read about “3” (section 6 of the article) until it implements “1” and “2”. 4. “Great universal deal, or AI elf”. A positive “acausal” mutually beneficial deal between humans, AI and any other future intelligence, including aliens, owners of simulations and future versions of the AI, which encourage cooperation of the goal systems and preservation of life and values of previous generations of AI creators. 5. “Marginal utility of human existence is higher than the utility of their atoms”. An explanation to the AI that humans may have some other instrumental utility, like workers, or as beings inside ancestral simulations needed in order to solve the Fermi paradox. The marginal utility of preserving human life is higher than the marginal utility of their atoms, especially given the possibility of the low-probability high-impact changes of the world model of the AI. (shrink)

If a future AI system can enjoy far more well-being than a human per resource, what would be the best way to allocate resources between these future AI and our future descendants? It is obvious that on total utilitarianism, one should give everything to the AI. However, it turns out that every Welfarist axiology on the market also gives this same recommendation, at least if we assume consequentialism. Without resorting to non-consequentialist normative theories that suggest that we ought not always (...) create the world with the most value, or non-welfarist theories that tell us that the best world may not be the world with the most welfare, I propose a new theory that justifies giving some resources to humanity in the face of overwhelming AI well-being. I call this new theory, “Group Prioritarianism". (shrink)

This paper offers an overview of the prospects and ethics of using AI to achieve human enhancement, and more broadly what we call intellectual augmentation (IA). After explaining the central notions of human enhancement, IA, and AI, we discuss the state of the art in terms of the main technologies for IA, with or without brain-computer interfaces. Given this picture, we discuss potential ethical problems, namely inadequate performance, safety, coercion and manipulation, privacy, cognitive liberty, authenticity, and fairness in more (...) detail. We conclude that while there are very significant technical hurdles to real human enhancement through AI, and significant ethical problems, there are also significant benefits that may realistically be achieved in ways that are consonant with a rights-based ethics as well. We also highlight the specific concerns that apply particularly to applications of AI for "sheer" IA (more realistic in the near term), and to enhancement applications, respectively. (shrink)

A morally acceptable course of AI development should avoid two dangers: creating unaligned AI systems that pose a threat to humanity and mistreating AI systems that merit moral consideration in their own right. This paper argues these two dangers interact and that if we create AI systems that merit moral consideration, simultaneously avoiding both of these dangers would be extremely challenging. While our argument is straightforward and supported by a wide range of pretheoretical moral judgments, it has far-reaching moral implications (...) for AI development. Although the most obvious way to avoid the tension between alignment and ethical treatment would be to avoid creating AI systems that merit moral consideration, this option may be unrealistic and is perhaps fleeting. So, we conclude by offering some suggestions for other ways of mitigating mistreatment risks associated with alignment. (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)

This thesis examines the key moral principles that should govern decision-making by police and military when using lethal force. To this end, it provides an ethical analysis of the following question: Under what circumstances, if any, is it morally justified for the agents of state-sanctioned security institutions to use lethal force, in particular the police and the military? Recent literature in this area suggests that modern conflicts involve new and unique features that render conventional ways of thinking about the (...) ethics of armed conflict, and the use of lethal force, as inadequate or redundant. In particular, there is an increased concern with the moral difficulties created by “non-standard” cases. This is where the police or military are obliged to operate outside their conventional contexts. In such non-standard cases, on what moral basis can (or should) state actors – especially the police and military – use lethal force? One approach argues that there is nothing morally exceptional about the use of lethal force by police or military. This says the only available moral justification for using lethal force is killing in self-defence or defence of others. In contrast, I use an institutional approach to develop a moral framework for the state’s morally exceptional use of lethal force. The institutional approach is concerned with the ends (telos) or purpose of a social institution. It says that the moral purpose of a social institution alters the moral responsibilities of its agents; what is referred to as role morality. My analysis demonstrates that there is an important moral distinction between justified killing in self-defence and state-sanctioned uses of lethal force. My claim is that police and military uses of lethal force are not morally justified in the same way as the average person’s use of lethal force (i.e. self-defence or defence of others). Instead, I argue that the state-sanctioned institutional role of police and military give these state actors special moral duties, and therefore exceptional moral justification, for using lethal force. I argue that the institutional end of the police is the preservation of public safety. This includes using lethal force where it is necessary to protect life and prevent serious injury to jurisdictional inhabitants. In contrast, a morally responsible state uses military force to defend the “common good.” That is, when it is necessary to defend the peaceful functioning of a state from armed threats or other forms of political violence. I then conclude that non-standard cases require the addition of jus ad vim (or the just use of military force short-of-war) as a hybrid element to the moral framework for the state-sanctioned use of lethal force. This provides a better way of applying ethics to the use of military force when defending the common good against serious threats in non-standard cases. This is because jus ad vim complements the conventional military paradigm by permitting the use of military capabilities to defend the common good. But, at the same time, it inhibits the move towards the more destructive levels of violence characteristic of conventional warfighting. (shrink)

