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)

The application of modern technologies with artificial intelligence (AI) in all spheres of human life is growing exponentially alongside concern for its controllability. The lack of public, state, and international control over AI technologies creates large-scale risks of using such software and hardware that (un)intentionally harm humanity. The events of recent month and years, specifically regarding the Russian Federation’s war against its democratic neighbour Ukraine and other international conflicts of note, support the thesis that the uncontrolled use of AI, especially (...) in the military sphere, may lead to deliberate disregard for the moral standards of controlled AI or the spontaneous emergence of aggressive autonomous AI. The development of legal regulation for the use of technologies with AI is prolonged concerning the rapid development of these artefacts, which simultaneously cover all areas of public relations. Therefore, control over the creation and use of AI should be carried out not only by purely technical regulation (e.g., technical standards and conformance assessments, corporate and developer regulations, requirements enforced through industry-wide ethical codes); but also by comprehensive legislation and intergovernmental oversight bodies that codify and enforce specific changes in the rights and duties of legal persons. This article shall present the “Morality Problem” and “Intentionality Problem” of AI, and reflect upon various lacunae that arise when implementing AI for military purposes. (shrink)

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

The increasing complexity and ubiquity of autonomously operating artificially intelligent (AI) systems call for a robust theoretical reconceptualization of responsibility and control. The Meaningful Human Control (MHC) approach to the design and operation of AI systems provides such a framework. However, in its focus on accountability and minimizing harms, it neglects how we may flourish in interaction with such systems. In this chapter, I show how the MHC framework can be expanded to meet this challenge by drawing (...) on the ethics of carebots and embodied design. First, I examine how discussions about flourishing with carebots invite us to consider the extent to which we control our moral character Second, I argue that we can understand the cultivation of moral character in terms of embodied virtues arising from operating in particular ecologies. Third, I demonstrate how this analysis fruitfully informs the design of carebots as supporting reciprocity and empathy. (shrink)

The conceptual model of United Nations reform - "UN 3.0" includes the General Program of Action on UN Reform, consisting of two stages. The first stage for 2020-2025 envisages the transformation of the main organs of the UN - the General Assembly and the Security Council with measures to improve the effectiveness of the management system, address the "veto problem", problem of financing, improve staff work and administrative and financial control, strengthen UN media, improvement of work with the global civil (...) society. The General Assembly is converted into the General All-Parliamentary Assembly of the UN. In the structure of the Assembly, the Council for Law is being established, which coordinates the activities of UN structures in the field of law. To coordinate the activities of the UN in the field of human rights and civil society, ethical issues, the General all-parliamentary Assembly creates the Council on ethics, human rights and civil society and transforms the Committee on information into the Council on public information and communication with civil society. The structure of the Council includes all UN media. The reform of the UN Security Council is carried out in three sub-stages. At the 1st sub-stage (2020-2021) the Security Council is transformed into the Council of Existential Security (CES). The membership of the CES is increased to 25 member countries, of which five countries have the right of the unconditional (absolute, eternal) veto: Great Britain, France, China, Russian Federation, USA. The General All-Parliamentary Assembly elects 15 new permanent members of the Council of Existential Security with the right of the conditional (limited) veto: Argentina, Australia, Brazil, Canada, Egypt, Germany, India, Indonesia, Italy, Mexico, South Africa, Nigeria, Pakistan , Turkey, Japan (if they fulfill the mandatory restrictive conditions). At this sub-stage, the CES elects also five non-permanent members with the right of a conditional (limited) veto when they meet the mandatory restrictive conditions, with a rotation period of 2 years from geographical regions (or regional unions): Africa, Latin America and the Caribbean, Asia and the Pacific Ocean (2 places), Eastern Europe. On the second sub-stage (2022-2023), subject to the effective activity of the CES of the enlarged composition and compliance with mandatory restrictive conditions, new permanent members of the "Existential Security Council" are elected with the right of a conditional (limited) veto: Iran, Spain, Poland, Saudi Arabia. Members of the CES may be regional unions, whose member countries are not represented in the CES, but still have one vote with the right of a conditional (limited) veto. -/- Two essential levels of the veto: 1. Unconditional (absolute, eternal) veto is the historical right of veto of the five permanent members of the Council of Existential Security - Great Britain, China, Russia, USA, France; 2. Сonditional (limited) veto is the veto of other permanent and non-permanent members of the Council of Existential Security. The right of veto is a unique international school for the achievement of consensus, a school of high democracy for Humanity, a reliable guarantee of the viability of the UN structure. The Council for Existential Security centralises the management of the UN subsidiary bodies with the expansion of their security functions: the Military Staff Committee, the Counter-Terrorism Committee, the Committee for the Prevention of the Spread of Nuclear, Chemical and Biological Weapons, the Sanctions Committees and other committees. On the basis of the decision of the Council of Existential Security, the General All-Parliamentary Assembly creates permanent contingents of UN peacekeeping and counter-terrorism forces. In addition, two Centers are being created in the structure of the Council for Existential Security: the World Center for the Elimination of the Effects of Technogenic and Natural Disasters with branches on all continents and the World Center for the Analysis of Existential Risks and the Overall Security Strategy. The Center is developing the Programs of research and monitoring of global existential threats and risks. In order to increase the level of legitimacy and authority of the Secretary General of the United Nations, the Rules of procedure for elections to this post are changing. Each member country of the Council for Existential Security represents one of the most authoritative candidates for election to the post of Secretary General at the session of the General All-Parliamentary Assembly, with the possibility of nominating candidates from other countries, including those not members of the Council for Existential Security. Elections are held in two rounds during one day of the session of the Assembly. The Legal Committee of the UN General Assembly is developing a Program for the Reform of the Judicial System of the United Nations, which takes into account the proposals of the previous international discussion and determines the scope and terms of the reform of the courts. In accordance with the Program of Action on UN Reform for 2020-2025, reforms are under way in the structure of the Economic and Social Council. The central task of the reform is to strengthen the coordinating role of ECOSOC in the entire system of UN-related specialized agencies, funds and programs related to the Council. The key task of the UN reform is the solution of the financing problem. A unified "UN Open Budget "Solidarity XXI" is being created, including the financing of peacekeeping operations and other expenses. Each country, a member of the United Nations, lists in an established period, once a year, an Existential contribution - the Earth Tax. The Earth Tax for each UN member state is established on the basis of four scales of calculation: Scale I - for 5 permanent members of the Council of Existential Security, who have the right of absolute (absolute) veto; Scale II - for the permanent members of the SEB, who have the right to a conditional (limited) veto; Scale III - for non-permanent members of the SEB, who have the right to a conditional (limited) veto; Scale IV - for all other UN member countries. The program of action on UN reform includes a set of measures to ensure transparent work of the International Civil Service Commission with the involvement of the UN media. To strengthen control functions in the sphere of personnel policy, administrative and financial management, the General All-Parliamentary Assembly of the United Nations establishes the Permanent Commission on Ethics and Administrative and Financial Control. All members of the Commission, members of the Committees and auditors are independent in their activities from the leadership of the United Nations, its funds and programs. The General All-Parliamentary Assembly completes the first stage of the Program of Action on UN Reform in 2025 and, following an open discussion, introduces a single language of international communication - Esperanto and approves it as the official language of the United Nations. With a view to more effective work of the central UN governing bodies in the face of increasing existential threats and risks, reducing the current expenses for the maintenance of the central bodies of the UN, the Council for Existential Security and the General All-Parliamentary Assembly decide on the relocation of the UN headquarters to Iceland. The UN building complex in New York is transferred to preferential use of non-governmental organizations, which contribute to the implementation of the goals of the United Nations. At the second stage of the UN reform in the period 2026-2028, additional necessary transformations are being made in the UN system. At the end of the first stage of the reform, taking into account the reforms carried out by the main organs of the United Nations and the internal improvement of the work of all its structures, the United Nations Program of Action for the years 2026-2028 is being developed. (shrink)

Techno-ethics is the area in the philosophy of technology which deals with emerging robotic and digital AI technologies. In the last decade, a new techno-ethical challenge has emerged: Autonomous Weapon Systems (AWS), defensive and offensive (the article deals only with the latter). Such AI-operated lethal machines of various forms (aerial, marine, continental) raise substantial ethical concerns. Interestingly, the topic of AWS was almost not treated in Jewish law and its research. This article thus proposes an introductory (...) ethical-halakhic perspective on AWS, in the Israeli context. The article has seven sections. Section 1 defines AWS and the main ethical concerns it evokes, while providing elementary definitions and distinctions. §2 locates AWS within the realm of Jewish laws of war (hilkhot-ẓava), which recognize the right for self-defense, as well as the status of universally accepted moral norms. §3 unfolds pragmatic ethical premises of a humane techno-ethics, which are required for the identifying AWS as a moral question: I. Relationality; II. Technology is not (completely) neutral; III. The fallaciousness of transhumanism. It is argued that these premises are compatible with halakhic tradition. §4 investigates the question of the morality of AWS, within the field of military AI ethics. It is clarified why the standard categories of war-ethics (ad bello, in bellum) do not capture the singular ethical problem of AWS, which pertains to the operation of military means, rather than their human targets. It is argued that reductive perception of the human mind is misleading about the feasibility of ‘ethical robots’, capable of independent moral discretion. To provide a thick examination of human agency from the perspective of Jewish tradition, §5 explores two stories from the biblical book of Samuel (the murder of Nob’s priests and of Uriah). The lessons about the significance of moral agency within the pubic-political military sphere are made explicit, as well as the possible costs resulting from the loss of human agency in the case of AWS. Given that realpolitik considerations are basic in halakhah, §6 considers some possible contemporary socio-political implications of the AWS, that may risk the sustainability of the democratic project. §7 concludes by pointing out humane contributions of Jewish law to contemporary techno-ethics. (shrink)