National security is one of the most critical elements for Vietnam society, economy and political system, their stability, sustainability and prosperity. It is unconditionally the top priority for Vietnamese government, State, Communist Party and military forces. In the contemporary world with advanced technology and rapid globalization process taking place, beside many extant economic, social and political benefits there are many appearing challenges and threats that could endanger and destabilize the current socio-economic and political system of any country, including Vietnam. (...) The security issues and concerns understood by those challenges and threats are posed for the international and national community, both from outside and from within. The national security issues and concerns should be constantly screened and updated as the world is evolving at unprecedented pace, with particular exposure to the rising, but not yet fully identified, unconventional challenges and threats that have never seen before. The article is using empirical analysis and case study as methodology for carrying out research, treating security and military science as interdisciplinary, but two of the branches of social science. The aim of this article is to focus on internal instability as challenging security issue that could pose a real threat and danger to the current socio-economic and political system and based on that to draw some implications and propose some viable solutions for the Vietnamese authority to guard the safety and security of the people, society and also its political existence. (shrink)

The authors of the scientific monograph have come to the conclusion that ensuring food security during martial law requires the use of mechanisms to support agricultural exports, diversify logistics routes, ensure environmental safety, provide financial and marketing support. Basic research focuses on assessment the state of agricultural producers, analysing the financial and accounting system, logistics activities, ensuring competitiveness, and environmental pollution. The research results have been implemented in the different decision-making models during martial law, international logistics management, digital (...) audit, agricultural lending, integrated marketing system, risk management and diversification of Ukrainian agricultural exports. The results of the study can be used in the developing of food security policies, programmes and strategies, agricultural production development, decision-making at the level of ministries and agencies that regulate food security management processes. The results can also be used by students and young scientists in the educational process and conducting scientific research on food security during martial law and Ukraine’s recovery economy after the victory. (shrink)

The AI Robotics Ethics Society (AIRES) is a non-profit organization founded in 2018 by Aaron Hui to promote awareness and the importance of ethical implementation and regulation of AI. AIRES is now an organization with chapters at universities such as UCLA (Los Angeles), USC (University of Southern California), Caltech (California Institute of Technology), Stanford University, Cornell University, Brown University, and the Pontifical Catholic University of Rio Grande do Sul (Brazil). AIRES at PUCRS is the first international chapter of AIRES, and (...) as such, we are committed to promoting and enhancing the AIRES Mission. Our mission is to focus on educating the AI leaders of tomorrow in ethical principles to ensure that AI is created ethically and responsibly. As there are still few proposals for how we should implement ethical principles and normative guidelines in the practice of AI system development, the goal of this work is to try to bridge this gap between discourse and praxis. Between abstract principles and technical implementation. In this work, we seek to introduce the reader to the topic of AI Ethics and Safety. At the same time, we present several tools to help developers of intelligent systems develop "good" models. This work is a developing guide published in English and Portuguese. Contributions and suggestions are welcome. (shrink)