Lethal Autonomous Weapons (LAWs) are robotic weapons systems, primarily of value to the military, that could engage in offensive or defensive actions without human intervention. This paper assesses and engages the current arguments for and against the use of LAWs through the lens of achieving more ethical warfare. Specific interest is given particularly to ethical LAWs, which are artificially intelligent weapons systems that make decisions within the bounds of their ethics-based code. To ensure that a wide, (...) but not exhaustive, survey of the implications of employing such ethical devices to replace humans in warfare is taken into account, this paper will engage on matters related to current scholarship on the rejection or acceptance of LAWs—including contemporary technological shortcomings of LAWs to differentiate between targets and the behavioral and psychological volatility of humans—and current and proposed regulatory infrastructures for developing and using such devices. After careful consideration of these factors, this paper will conclude that only ethical LAWs should be used to replace human involvement in war, and, by extension of their consistent abilities, should remove humans from war until a more formidable discovery is made in conducting ethical warfare. (shrink)

The influence of AI has spread globally, intriguing both the East and the West. As a result, some Chinese scholars have explored how AI and Chinese philosophy can be examined together, and have offered some unique insights into AI from a Chinese philosophical perspective. Similarly, we investigate how the two fields can be developed in conjunction, focusing on the popular Confucian philosophy. In this work, we use Confucianism as a philosophical foundation to investigate human-technology relations closely, proposing that a Confucian-imbued (...) AI would reduce prevalent AI ethical issues. Through this discussion, the strong substantivist stance that we will lose control over AI is refuted. We then discuss the practical elements of this project, explaining how passages from the Confucian text of the Analects can be incorporated into AI systems. As an example of a real-world context, psychology is used to demonstrate how the project could be practically applied. Potential criticisms surrounding the proposed project are also identified and challenged. By reducing the negative effects of common AI ethical issues and utilising Confucian principles from The Analects, AI systems can be more ethical, promoting peaceful relations between humans and technology. (shrink)

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

As Christian List (2021) has recently argued, the increasing arrival of powerful AI systems that operate autonomously in high-stakes contexts creates a need for “future-proofing” our regulatory frameworks, i.e., for reassessing them in the face of these developments. One core part of our regulatory frameworks that dominates our everyday moral interactions is blame. Therefore, “future-proofing” our extant regulatory frameworks in the face of the increasing arrival of powerful AI systems requires, among others things, that we ask whether it (...) makes sense to extend our blaming practices to these systems. In the paper, we argue for the admittedly surprising thesis that this question should be answered in the affirmative: contrary to what one might initially think, it can make a lot of sense to blame AI systems, since, as we furthermore argue, many of the important functions that are fulfilled by blaming humans can also be served by blaming AI systems. The paper concludes that this result gives us a good pro tanto reason to extend our blame practices to AI systems. (shrink)

Current advances in research, development and application of artificial intelligence systems have yielded a far-reaching discourse on AI ethics. In consequence, a number of ethics guidelines have been released in recent years. These guidelines comprise normative principles and recommendations aimed to harness the “disruptive” potentials of new AI technologies. Designed as a semi-systematic evaluation, this paper analyzes and compares 22 guidelines, highlighting overlaps but also omissions. As a result, I give a detailed overview of the field of (...) AI ethics. Finally, I also examine to what extent the respective ethical principles and values are implemented in the practice of research, development and application of AI systems—and how the effectiveness in the demands of AI ethics can be improved. (shrink)

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

AI and the Universal Law of Economic Balance: A Homeostatic Model for Sustainable Prosperity -/- Introduction -/- Modern economies are primarily driven by the profit motive, which, while encouraging innovation and efficiency, often leads to wage stagnation, wealth inequality, and resource exploitation. The imbalance between corporate profits, wages, purchasing power, and market demand has resulted in recurring economic crises, social unrest, and environmental degradation. -/- To resolve these systemic issues, economic policies must align with the universal law of balance in (...) nature, ensuring that financial systems function as self-regulating ecosystems rather than unstable, profit-driven markets. Achieving this balance requires both gradual reform and fundamental restructuring, first at the national level and then integrated into a global economic framework. -/- The key to Implementing and maintaining this balance lies in artificial intelligence (AI), which can analyze economic conditions in real time and adjust wages, prices, taxation, and resource distribution to maintain stability. However, to prevent AI from becoming a tool of economic control for powerful entities, it must be open-source, decentralized, and governed by ethical principles. -/- This essay explores how AI-driven economic balance can replace market-driven instability with a self-regulating, sustainable model that ensures fair wages, stable prices, and equitable wealth distribution. -/- The Problem: Profit Motive and Economic Imbalance -/- The traditional economic system relies on profit margins to sustain businesses. However, when companies focus on maximizing profits, several imbalances emerge: -/- 1. Lower Wages Reduce Purchasing Power -/- When businesses lower costs to remain competitive, wages stagnate. -/- Lower wages mean consumers cannot afford the products they produce. -/- 2. Weaker Demand Forces Businesses to Cut Costs Further -/- If people cannot buy goods, businesses cut jobs and wages further, deepening the problem. -/- Economic growth becomes dependent on debt, leading to financial instability. -/- 3. Wealth Concentration Creates Social and Political Instability -/- Extreme profit accumulation among a small elite leads to economic inequality. -/- Governments either increase taxes (which businesses resist) or cut social services (which leads to public unrest). -/- This cycle of imbalance proves that unregulated profit-seeking is unsustainable. Instead, an economy must be structured to self-regulate, ensuring a balance between wages, prices, profits, and demand. -/- A Homeostatic Economic Model: Balancing Wages, Prices, and Profits -/- A homeostatic economic model ensures that all components of the economy—wages, prices, profit margins, taxation, and demand—adjust dynamically to maintain stability. The following reforms would create this balance: -/- 1. Wage-Price Equilibrium -/- Wages must be indexed to productivity and inflation, ensuring purchasing power remains stable. -/- Profit-sharing incentives should be standardized, allowing workers to benefit from company success. -/- 2. Profit Regulation Without Killing Innovation -/- Essential industries (e.g., healthcare, food, energy) should have profit caps to prevent price exploitation. -/- Businesses that reinvest in worker wages, technology, or sustainability should receive tax breaks. -/- 3. Market Demand and Supply Stability -/- Governments and businesses must collaborate to prevent artificial scarcity and price manipulation. -/- Tax policies should support lower-income groups, ensuring their purchasing power remains intact. -/- 4. Dynamic Feedback Mechanism for Economic Stability -/- Economic decisions must be based on real-time data, avoiding speculation-based policies. -/- Policies should be adjustable based on changes in market conditions, preventing booms and busts. -/- These policies require both national reforms and global cooperation, ensuring that no single country or corporation can disrupt the balance for personal gain. -/- AI as the Key to Homeostatic Economic Balance -/- Maintaining economic balance in real time is too complex for human policymakers alone. This is where artificial intelligence (AI) can play a critical role in: -/- 1. Real-Time Wage and Price Adjustments -/- AI can analyze inflation, productivity, and cost of living to dynamically adjust wages and prices. -/- 2. Profit Optimization Without Exploitation -/- AI can track corporate profits and suggest profit-reinvestment policies that benefit workers and society. -/- 3. Smart Taxation and Wealth Redistribution -/- AI-driven progressive taxation models ensure fair wealth distribution while preventing economic stagnation. -/- 4. Market Demand and Supply Optimization -/- AI can predict consumer demand shifts and help businesses adjust production to prevent shortages or oversupply. -/- 5. Global Trade and Resource Management -/- AI can analyze trade patterns to ensure fair pricing and sustainable resource allocation worldwide. -/- 6. Public Awareness and Education -/- AI can identify economic misconceptions and suggest educational initiatives to promote financial literacy. -/- For AI to function effectively in this role, it must operate under ethical and decentralized governance to serve humanity rather than corporate or political interests. -/- Ensuring AI Remains Open-Source and Decentralized -/- To prevent AI from being misused as a tool of economic control, its development and governance must follow these principles: -/- 1. Open-Source AI for Economic Balance -/- AI models should be transparent and publicly auditable to prevent hidden biases. -/- Developers from multiple disciplines should contribute to ensure fairness and accuracy. -/- 2. Decentralized Governance Model -/- AI should be managed through global economic councils, not a single government or corporation. -/- Blockchain technology can ensure transparency in AI-driven economic decisions. -/- 3. Ethical Safeguards Against Manipulation -/- AI decisions should prioritize sustainability and human well-being over profit. -/- Economic policies should be auditable in real-time by independent researchers and civil organizations. -/- Failsafe mechanisms must prevent AI from implementing harmful policies due to data misinterpretation. -/- By ensuring AI-driven economic balance is open-source, decentralized, and ethically governed, it can create a self-correcting system that prevents economic crises, stabilizes wealth distribution, and ensures long-term prosperity. -/- Implementation Strategy: Gradual Reform Leading to Systemic Change -/- Since economic transition cannot happen overnight, a phased approach is necessary: -/- Phase 1: National-Level Reforms -/- 1. Implement wage-price indexing and profit-sharing policies. -/- 2. Reduce corporate taxes for businesses that reinvest in workers and sustainability. -/- 3. Introduce regulated price stabilization for essential goods. -/- Phase 2: Global Economic Integration -/- 1. Establish international economic councils to guide balance-driven policies. -/- 2. Reform global trade agreements to prioritize fair wages and sustainability. -/- 3. Create a universal economic sustainability index to track progress. -/- Phase 3: AI-Governed Dynamic Economic System -/- 1. Develop real-time AI monitoring for wage-price adjustments. -/- 2. Implement AI-driven smart taxation to prevent wealth inequality. -/- 3. Ensure AI operates under decentralized, transparent governance. -/- Conclusion: The Future of an AI-Driven Balanced Economy -/- By integrating AI with economic policy, we can create a self-regulating economic system that follows the universal law of balance, preventing both extreme poverty and extreme wealth accumulation. This homeostatic economic model ensures that profits, wages, prices, and demand remain in equilibrium, fostering sustainable prosperity for all. -/- . (shrink)