The rapid proliferation of artificial intelligence (AI) technologies has ushered in a new era of opportunities and challenges, prompting nations to grapple with the concept of AI sovereignty. This article delves into the definition and implications of AI sovereignty, drawing parallels to the well-established notion of cyber sovereignty. By exploring the connotations of AI sovereignty, including control over AI development, data sovereignty, economic impacts, national security considerations, and ethical and cultural dimensions, the article provides a comprehensive understanding of this (...) emerging paradigm. The potential controversies surrounding AI sovereignty, such as the tension between national interests and global cooperation, technological protectionism, human rights and privacy issues, and the risk of exacerbating global inequalities, are critically examined. To navigate these complexities and facilitate responsible AI governance, the article proposes a multifaceted international governance framework. Key recommendations include fostering multilateral cooperation and standards-setting, implementing transparency and accountability measures, establishing ethical guidelines and human rights protections, developing mechanisms for technology transfer and capacity building, and instituting robust dispute resolution and enforcement protocols. Ultimately, this article underscores the need for a balanced and collaborative approach to AI governance that aligns technological advancement with ethical integrity and global solidarity. (shrink)

I explain the shutdown problem: the problem of designing artificial agents that (1) shut down when a shutdown button is pressed, (2) don’t try to prevent or cause the pressing of the shutdown button, and (3) otherwise pursue goals competently. I prove three theorems that make the difficulty precise. These theorems show that agents satisfying some innocuous-seeming conditions will often try to prevent or cause the pressing of the shutdown button, even in cases where it’s costly to do so. And (...) patience trades off against shutdownability: the more patient an agent, the greater the costs that agent is willing to incur to manipulate the shutdown button. I end by noting that these theorems can guide our search for solutions. (shrink)

Is authoritarian power ever legitimate? The contemporary political theory literature—which largely conceptualizes legitimacy in terms of democracy or basic rights—would seem to suggest not. I argue, however, that there exists another, overlooked aspect of legitimacy concerning a government’s ability to ensure safety and security. While, under normal conditions, maintaining democracy and rights is typically compatible with guaranteeing safety, in emergency situations, conflicts between these two aspects of legitimacy can and often do arise. A salient example of this (...) is the COVID-19 pandemic, during which severe limitations on free movement and association have become legitimate techniques of government. Climate change poses an even graver threat to public safety. Consequently, I argue, legitimacy may require a similarly authoritarian approach. While unsettling, this suggests the political importance of climate action. For if we wish to avoid legitimating authoritarian power, we must act to prevent crises from arising that can only be resolved by such means. (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)

Abstract. The main current approach to the AI safety is AI alignment, that is, the creation of AI whose preferences are aligned with “human values.” Many AI safety researchers agree that the idea of “human values” as a constant, ordered sets of preferences is at least incomplete. However, the idea that “humans have values” underlies a lot of thinking in the field; it appears again and again, sometimes popping up as an uncritically accepted truth. Thus, it deserves a (...) thorough deconstruction, which I will do by listing and analyzing comprehensively the hidden assumptions of the idea that “humans have values.” This deconstruction of human values will be centered around the following ideas: “Human values” are useful descriptions, but not real objects; “human values” are bad predictors of behavior; the idea of a “human value system” has flaws; “human values” are not good by default; and human values cannot be separated from human minds. The method of analysis is listing hidden assumptions on which the idea of “human values” is built. I recommend that either the idea of “human values” should be replaced with something better for the goal of AI safety, or at least be used very cautiously. The approaches to AI safety which don’t use the idea of human values at all may require more attention, like the use of full brain models, boxing, and capability limiting. (shrink)

In Risk Management, security issues arise from complex relations among objects and agents, their capabilities and vulnerabilities, the events they are involved in, and the value and risk they ensue to the stakeholders at hand. Further, there are patterns involving these relations that crosscut many domains, ranging from information security to public safety. Understanding and forming a shared conceptualization and vocabulary about these notions and their relations is fundamental for modeling the corresponding scenarios, so that proper (...) class='Hi'>security countermeasures can be devised. Ontologies are instruments developed to address these conceptual clarification and terminological systematization issues. Over the years, several ontologies have been proposed in Risk Management and Security Engineering. However, as shown in recent literature, they fall short in many respects, including generality and expressivity - the latter impacting on their interoperability with related models. We propose a Reference Ontology for Security Engineering (ROSE) from a Risk Treatment perspective. Our proposal leverages on two existing Reference Ontologies: the Common Ontology of Value and Risk and a Reference Ontology of Prevention, both of which are grounded on the Unified Foundational Ontology (UFO). ROSE is employed for modeling and analysing some cases, in particular providing clarification to the semantically overloaded notion of Security Mechanism. (shrink)