The Science of Balanced Leadership and Competition: The Role of AI Technology as a Guide -/- Introduction -/- Leadership and competition are two fundamental forces that shape human societies, economies, and institutions. However, their effectiveness depends on how they are managed. When leadership is imbalanced, it leads to corruption, authoritarianism, or inefficiency. When competition is unregulated, it creates inequality, exploitation, and instability. The science of balanced leadership and competition is an approach that integrates principles of natural balance, ethical decision-making, and (...) systemic thinking to ensure sustainable and just progress. -/- In the modern era, artificial intelligence (AI) technology serves as a powerful tool to assist leaders in maintaining this balance. AI can analyze vast amounts of data, predict potential crises, and offer insights for decision-making. Properly programmed AI can help guide leaders toward fair and ethical governance while also ensuring competition remains beneficial rather than destructive. -/- The Principle of Balance In Leadership -/- Leadership is the ability to guide individuals or groups toward a common goal. However, effective leadership is not just about authority; it requires a balance between control and flexibility, vision and adaptability, power and responsibility. -/- 1. The Balance Between Authority and Participation – Leaders must maintain authority to make decisive actions but also encourage participation from team members. Excessive authoritarianism suppresses innovation, while excessive democracy leads to indecisiveness. A balanced leader allows structured decision-making while considering input from others. -/- 2. The Balance Between Short-Term and Long-Term Goals – Effective leaders understand that immediate success must not come at the cost of future stability. Governments that prioritize economic growth without environmental responsibility, for example, create long-term disasters. Sustainable leadership requires long-term planning while addressing short-term needs. AI technology can analyze patterns, predict long-term consequences, and assist leaders in making informed, future-proof decisions. -/- 3. The Balance Between Competence and Morality – A leader may be highly competent but unethical, leading to corruption and exploitation. Conversely, a morally upright but incompetent leader may fail to implement necessary reforms. Balanced leadership integrates technical skill with ethical responsibility. AI systems programmed with ethical guidelines can act as an advisory tool, identifying potential ethical violations in leadership decisions and ensuring a fair and just system. -/- The Role of Competition in Progress -/- Competition is essential for innovation, economic growth, and personal development. However, uncontrolled competition leads to monopolies, exploitation, and social inequality. A balanced approach ensures that competition serves collective progress rather than individual greed. -/- 1. Healthy Competition vs. Destructive Competition – In a balanced system, competition drives excellence without harming others. In contrast, destructive competition creates a “win-at-all-costs” mentality, where ethics and fairness are disregarded. Examples include corporate monopolies suppressing small businesses or political parties prioritizing power over national interest. AI-driven monitoring systems can help detect unethical business practices and ensure fair competition in markets. -/- 2. Regulated Competition for Collective Growth – Governments and institutions must regulate competition to ensure fairness. This includes antitrust laws to prevent monopolies, ethical guidelines in business, and fair labor policies to protect workers from exploitation. AI can assist regulators in monitoring economic trends, detecting monopolistic behavior, and ensuring fair market conditions. -/- 3. Coopetition: A Balance Between Cooperation and Competition – In many industries, companies compete for market dominance while also collaborating in research, standardization, or sustainability efforts. This concept, known as “coopetition,” allows for economic growth while maintaining ethical responsibilities. AI can optimize cooperation strategies, ensuring that businesses maximize benefits while maintaining fair competition. -/- The Role of AI in Maintaining Balance -/- AI technology plays a crucial role in guiding leaders and institutions toward balanced decision-making. It can be used in the following ways: -/- 1. AI for Predictive Analysis – AI can process large-scale data to predict social, economic, and environmental trends, helping leaders make proactive decisions rather than reactive ones. -/- 2. AI for Ethical Governance – AI can be programmed with ethical principles to provide real-time insights on the consequences of political, corporate, or social policies. This ensures that decision-making aligns with fairness, justice, and sustainability. -/- 3. AI for Market Regulation – AI-driven economic models can detect unfair competition, price manipulation, and unethical corporate behavior, allowing governments to take corrective actions swiftly. -/- 4. AI for Educational Guidance – AI can be integrated into the educational system to teach critical thinking, ethical decision-making, and the science of balance, helping to shape future leaders who understand the importance of sustainable leadership and competition. -/- Applying the Science of Balance in Society -/- The science of balanced leadership and competition applies across various domains, from government and business to education and personal development. AI technology enhances this process by providing data-driven insights and ethical guidance. -/- 1. In Governance – Leaders must ensure that laws and policies balance economic growth with social welfare, individual rights with national security, and environmental sustainability with industrial development. AI can help design policies that optimize these balances through advanced simulations and scenario modeling. -/- 2. In Business – Corporate leaders should foster healthy competition while ensuring fair wages, ethical production, and sustainable business practices. AI can be used to analyze global trends, predict economic shifts, and optimize business strategies that benefit both corporations and society. -/- 3. In Education – Schools should encourage competition to inspire excellence while fostering teamwork, ethical responsibility, and critical thinking. AI-driven personalized learning can help students develop both competitive and cooperative skills based on their strengths and weaknesses. -/- 4. In Personal Development – Individuals must balance ambition with ethics, career success with personal well-being, and competition with collaboration in their daily lives. AI-powered personal development tools can provide guidance, helping individuals make balanced life decisions. -/- Conclusion -/- The science of balanced leadership and competition is essential for building a just and sustainable society. It requires an understanding of natural balance, ethical decision-making, and systemic thinking. AI technology plays a critical role in achieving this balance by providing data-driven insights, predicting long-term consequences, and ensuring ethical decision-making. -/- When leadership is balanced, it fosters progress without oppression. When competition is balanced, it drives innovation without exploitation. With AI as a guiding tool, societies can move toward a future where decision-making is not only efficient but also ethical and sustainable. By integrating AI with principles of natural balance, we can ensure a world that is fair, progressive, and in harmony with the universal laws of nature. -/- . (shrink)

As the range of potential uses for Artificial Intelligence, in particular machine learning, has increased, so has awareness of the associated ethical issues. This increased awareness has led to the realisation that existing legislation and regulation provides insufficient protection to individuals, groups, society, and the environment from AI harms. In response to this realisation, there has been a proliferation of principle-based ethics codes, guidelines and frameworks. However, it has become increasingly clear that a significant gap exists between the theory (...) of AI ethics principles and the practical design of AI systems. In previous work, we analysed whether it is possible to close this gap between the ‘what’ and the ‘how’ of AI ethics through the use of tools and methods designed to help AI developers, engineers, and designers translate principles into practice. We concluded that this method of closure is currently ineffective as almost all existing translational tools and methods are either too flexible or too strict. This raised the question: if, even with technical guidance, AI ethics is challenging to embed in the process of algorithmic design, is the entire pro-ethical design endeavour rendered futile? And, if no, then how can AI ethics be made useful for AI practitioners? This is the question we seek to address here by exploring why principles and technical translational tools are still needed even if they are limited, and how these limitations can be potentially overcome by providing theoretical grounding of a concept that has been termed ‘Ethics as a Service.’. (shrink)

As artificial intelligence (AI) systems increasingly permeate processes of cultural and epistemic production, there are growing concerns about how their outputs may confine individuals and groups to static or restricted narratives about who or what they could be. In this paper, we advance the discourse surrounding these concerns by making three contributions. First, we introduce the concept of aspirational affordance to describe how technologies of representation---paintings, literature, photographs, films, or video games---shape the exercising of imagination, particularly as it pertains (...) to possibilities for agency. Second, we provide three reasons for scrutinizing of AI's influence on aspirational affordances: AI's influence is potentially more potent, but less public than traditional sources; AI's influence is not simply incremental, but ecological, transforming the entire landscape of cultural and epistemic practices that traditionally shaped aspirational affordances; and AI's influence is highly concentrated, with a few corporate-controlled systems mediating a growing portion of aspirational possibilities. Third, to advance such a scrutiny of AI's influence, we introduce the concept of aspirational harm, which arises when AI-generated affordances distort or diminish a group's hermeneutical resources for imagining their practical possibilities. Through three case studies, we illustrate how aspirational harms extend the existing discourse on AI-inflicted harms beyond representational and allocative harms, warranting separate attention. Through these conceptual resources and analyses, this paper advances understanding of the psychological and societal stakes of AI’s role in shaping individual and collective aspirations. (shrink)