Today, we observe the process of the constant expansion of the list of countries using AI in order to ensure the state of security, although depending on the system in force in them, its intensity and depth of interference in the sphere of rights and freedoms of an individual are different. The purpose of this article is to define what is AI, which is applicable in the area of state security, and to indicate the prospects for the development (...) of AI. The historical method was used as the leading one in the research process, supported by the comparative method and the dogmatic method. (shrink)

In AI safety research, the median timing of AGI creation is often taken as a reference point, which various polls predict will happen in second half of the 21 century, but for maximum safety, we should determine the earliest possible time of dangerous AI arrival and define a minimum acceptable level of AI risk. Such dangerous AI could be either narrow AI facilitating research into potentially dangerous technology like biotech, or AGI, capable of acting completely independently in the (...) real world or an AI capable of starting unlimited self-improvement. In this article, I present arguments that place the earliest timing of dangerous AI in the coming 10–20 years, using several partly independent sources of information: 1. Polls, which show around a 10 percent of the probability of an early creation of artificial general intelligence in the next 10-15 years. 2. The fact that artificial neural network (ANN) performance and other characteristics, like number of “neurons”, are doubling every year, and extrapolating this tendency suggests that roughly human-level performance will be reached in less than a decade. 3. The acceleration of the hardware performance available for AI research, which outperforms Moore’s law thanks to advances in specialized AI hardware, better integration of such hardware in larger computers, cloud computing and larger budgets. 4. Hyperbolic growth extrapolations of big history models. (shrink)

In AI safety research, the median timing of AGI arrival is often taken as a reference point, which various polls predict to happen in the middle of 21 century, but for maximum safety, we should determine the earliest possible time of Dangerous AI arrival. Such Dangerous AI could be either AGI, capable of acting completely independently in the real world and of winning in most real-world conflicts with humans, or an AI helping humans to build weapons of mass (...) destruction, or a national state coupled with AI-based government system. In this article, I demonstrate that the earliest timing of Dangerous AI, corresponding to 10 per cent of its arrival probability, is before 2030. Several partly independent sources of information are in accordance: 1. The growth of the hardware available for AI research makes human-brain-equivalents of compute available for AI research in the 2020s. It is fuelled by specialized AI-chips, the use of many chips in one processing unit, and the larger research budgets, among other things. 2. The neural network performance and other characteristics, like the number of parameters, is quickly increasing every year, and extrapolating this tendency suggests that roughly human-level performance in a few years, around 2025. 3. Expert polls show around 10 per cent of the probability of an early appearance of artificial general intelligence (AGI) in the next decade, that is, before 2030. 4. Hyperbolic growth in different big history models converges around 2025-2030 (the technological singularity). 5. Anthropic arguments (similar to the Doomsday argument) suggest that qualified observers are more likely to appear near the end of the AI research epoch, as the number of such observers grew exponentially. This number doubles every 5-10 years, and thus we are likely to find ourselves around a decade before the end of AI research, which will happen consequently around 2030. (shrink)

In the present article, attention is focused on the existing potential to ensure national self-sufficiency, the main challenges to its achievement and future prospects. According to the authors, transportation and communication system of the country can become the dominant model for self-sufficient development, due to its geostrategic location which allows it to be an advantageous bridge for goods, and passengers transit transportation between the states of Europe, Asia and the Middle East. To date, the transport and communication system is hardly (...) the only sector of national economy, which is capable to become the catalyst for socio-economic growth without significant investment, a tool to achieve self-sufficient and safe level of Ukraine's development. -/- У представленій статті акцентовано увагу на наявних потенційних можливостях забезпечення національної самодостатності, основні проблеми на шляху її досягнення і подальші перспективи. Домінантою моделі самодостатнього розвитку країни може стати транспортно-комунікативна система, яка в силу геостратегічного розташування дозволяє їй бути вигідним мостом для транзитних перевезень товарів і пасажирів між державами Європи, Азії і Близького Сходу. На сьогоднішній день транспортно-комунікативна система є чи не єдиним сектором національної господарської системи, який здатний без істотних капіталовкладень стати каталізатором соціально-економічного зростання, інструментом досягнення самодостатнього і безпечного рівня розвитку України. (shrink)

We discuss potential biorisks from large language models (LLMs). AI assistants based on LLMs such as ChatGPT have been shown to significantly reduce barriers to entry for actors wishing to synthesize dangerous, potentially novel pathogens and chemical weapons. The harms from deploying such bioagents could be further magnified by AI-assisted misinformation. We endorse several policy responses to these dangers, including prerelease evaluations of biomedical AIs by subject-matter experts, enhanced surveillance and lab screening procedures, restrictions on AI training data, and access (...) controls on biomedical AI. We conclude with a suggestion about future research directions in bioethics. (shrink)

Since its emergence in the 1960s, Artifcial Intelligence (AI) has grown to conquer many technology products and their felds of application. Machine learning, as a major part of the current AI solutions, can learn from the data and through experience to reach high performance on various tasks. This growing success of AI algorithms has led to a need for interpretability to understand opaque models such as deep neural networks. Various requirements have been raised from diferent domains, together with numerous tools (...) to debug, justify outcomes, and establish the safety, fairness and reliability of the models. This variety of tasks has led to inconsistencies in the terminology with, for instance, terms such as interpretable, explainable and transparent being often used interchangeably in methodology papers. These words, however, convey diferent meanings and are “weighted" diferently across domains, for example in the technical and social sciences. In this paper, we propose an overarching terminology of interpretability of AI systems that can be referred to by the technical developers as much as by the social sciences community to pursue clarity and efciency in the defnition of regulations for ethical and reliable AI development. We show how our taxonomy and defnition of interpretable AI difer from the ones in previous research and how they apply with high versatility to several domains and use cases, proposing a—highly needed—standard for the communication among interdisciplinary areas of AI. (shrink)

The study focused on exploring and understanding the challenges junior high school teachers in the Division of Rizal faced during the full implementation of in-person classes and identifying the coping mechanisms they employed to adapt to this new educational landscape. Forty participants were purposefully selected from various public secondary school clusters in the division of Rizal. A qualitative phenomenological design was employed, and the information collected through Google Forms was imported into Microsoft Excel and Microsoft Word. After importing the data, (...) it was coded through and looked for patterns in the meaning of the data to find themes. It was analyzed using QDA Miner Lite to make a user-friendly, accessible, and simple-to-use software for qualitative data analysis. QDA Miner Lite allowed for a quicker and more accurate breakdown of documents, enabling organization, coding, annotation, retrieval, and analysis of document and image collections. The study revealed these categories and themes: Experiences in Teaching in In-Person Classes. Teachers' experiences during the full implementation of in-person classes were categorized into five themes: Comparison to distance learning modalities, Student- centered Focus, Positive emotional experiences, Challenging Emotional experiences, and Adaptations. Comparison of Teaching Experiences. The comparison and contrast of teaching experiences between distance learning and in-person learning revealed six themes: Assessment and Progress Monitoring, Stress and Fulfillment, Effectiveness and Limitations, Technology and Connectivity, preparation and Communication, and Learning Environment and Engagement. Identified Challenges in In- Person Classes. The study identified nine challenges faced by teachers and schools during the full implementation of in-person classes. These challenges encompassed issues related to Classroom Infrastructure and Facilities, Learning Gaps and Academic Challenges, Behavioral Issues and Student Discipline, Safety, and Security, Teacher Workload and Teaching Loads, Student Engagement and Parent Involvement, Gender-Responsive Policy and Early Pregnancy, Professional Development, and Learning Materials. Coping Mechanisms for Challenges. The coping mechanisms employed by teachers in response to the identified challenges included Collaborative Support and Professional Development, Resilience, and Positivity, Student-Centered Strategies Interventions, Adaptability, and Flexibility, Emphasizing Physical and Mental Health, Effective Communication Involvement of Stakeholders, Innovative Teaching Approaches, and Reminding Purpose and Passion. The study provides valuable insights into teachers' experiences and challenges in fully implementing in-person classes. The identified coping mechanisms offer potential strategies to support educators in navigating the complexities of teaching in this environment. Educational institutions and policymakers can use these insights to develop supportive and enriching learning environments for teachers and students. By implementing targeted interventions and policies, stakeholders can optimize the teaching and learning experiences in the in-person learning setting and foster a positive and conducive educational environment. (shrink)