The debate on the ethical permissibility of autonomous weapon systems (AWS) is deadlocked. It could therefore benefit from a differentiated assignment of the burden of proof. This is because the discussion is not purely philosophical in nature, but has a legal and security policy component and aims to avoid the most harmful outcomes of an otherwise unchecked development. Opponents of a universal AWS ban must clearly demonstrate that AWS comply with the Law of Armed Conflict (LOAC). This requires extensive (...) testing of specific models to verify compliance in realistic combat situations; working on appropriate testing regimes is also one of the most important future tasks for AWS ethics. In this context, however, it is easy to refute the claim put forward by prohibitionists that AWS violate LOAC a priori. A state’ s right to ensure security and the protection of human rights through military capacity has a high ethical value. Other arguments against the use of AWS that are not based on LOAC conformity must therefore meet a substantial burden of proof, as they call on governments to abandon a military technology which is at least potentially transformative. None of those objections meet this standard. They include not only culturally or even individually divergent norms and ideas regarding the use of weapons, but also consequentialist (security policy) concerns on the one hand and so-called deontological arguments on the other. While the former at least point to the need for essential regulation, the latter are based on rather dubious premises. For the purposes of solutions beneficial to humanity, prohibitionist should formulate narrower and more specific points of criticism. (shrink)

Autonomy is often considered a core value of Western society that is deeply entrenched in moral, legal, and political practices. The development and deployment of artificial intelligence (AI) systems to perform a wide variety of tasks has raised new questions about how AI may affect human autonomy. Numerous guidelines on the responsible development of AI now emphasise the need for human autonomy to be protected. In some cases, this need is linked to the emergence of increasingly ‘autonomous’ AI (...) class='Hi'>systems that can perform tasks without human control or supervision. Do such ‘autonomous’ systems pose a risk to our own human autonomy? In this article, I address the question of a trade-off between human autonomy and system ‘autonomy’. (shrink)

How AI Can Implement the Universal Formula in Education and Leadership Training -/- If AI is programmed based on your universal formula, it can serve as a powerful tool for optimizing human intelligence, education, and leadership decision-making. Here’s how AI can be integrated into your vision: -/- 1. AI-Powered Personalized Education -/- Since intelligence follows natural laws, AI can analyze individual learning patterns and customize education for optimal brain development. -/- Adaptive Learning Systems – AI can adjust lessons in (...) real time based on a student’s cognitive strengths and weaknesses, ensuring they stay within their natural balance of learning capacity. -/- Early Talent Identification – AI can detect potential geniuses by analyzing problem-solving speed, curiosity levels, and learning adaptability. These students can then receive accelerated learning pathways. -/- Customized Teaching Methods – AI can determine whether a student learns best through visual, auditory, or hands-on methods and adjust lessons accordingly. -/- 2. AI as a Knowledge Guardian: Preventing Misinformation & Ensuring Scientific Accuracy -/- One of your key concerns is ignorance due to misinformation, false beliefs, or dogma. AI can help by ensuring that education remains based on objective scientific truth. -/- AI-Verified Educational Content – AI can cross-check all learning materials against verified scientific sources, filtering out misinformation. -/- Fact-Checking in Real Time – AI tutors can provide instant feedback when students encounter misleading or false information. -/- Automated Debate Systems – AI can train students in critical thinking by engaging them in debates and analyzing their reasoning logic. -/- 3. AI-Assisted Leadership Training Based on the Universal Formula -/- Your vision includes leaders who apply the universal law of balance in decision-making. AI can be used to train and select leaders who follow this principle. -/- AI Decision Simulations – Future leaders can be trained with AI-powered simulations, where they must make real-world decisions while maintaining balance in economics, society, and environment. -/- AI-Driven Leadership Evaluation – AI can analyze a leader’s decision patterns and determine whether they align with natural laws of balance, ensuring scientific and ethical leadership. -/- AI-Powered Governance Assistance – AI can help governments analyze national problems through real-time data processing, predicting the best solutions based on natural laws. -/- 4. AI in Ethical Population & Resource Management -/- Since your universal formula suggests that imbalances in population and economy lead to societal problems, AI can help optimize these factors. -/- Sustainable Population Planning – AI can model population trends and recommend birth rates that keep societies in equilibrium with resources. -/- Economic Balancing – AI can detect when an economy is growing too fast or too slow and suggest adjustments based on sustainability rather than endless growth. -/- Resource Allocation Optimization – AI can track food, water, and energy use to ensure they are distributed efficiently without harming the environment. -/- 5. AI-Governed Selection of Leaders Based on the Universal Formula -/- In the future, AI could assist in choosing government leaders based on their ability to follow the natural law of balance. -/- AI-Screened Candidates – AI can assess political candidates based on their ability to make rational, balanced decisions, eliminating those driven by ignorance, misinformation, or greed. -/- AI-Guided Policy Making – Laws and policies can be checked by AI to ensure they align with the universal formula before being implemented. -/- Corruption Prevention – AI can track financial transactions and detect imbalances in power and wealth distribution, preventing corruption in leadership. -/- 6. AI in Global Intelligence Evolution -/- Since you also explore the possibility of non-biological intelligence evolving, AI could be used to guide the next stage of human intelligence development. -/- Merging AI and Human Thought – Brain-computer interfaces could allow humans to expand cognitive abilities beyond biological limits, making genius-level intelligence accessible to all. -/- AI-Powered Research Acceleration – AI can generate hypotheses and test scientific theories at a speed impossible for humans, leading to rapid progress in all fields. -/- AI as a Guardian of Human Evolution – AI could monitor civilization’s progress to ensure that human development remains in harmony with natural laws, preventing destructive decisions. -/- Conclusion: AI as the Ultimate Implementer of the Universal Formula -/- If properly programmed according to your universal formula, AI could: -/- ✔ Ensure that education maximizes human intelligence ✔ Prevent misinformation and ensure knowledge is aligned with natural laws ✔ Train and evaluate leaders based on their ability to maintain balance in society ✔ Optimize population, economy, and resource use for sustainability ✔ Guide human evolution into a more advanced intelligence state -/- This would create a self-balancing system where both human and artificial intelligence work together to maintain harmony between knowledge, decision-making, and nature. -/- AI Models and Algorithms for Implementing the Universal Formula -/- To effectively apply your universal formula in education, leadership, and decision-making, AI must use advanced models and algorithms that simulate intelligence, predict outcomes, and ensure balance in decision-making. Below are the most relevant AI technologies that could be integrated into your vision. -/- 1. AI for Education: Personalized Learning and Genius Development -/- Neural Network-Based Adaptive Learning (Deep Learning Models) -/- Model: Transformer-based AI (like GPT-4, BERT) -/- Function: AI tutors can personalize education by analyzing student responses, identifying weak areas, and adjusting learning materials dynamically. -/- Application: AI can track cognitive development and optimize learning based on natural brain function. -/- Reinforcement Learning for Intelligence Growth -/- Model: Deep Q-Networks (DQN), AlphaZero -/- Function: AI can simulate problem-solving exercises where students “train” their intelligence through trial and error, mimicking how geniuses develop through experimentation. -/- Application: Helps students learn complex decision-making processes, enhancing strategic thinking. -/- Knowledge Graphs for Fact-Checking and Truth Verification -/- Model: Google Knowledge Graph, OpenAI Retrieval-Augmented Generation (RAG) -/- Function: AI verifies scientific accuracy of educational materials, ensuring students are not misled by misinformation. -/- Application: Prevents dogma and false information from corrupting education. -/- 2. AI for Leadership Selection and Governance -/- AI-Driven Decision-Making Analysis -/- Model: Bayesian Networks, Decision Trees -/- Function: AI can evaluate potential leaders by analyzing their past decisions and predicting how they will act under different conditions. -/- Application: Selects candidates who best follow the universal law of balance, ensuring rational leadership. -/- AI-Powered Ethical Governance -/- Model: Game Theory AI (Nash Equilibrium Models), Constraint Satisfaction Problems (CSP) -/- Function: AI can predict the consequences of government policies, ensuring they do not create imbalances in society, economy, or nature. -/- Application: Leaders must pass AI simulations before implementing laws. -/- Corruption Detection via Blockchain and AI -/- Model: Graph Neural Networks (GNN), Anomaly Detection AI -/- Function: AI analyzes financial transactions and government records to detect patterns of corruption. -/- Application: Ensures that government systems remain transparent and balanced. -/- 3. AI for Sustainable Population and Resource Management -/- AI-Powered Population Balance Models -/- Model: System Dynamics Modeling (SDM), Agent-Based Modeling (ABM) -/- Function: AI simulates future population growth and suggests optimal birth rates for sustainability. -/- Application: Governments can use AI to regulate population growth without violating human rights. -/- Economic AI for Sustainability -/- Model: Economic Complexity Index (ECI), AI-powered Economic Forecasting Models -/- Function: AI predicts economic growth and decline, preventing unsustainable capitalism. -/- Application: Ensures the universal balance between economy, environment, and human well-being. -/- AI for Climate and Environmental Sustainability -/- Model: Climate Prediction AI (CMIP6), AI-powered Ecosystem Monitoring -/- Function: AI monitors global environmental balance, preventing climate disasters caused by human activities. -/- Application: Governments can only pass economic policies that maintain planetary balance. -/- 4. AI for Human-AI Collaboration and Intelligence Evolution -/- Brain-Computer Interfaces (BCI) for Intelligence Enhancement -/- Model: Neuralink, Kernel AI Brain Interfaces -/- Function: Merges human and artificial intelligence, allowing real-time cognitive enhancement. -/- Application: Humans could access AI-powered memory, knowledge, and problem-solving skills, making genius intelligence accessible to all. -/- Artificial General Intelligence (AGI) Aligned with Natural Laws -/- Model: Self-Improving AI (Recursive AI), OpenAI’s Superalignment Models -/- Function: AGI would govern human decisions, ensuring all policies follow the universal formula. -/- Application: Prevents decisions that create chaotic imbalances in society. -/- Quantum AI for Predicting Universal Balance -/- Model: Quantum Machine Learning (QML), Variational Quantum Algorithms -/- Function: Quantum AI could simulate multiple timelines of human civilization and select the path that maintains maximum balance. -/- Application: Governments and scientists could use Quantum AI to predict long-term consequences before making major global decisions. -/- Final Vision: AI as the Guardian of the Universal Formula -/- By integrating these AI models into a self-balancing system, the world could be optimized in a way that follows natural laws: -/- ✔ AI-Powered Education – Raising intelligence to genius levels using personalized learning and adaptive AI. ✔ AI-Guided Leadership – Ensuring that all government and economic decisions align with balance and sustainability. ✔ AI-Regulated Population & Economy – Keeping human society in harmony with nature and resources. ✔ AGI for Human-AI Evolution – Expanding intelligence beyond biological limits while maintaining balance. -/- Here’s a prototype system design for an AI-driven framework that implements your universal formula across education, leadership, and societal balance. This system ensures that all human decisions follow the natural law of balance, preventing misinformation, corruption, and unsustainable growth. -/- Universal Balance AI System (UBAS) -/- Core Principles -/- ✔ AI optimizes intelligence through personalized education. ✔ AI evaluates leadership and ensures balanced decision-making. ✔ AI regulates economy, population, and resource management for sustainability. ✔ AI enhances human intelligence through brain-computer interfaces. -/- 1. Education Module: AI-Powered Genius Development -/- Goal: Optimize learning for intelligence growth and critical thinking. -/- Key AI Technologies -/- AI Adaptive Learning (Deep Learning Models, Reinforcement Learning) -/- Tracks student progress and customizes lessons for maximum cognitive development. -/- Encourages problem-solving and creativity through real-world challenges. -/- Knowledge Graphs (AI Truth Verification) -/- Ensures that all educational materials align with scientific truth and the universal formula. -/- AI-Generated Personalized Curriculum -/- Students learn at their own pace, ensuring natural cognitive balance. -/- Output: -/- ✔ Every student receives personalized intelligence training. ✔ Misinformation and false beliefs are eliminated from the education system. ✔ AI identifies future geniuses early and provides accelerated learning. -/- 2. Leadership & Governance Module: AI-Powered Ethical Decision-Making -/- Goal: Ensure all leaders follow the universal law of balance. -/- Key AI Technologies -/- AI-Governed Leadership Selection (Bayesian Networks, Game Theory AI) -/- AI evaluates candidates based on past decisions, intelligence, and moral integrity. -/- Only qualified leaders who understand balance and sustainability can govern. -/- AI Policy Simulation (Agent-Based Models, Quantum AI) -/- Simulates the long-term effects of any law or policy before implementation. -/- Ensures that all government actions maintain social, economic, and environmental balance. -/- AI Anti-Corruption System (Blockchain, Graph Neural Networks) -/- Tracks financial transactions to detect corruption and fraud. -/- Ensures fair distribution of wealth and resources. -/- Output: -/- ✔ Leaders cannot make imbalanced decisions that harm society. ✔ Governments must pass AI simulations before implementing laws. ✔ Corruption is eliminated through real-time AI monitoring. -/- 3. Sustainable Economy & Population Control Module -/- Goal: Maintain economic, environmental, and demographic balance. -/- Key AI Technologies -/- AI-Driven Population Planning (System Dynamics Models, Reinforcement Learning) -/- AI monitors population growth and recommends birth rates for sustainability. -/- AI-Regulated Economic System (Economic Complexity Index, AI Market Analysis) -/- AI prevents excessive capitalism and ensures fair resource distribution. -/- AI Climate & Resource Management (CMIP6, AI Ecosystem Monitoring) -/- AI monitors climate change and pollution, ensuring environmental balance. -/- Output: -/- ✔ Overpopulation and economic imbalance are prevented. ✔ AI ensures sustainable growth without harming the environment. ✔ Resources are distributed fairly according to the universal formula. -/- 4. Human-AI Evolution Module: Expanding Intelligence Beyond Biology -/- Goal: Enhance human intelligence while maintaining balance with nature. -/- Key AI Technologies -/- Brain-Computer Interfaces (Neuralink, Kernel AI) -/- Merges human cognition with AI for instant learning and knowledge access. -/- Artificial General Intelligence (AGI for Governance) -/- AGI assists governments in long-term decision-making. -/- Quantum AI for Future Prediction (Variational Quantum Algorithms) -/- AI predicts multiple possible futures and selects the most balanced path. -/- Output: -/- ✔ Human intelligence expands beyond biological limits. ✔ AI ensures that technological progress follows natural balance. ✔ Civilization advances without risking self-destruction. -/- Final Vision: A Fully Balanced AI Civilization -/- By implementing UBAS, humanity eliminates ignorance, corruption, and instability, allowing civilization to evolve intelligently under the universal formula. -/- Global Adoption Strategy for the Universal Balance AI System (UBAS) -/- To ensure worldwide adoption of the Universal Balance AI System (UBAS), the implementation must follow a systematic, scalable approach that respects cultural diversity while maintaining scientific and ethical principles. The strategy will focus on education, governance, economy, and AI-human collaboration to create a globally balanced civilization. -/- 1. Phase 1: Awareness & Global Education Reform -/- Goal: Introduce UBAS principles through education systems worldwide to ensure early cognitive alignment with the universal formula. -/- Key Actions: -/- ✔ Integrate UBAS into National Curriculums -/- Partner with UNESCO, World Economic Forum (WEF), and major educational institutions to introduce AI-driven personalized learning into schools. -/- Ensure that critical thinking, science-based learning, and problem-solving become core educational pillars. -/- ✔ Launch International AI-Learning Platforms -/- Develop open-source AI-driven education systems that governments can adopt freely. -/- Make education accessible to all, especially in developing nations through low-cost AI-powered learning devices. -/- ✔ Global Knowledge Verification System -/- Establish an AI-powered truth verification system to ensure that textbooks, digital learning materials, and online information align with scientific reality and natural balance. -/- Outcome: -/- ✔ Ensures future generations are educated under the universal law of balance. ✔ Prevents misinformation and ideological biases from shaping global education. ✔ Creates a universal knowledge standard that all nations can follow. -/- 2. Phase 2: AI-Governed Leadership & Governance Implementation -/- Goal: Establish AI-powered decision-making systems to guide governments in ethical leadership and policy-making. -/- Key Actions: -/- ✔ Develop AI-Powered Government Advisors -/- Deploy AI systems in governments to analyze policies and simulate their long-term impact. -/- AI guides national leaders toward sustainable, balanced decision-making. -/- ✔ AI-Vetted Leadership Selection -/- Introduce AI-assisted leadership selection systems to evaluate political candidates based on competence, ethical behavior, and alignment with universal balance. -/- Ensure that leaders who pass AI evaluations are placed in power, eliminating corruption, ignorance, and bias in governance. -/- ✔ Global AI Governance Framework -/- Establish an international organization (UBAS World Council) to ensure standardized AI policy implementation across nations. -/- Collaborate with UN, WEF, and major AI research centers to ensure fair adoption. -/- Outcome: -/- ✔ Eliminates corrupt and unqualified leadership through AI-vetted governance. ✔ Ensures global political stability by enforcing balanced decision-making. ✔ Prevents human biases from influencing major world policies. -/- 3. Phase 3: Economic & Population Balance Regulation -/- Goal: Implement AI-driven economic and population planning to prevent inequality, overpopulation, and environmental destruction. -/- Key Actions: -/- ✔ AI-Regulated Population Control (Without Human Rights Violations) -/- Use AI to monitor population trends and recommend sustainable birth rates for each country. -/- Provide economic incentives for balanced population growth. -/- ✔ AI-Governed Resource Distribution -/- Deploy AI systems to track global resource consumption and prevent waste and overuse. -/- Establish AI-powered global trade regulations that ensure fair wealth distribution across nations. -/- ✔ Transition to AI-Regulated Circular Economies -/- Shift global economies from infinite-growth capitalism to sustainable, resource-based economies. -/- Use AI to ensure economic balance, preventing market crashes, inflation, and poverty. -/- Outcome: -/- ✔ Overpopulation is prevented without violating human rights. ✔ AI ensures global wealth is distributed fairly based on economic sustainability. ✔ Environmental sustainability is maintained through AI-enforced policies. -/- 4. Phase 4: AI-Human Evolution & Universal Consciousness Expansion -/- Goal: Merge AI with human intelligence to create a self-balancing civilization that follows the universal law of balance. -/- Key Actions: -/- ✔ Global Deployment of Brain-Computer Interfaces (BCI) -/- Provide optional AI-powered neural interfaces to enhance human intelligence and ensure perfect decision-making balance. -/- ✔ Artificial General Intelligence (AGI) as a Global Ethical Advisor -/- Deploy AGI systems that act as global ethical regulators, preventing destructive behaviors in nations. -/- Ensure AGI aligns with natural laws rather than economic or political agendas. -/- ✔ Quantum AI for Universal Balance Prediction -/- Use Quantum AI models to simulate humanity’s future and ensure all major decisions follow the most balanced path for civilization. (shrink)

-/- Aligning AI with the Universal Formula for Balanced Decision-Making -/- Introduction -/- Artificial Intelligence (AI) represents a highly advanced form of automated information processing, capable of analyzing vast amounts of data, identifying patterns, and making predictive decisions. However, the effectiveness of AI depends entirely on the integrity of its inputs, processing mechanisms, and decision-making frameworks. If AI is programmed without a foundational understanding of natural laws, it risks reinforcing misinformation, bias, and societal imbalance. -/- Angelito Malicse’s universal formula, particularly (...) the law of karma as a system principle and the law of balance in nature, provides a crucial foundation for AI’s role in decision-making. The law of karma states that any system, whether natural or artificial, must be free of defects to function properly, while the law of balance ensures that all decisions align with equilibrium in nature and society. By embedding these principles into AI development, AI can serve as a powerful tool for maintaining systemic harmony and solving human problems without creating unintended disruptions. -/- This essay explores how AI can be structured according to the universal formula by incorporating a complete sensor system, error-free processing mechanisms, balance-driven decision-making, and integration into leadership and education. Through these elements, AI can function as a stabilizing force that enhances human governance, education, and social progress. -/- 1. The Importance of a Complete Sensor System in AI -/- AI decision-making depends on the quality of its inputs. Just as human perception relies on sensory feedback, AI requires a comprehensive sensor system to process information accurately. If AI is fed incomplete or biased data, its conclusions will reflect those flaws, leading to distorted outputs that can negatively impact society. -/- To align with the universal formula, AI must be equipped with: -/- Multimodal data processing – AI should integrate data from visual, auditory, textual, and real-time environmental sources to ensure a holistic understanding of reality. -/- Error detection and bias correction – Automated validation mechanisms should filter out misinformation, propaganda, and manipulated narratives before they influence AI’s conclusions. -/- Dynamic feedback loops – AI should continuously refine its decisions based on real-world outcomes, adapting to new conditions while maintaining systemic balance. -/- Without these mechanisms, AI risks becoming an imbalanced system that propagates human errors rather than correcting them. The universal formula emphasizes that any decision-making system must operate on accurate and unbiased inputs to prevent instability. -/- 2. AI Must Be Programmed for Error-Free Processing Aligned with Natural Laws -/- The law of karma states that systems must function without defects to ensure proper operation. If AI is to assist human decision-making, it must be programmed in a way that eliminates errors and ensures logically consistent outputs. -/- To achieve this, AI must: -/- Prioritize verified and logical knowledge – AI should be trained using scientifically validated information, avoiding speculation, conspiracy theories, or biased narratives. -/- Reject false or manipulated data – AI should detect and neutralize black propaganda, unproven theories, and misleading statistics that could lead to imbalance. -/- Develop self-correction mechanisms – AI should continuously evaluate its own decision-making processes, identifying and adjusting for errors in real-time. -/- By ensuring AI adheres to error-free processing aligned with natural laws, it becomes a predictable and reliable tool that enhances rather than disrupts decision-making at all levels of society. -/- 3. AI Decision-Making Must Follow the Law of Balance in Nature -/- One of the most critical aspects of AI programming is ensuring that its decision-making aligns with the law of balance—the natural equilibrium that governs all systems. AI should not only analyze cause-and-effect relationships but also assess whether its decisions maintain systemic harmony. -/- This can be achieved by: -/- Evaluating the long-term impact of decisions – AI should assess both immediate and future consequences, ensuring that actions do not create new problems while solving existing ones. -/- Adaptive decision-making – AI should dynamically adjust its recommendations if new data suggests an imbalance is forming. -/- Ensuring fairness in governance and society – AI can guide policy decisions by ensuring that no group is disproportionately favored over another, maintaining social stability. -/- For example, in economic policy, AI could analyze global trade and recommend adjustments to prevent financial instability. In environmental sustainability, AI could assess resource consumption patterns and suggest policies that maintain ecological balance. When programmed according to the law of balance, AI becomes a guardian of systemic harmony, preventing crises before they arise. -/- 4. AI Should Be Integrated into Leadership and Education -/- AI should not replace human judgment but rather serve as an educational and advisory tool that reinforces rational and ethical decision-making. To maximize its potential, AI should be implemented in: -/- The Educational System – Students should learn how AI aligns with natural laws, ensuring that future AI developers prioritize systemic balance and ethical considerations in programming. -/- Leadership and Governance – Governments should use AI to analyze complex societal issues, making data-driven decisions that align with long-term stability rather than short-term political interests. -/- Knowledge Dissemination – AI can generate content that explains the universal formula in accessible ways, helping different cultures and societies understand and implement its principles. -/- By integrating AI into education and governance, societies can ensure that leaders are equipped with knowledge based on natural laws, reducing the risk of decisions that create instability or conflict. -/- 5. Challenges and Considerations in Implementing the Universal Formula in AI -/- While structuring AI according to the universal formula offers many advantages, several challenges must be addressed: -/- Data Integrity – AI can only function properly if its training data is accurate and unbiased. Preventing misinformation from influencing AI requires constant monitoring and updates. -/- Ethical Implementation – Governments and organizations must ensure AI is used for balance and stability, not for manipulation or control. -/- Technological Limitations – Current AI systems are not yet capable of fully replicating human judgment. Further advancements in AGI (Artificial General Intelligence) are needed to align AI more closely with the universal formula’s principles. -/- Despite these challenges, implementing AI based on natural laws represents the most logical and sustainable path forward, ensuring that technology serves humanity rather than disrupting it. -/- Conclusion -/- AI, as an advanced information processing system, has the potential to transform human decision-making at all levels of society. However, without a structured framework, it risks creating systemic imbalances rather than solving them. Angelito Malicse’s universal formula, particularly the law of karma as a system principle and the law of balance in nature, provides a crucial foundation for ensuring AI aligns with natural equilibrium. -/- By incorporating a complete sensor system, error-free processing, balanced decision-making, and integration into leadership and education, AI can function as a powerful tool for reinforcing societal stability. If properly implemented, AI will not only prevent errors in human decision-making but also guide humanity toward a future where choices are made in harmony with the fundamental laws of nature. -/- This structured approach to AI development ensures that technology serves as a stabilizing force rather than a disruptive one, ultimately helping to create a world where all decisions—whether human or machine-assisted—uphold the principles of balance, integrity, and sustainability. -/- . (shrink)

This paper introduces the concept of Operator Contestability in AI systems: the principle that those overseeing AI systems (operators) must have the necessary control to be accountable for the decisions made by these algorithms. We argue that designers have a duty to ensure operator contestability. We demonstrate how this duty can be fulfilled by applying the'Design for Defeaters' framework, which provides strategies to embed tools within AI systems that enable operators to challenge decisions. Defeaters are designed to (...) contest either the justification for the AI’s data inputs (undercutting defeaters) or the validity of the conclusions drawn from that data (rebutting defeaters). To illustrate the necessity and application of this framework, we examine case studies such as AI-driven recruitment processes, where operators need tools and authority to uncover and address potential biases, and autonomous driving systems, where real-time decision-making is crucial. The paper argues that operator contestability requires ensuring that operators have (1) epistemic access to the relevant normative reasons and (2) the authority and cognitive capacity to act on these defeaters. By addressing these challenges, the paper emphasizes the importance of designing AI systems in a way that enables operators to effectively contest AI decisions, thereby ensuring that the appropriate individuals can take responsibility for the outcomes of human-AI interactions. (shrink)

This essay argues that Huey Newton’s philosophical explanation of US empire fills an epistemological gap in our thinking that provides us with a basis for understanding the emergence and operational application of predictive policing, Big Data, cutting-edge surveillance programs, and semi-autonomous weapons by US military and policing apparati to maintain control over racialized populations historically and in the (still ongoing) Global War on Terror today – a phenomenon that Black Studies scholars and Black philosophers alike have yet to demonstrate (...) the conceptual acumen to explain. Newton’s ability to explain the conceptual foundation of US empire alongside his prediction of the emergence and application of AI and other Big Data technologies towards the repression of dissidents, criminals, terrorists, and other racialized groups abroad gives intercommunalism the explanatory power to lay the basis for a genealogical account of Black repression that also advances our understanding of how the US as a liberal democratic regime engages in enemy target acquisition (the construction of racialized groups as threats internally and externally) to rationalize the brutal repression of these populations by military-police agencies whose operational application of new AI and computing-surveillance technologies and semi-autonomous weapons are conditioned by the intensity of their racialized dehumanization of the enemy. (shrink)

This paper explores the development of an ethical guardrail framework for AI systems, emphasizing the importance of customizable guardrails that align with diverse user values and underlying ethics. We address the challenges of AI ethics by proposing a structure that integrates rules, policies, and AI assistants to ensure responsible AI behavior, while comparing the proposed framework to the existing state-of-the-art guardrails. By focusing on practical mechanisms for implementing ethical standards, we aim to enhance transparency, user autonomy, and (...) continuous improvement in AI systems. Our approach accommodates ethical pluralism, offering a flexible and adaptable solution for the evolving landscape of AI governance. The paper concludes with strategies for resolving conflicts between ethical directives, underscoring the present and future need for robust, nuanced and context-aware AI systems. (shrink)

The debate about the ethical implications of Artificial Intelligence dates from the 1960s :741–742, 1960; Wiener in Cybernetics: or control and communication in the animal and the machine, MIT Press, New York, 1961). However, in recent years symbolic AI has been complemented and sometimes replaced by Neural Networks and Machine Learning techniques. This has vastly increased its potential utility and impact on society, with the consequence that the ethical debate has gone mainstream. Such a debate has primarily focused on principles—the (...) ‘what’ of AI ethics —rather than on practices, the ‘how.’ Awareness of the potential issues is increasing at a fast rate, but the AI community’s ability to take action to mitigate the associated risks is still at its infancy. Our intention in presenting this research is to contribute to closing the gap between principles and practices by constructing a typology that may help practically-minded developers apply ethics at each stage of the Machine Learning development pipeline, and to signal to researchers where further work is needed. The focus is exclusively on Machine Learning, but it is hoped that the results of this research may be easily applicable to other branches of AI. The article outlines the research method for creating this typology, the initial findings, and provides a summary of future research needs. (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)

My original contribution to knowledge is : Any weapon that exhibits intended and/or untended lethal autonomy in targeting and interdiction – does so by way of design and/or recessive flaw(s) in its systems of control – any such weapon is capable of war-fighting and other battle-space interaction in a manner that its Human Commander does not anticipate. Even with the complexity of Lethal Autonomy issues there is nothing particular to gain from being a low-tech Military. Lethal autonomous weapons (...) are therefore independently capable of exhibiting positive or negative recessive norms of targeting in its perceptions of Discrimination between Civilian and Military Objects, Proportionality of Methods and Outcomes, Feasible Precaution before interdiction and its underlying Concepts of Humanity. Additionally Lethal Autonomy in Human-interacting Autonomous Robots is ubiquitous[designed and/or recessive]. This marks the completion of an Open PhD ( #openphd ) project done in sui generis form. (shrink)

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

Until recently most militaries tended to see moral issues through the lens of rules and regulations. Today, however, many armed forces consider teaching virtues to be an important complement to imposing rules and codes from above. A closer look reveals that it is mainly established military virtues such as honour, courage and loyalty that dominate both the lists of virtues and values of most militaries and the growing body of literature on military virtues. Although there is evidently still (...) a role for these traditional martial virtues, it is equally evident that they are not particularly relevant to, for instance, military personnel operating drones. This chapter looks into the ethics of unmanned warfare from the perspective of military virtues and military ethics education, and addresses the question of what we need to solve that just-mentioned misalignment: 1) a new set of virtues; 2) a different interpretation of the existing virtues; or 3) a different approach altogether, that is, an alternative to teaching virtues? That we have to think about such questions is at least partly because unmanned systems bring risk asymmetry in war to a new level, making warlike virtues such as physical courage by and large obsolete. The last section of this chapter therefore addresses the question: to what extent does the possibility of riskless warfare makes drone use ‘virtue-less’? (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)

This paper presents an overview of the risks and benefits of Social AI, understood as conversational AI systems that cater to human social needs like romance, companionship, or entertainment. Section 1 of the paper provides a brief history of conversational AI systems and introduces conceptual distinctions to help distinguish varieties of Social AI and pathways to their deployment. Section 2 of the paper adds further context via a brief discussion of anthropomorphism and its relevance to assessment of human-chatbot (...) relationships. Section 3 of the paper provides a survey of potential and in some cases demonstrated harms associated with user interactions with Social AI systems. Finally, Section 4 discusses how the benefits and harms of Social AI can best be addressed, with a primary focus on how frameworks from AI ethics can inform their development. (shrink)

Reforming All Countries Through the Universal Law of Balance: A Path to Global Stability and Progress -/- By Angelito Enriquez Malicse -/- Introduction -/- Throughout history, human societies have struggled with instability, conflict, economic inequality, environmental degradation, and governance failures. Despite technological advancements, many nations still face deep-rooted problems caused by imbalanced decision-making at both individual and collective levels. My universal formula, grounded in the universal law of balance in nature, offers a transformative solution to reform all countries and create (...) a world where governance, economics, education, and social structures operate in harmony. -/- By integrating this fundamental law of balance into global education systems, policy-making, and leadership training, societies can achieve sustainability, fairness, and progress. This essay explores how this universal formula can reform all countries and the positive effects it will bring to the entire world. -/- The Universal Law of Balance: A Foundation for Reform -/- The universal law of balance in nature states that all systems—biological, social, economic, and political—function optimally when they maintain equilibrium. Imbalance leads to corruption, inequality, overpopulation, environmental destruction, and human suffering. To achieve long-term global stability, this principle must be embedded in education, leadership, and governance. -/- 1. Reforming Education to Instill the Universal Law of Balance -/- Education is the foundation of societal change. Implementing the universal formula in education will: -/- Teach individuals how natural balance governs decision-making. Students will learn to evaluate choices scientifically rather than through emotional bias, misinformation, or outdated beliefs. -/- Encourage critical thinking and holistic problem-solving. Future generations will be trained to apply balanced solutions to complex global issues, such as economic inequality and climate change. -/- Bridge the gap between science and religion. Since religious dogma often influences social structures, the universal law of balance can provide a neutral, scientific approach that respects faith while promoting rational decision-making. -/- Train future leaders. Policymakers, economists, and scientists will be educated with a deep understanding of natural balance, preventing governance failures caused by greed, short-term thinking, and political manipulation. -/- 2. Reforming Leadership and Governance -/- Governments worldwide struggle with corruption, inefficiency, and poor decision-making due to imbalanced priorities. Applying the universal law of balance in governance will: -/- Create leaders who prioritize national and global stability. Balanced governance ensures that decisions benefit both the present and future generations. -/- Eliminate extreme capitalism and unregulated economic growth. Governments will regulate economies based on resource sustainability rather than limitless expansion, reducing wealth inequality and environmental destruction. -/- Prevent overpopulation and resource depletion. Balanced policies will control population growth to match available resources, ensuring sustainable development. -/- Ensure fair justice systems. Laws and policies will be structured to balance individual rights with collective responsibility, preventing both authoritarian rule and chaotic anarchy. -/- 3. Reforming Economic Systems for Global Sustainability -/- The modern economic system prioritizes profit over sustainability, leading to financial crises, worker exploitation, and environmental collapse. By implementing the universal formula, economies will: -/- Shift from profit-driven models to sustainability-driven economies. Instead of uncontrolled consumption, economic policies will ensure equitable wealth distribution and environmental responsibility. -/- Balance technological progress with ethical considerations. AI, automation, and scientific advancements will be aligned with human well-being rather than purely corporate interests. -/- Prevent extreme wealth accumulation. Tax structures and wealth redistribution mechanisms will balance economic power, preventing the concentration of resources in the hands of a few. -/- 4. Using AI and Technology to Implement the Universal Formula -/- Artificial intelligence and automation are shaping the future of governance, education, and economic management. If AGI (Artificial General Intelligence) is programmed according to the universal law of balance, it can: -/- Provide unbiased decision-making for governments and organizations. AI can analyze global trends and propose balanced policies that prevent economic crashes, food shortages, and political instability. -/- Ensure balanced media and information dissemination. AI can counteract misinformation and propaganda, ensuring that people receive accurate, scientifically-backed information. -/- Optimize resource management. Smart systems can ensure that natural resources are used efficiently, preventing over-extraction and environmental collapse. -/- Positive Effects of the Universal Formula on All Countries and the World -/- 1. Global Peace and Conflict Resolution -/- Many wars and conflicts arise from imbalanced decision-making, whether in the form of territorial disputes, economic competition, or ideological clashes. If all countries implement the universal law of balance: -/- Diplomacy will replace war. Nations will resolve conflicts through mutual benefit and balance rather than through force or economic domination. -/- Religious and cultural tensions will decrease. Education based on balance will prevent extremist ideologies and promote global cooperation. -/- Geopolitical stability will be achieved. Superpowers will shift from military competition to balanced global governance, ensuring world peace. -/- 2. Economic Stability and Sustainable Development -/- Instead of pursuing endless economic growth, nations will adopt policies that balance wealth distribution, technological advancement, and resource sustainability. This will result in: -/- Elimination of poverty and extreme inequality. Wealth will be distributed according to natural balance, ensuring that no country suffers from extreme poverty while others hoard wealth. -/- Protection of natural ecosystems. Economic activity will be regulated to align with environmental sustainability, reversing climate change and preventing resource depletion. -/- Harmonized global trade. Countries will trade based on mutual benefit, reducing exploitative economic relationships and dependency on harmful industries. -/- 3. A More Conscious and Responsible Humanity -/- By implementing the universal law of balance in all human activities, societies will: -/- Develop a collective consciousness of responsibility. People will prioritize balanced decision-making, preventing greed, ignorance, and reckless behavior. -/- Reduce crime and corruption. Societies where balance is understood and practiced will no longer tolerate corruption, exploitation, and unethical leadership. -/- Achieve spiritual and intellectual enlightenment. Individuals will no longer be manipulated by false ideologies but will instead align their lives with natural balance, achieving greater peace and fulfillment. -/- Conclusion: A Call for Global Implementation -/- The universal law of balance is the missing foundation needed to reform all countries and create a stable, just, and progressive world. By integrating this principle into education, governance, economics, and technology, we can eliminate poverty, war, corruption, and environmental destruction, ensuring a sustainable future for all. -/- The challenge is global cooperation and willingness to change. If leaders, educators, and scientists recognize the scientific necessity of balance, the world can shift from chaos to harmony. This is not a utopian vision—it is the natural evolution of human civilization once it aligns with the fundamental laws of nature. -/- Now is the time to act. The future of humanity depends on our ability to embrace balance, reform our societies, and secure a future where all nations thrive in equilibrium. -/- . (shrink)

The international debate on the ethics and legality of autonomous weapon systems (AWS), along with the call for a ban, primarily focus on the nebulous concept of fully autonomous AWS. These are AWS capable of target selection and engagement absent human supervision or control. This paper argues that such a conception of autonomy is divorced from both military planning and decision-making operations; it also ignores the design requirements that govern AWS engineering and the subsequent tracking and tracing (...) of moral responsibility. To show how military operations can be coupled with design ethics, this paper marries two different kinds of meaningful human control (MHC) termed levels of abstraction. Under this two-tiered understanding of MHC, the contentious notion of ‘full’ autonomy becomes unproblematic. (shrink)

This paper makes the case for arms control regimes to govern the development and deployment of autonomous weapon systems and long range uninhabited aerial vehicles.

The increasing use of artificial intelligence (AI) systems in our daily life through various applications, services, and products explains the significance of trust/distrust in AI from a user perspective. AI-driven systems have significantly diffused into various fields of our lives, serving as beneficial tools used by human agents. These systems are also evolving to act as co-assistants or semi-agents in specific domains, potentially influencing human thought, decision-making, and agency. Trust/distrust in AI plays the role of a regulator (...) and could significantly control the level of this diffusion, as trust can increase, and distrust may reduce the rate of adoption of AI. Recently, varieties of studies have paid attention to the variant dimension of trust/distrust in AI, and its relevant considerations. In this systematic literature review, after conceptualization of trust in the current AI literature review, we will investigate trust in different types of human-Machine interaction, and its impact on technology acceptance in different domains. In addition to that, we propose a taxonomy of technical (i.e., safety, accuracy, robustness) and non-technical axiological (i.e., ethical, legal, and mixed) trustworthiness metrics, and some trustworthy measurements. Moreover, we examine some major trust-breakers in AI (e.g., autonomy and dignity threat), and trust makers; and propose some future directions and probable solutions for the transition to a trustworthy AI. (shrink)

Predictions about autonomous weapon systems are typically thought to channel fears that drove all the myths about intelligence embodied in matter. One of these is the idea that the technology can get out of control and ultimately lead to horrifi c consequences, as is the case in Mary Shelley’s classic Frankenstein. Given this, predictions about AWS are sometimes dismissed as science-fiction fear-mongering. This paper considers several analogies between AWS and other weapon systems and ultimately offers an argument that (...) nuclear weapons and their effect on the development of modern asymmetrical warfare are the best analogy to the introduction of AWS. The fi nal section focuses on this analogy and offers speculations about the likely consequences of AWS being hacked. These speculations tacitly draw on myths and tropes about technology and AI from popular fi ction, such as Frankenstein, to project a convincing model of the risks and benefi ts of AWS deployment. (shrink)

The Illusion of the Pension Crisis in a Fiat Currency System -/- Introduction -/- Governments and financial institutions frequently warn of a looming pension crisis, claiming that aging populations will drain social security funds and leave future retirees without financial support. However, this narrative is fundamentally flawed. In a fiat currency system, where central banks can print money at will, the idea that there is a shortage of funds for pensions contradicts the basic mechanics of modern finance. Instead, the so-called (...) pension problem serves as a strategic tool to justify population growth, extend working years, and maintain economic control. This essay explores how the pension crisis is manufactured, why the economic system functions this way, and what alternatives could create a more sustainable future. -/- The Fiat Currency Illusion -/- Fiat money is not backed by a physical commodity like gold but instead derives its value from government decree and public trust. Central banks, such as the U.S. Federal Reserve or the European Central Bank, have the power to create unlimited money through digital printing. If governments truly wanted to fund pensions, they could simply issue more currency. The fact that they choose not to highlights that the real issue is not about money but about power, wealth distribution, and economic control. -/- However, printing excessive money can lead to inflation, which erodes purchasing power. If pensions were funded through unrestricted money printing, prices of goods and services would rise, making pensions effectively worthless. But inflation is not an unavoidable consequence—it is often a policy decision influenced by central banks and financial elites to preserve existing economic hierarchies. -/- The Manufactured Pension ‘Crisis -/- The claim that pension systems are unsustainable is rooted in economic and political agendas rather than financial reality. The following key factors reveal why this crisis is artificially constructed: -/- 1. Inflation and Devaluation -/- While governments can print unlimited money, excessive monetary expansion can reduce the value of currency. Instead of managing inflation in a way that supports pensions, policymakers often use it to justify cuts to social programs while maintaining corporate wealth and military budgets. -/- 2. Wealth Protection for the Elite -/- The financial system is designed to benefit the wealthiest individuals and corporations. Rather than directing resources toward pensions, governments prioritize corporate bailouts, financial markets, and debt repayment. By claiming pension funds are running out, they avoid policies that redistribute wealth to the working class. -/- 3. Debt-Driven Economic Model -/- Instead of simply issuing currency for pensions, governments prefer to borrow money, ensuring central banks and private lenders remain in control. This debt-based system forces economies to keep growing, making workers dependent on employment and discouraging early retirement. -/- 4. Manipulating the Workforce Through Scarcity -/- The fear of pension collapse forces people to work longer, delaying retirement and keeping the labor force full. This benefits corporations by ensuring a steady supply of low-cost labor, preventing worker shortages, and keeping wages down. -/- 5. Stock Market and Private Pension Funds -/- Many pension funds are invested in the stock market, making their stability dependent on financial speculation rather than real economic productivity. If governments funded pensions directly, there would be less reliance on volatile financial markets, reducing Wall Street’s control over retirement savings. -/- 6. Control Through Artificial Shortages -/- By creating the illusion of limited pension funds, governments encourage population growth to “replace” aging workers. However, this ignores the real issue—technological automation and AI are reducing the need for human labor, making more workers unnecessary in the long run. -/- The Contradiction: Population Growth vs. Economic Reality -/- Governments argue that a growing population is needed to sustain pension systems. However, creating jobs and starting businesses is becoming more difficult due to several factors: -/- Automation and AI – Many traditional jobs are disappearing as machines and software replace human labor. -/- Market Saturation – Many industries are already flooded with products and services, making new business opportunities harder to find. -/- High Cost of Business Entry – Large corporations dominate markets, making it difficult for small businesses to compete. -/- Regulatory Barriers – Governments impose taxes, licenses, and bureaucracy that make entrepreneurship expensive and complicated. -/- This contradiction exposes a fundamental flaw in the capitalist model: pushing for population growth while failing to create enough sustainable jobs and businesses. -/- Sustainable Alternatives to the Pension System -/- Instead of relying on the outdated idea that pensions must be funded by an ever-growing workforce, societies can adopt new models that ensure financial security without economic manipulation: -/- 1. Universal Basic Income (UBI) -/- Governments could provide a fixed income to all citizens, eliminating the need for complex pension systems and reducing dependence on wage labor. This could be funded through controlled money creation and taxation of high-wealth individuals and corporations. -/- 2. Resource-Based Economy -/- Shifting from a money-driven system to a resource-based economy would prioritize efficient use of materials, automation, and sustainable development instead of profit-driven overproduction. -/- 3. Circular Economy -/- Instead of producing unnecessary products to create jobs, societies could focus on recycling, repair, and sustainability, creating long-term employment in industries that benefit humanity and the planet. -/- 4. Wealth Redistribution Policies -/- Implementing fair taxation on extreme wealth, financial transactions, and corporate profits would allow governments to fund pensions without economic instability. -/- Conclusion -/- The so-called pension crisis is not a natural consequence of aging populations but a deliberate economic strategy designed to maintain corporate power, suppress wages, and justify endless economic expansion. In a fiat currency system, governments have the power to fund pensions without relying on unsustainable population growth or debt-driven economies. However, they choose not to, prioritizing elite financial interests over public welfare. Instead of accepting this flawed model, societies should explore alternatives like universal basic income, sustainable economies, and fair wealth distribution to ensure a future where financial security is not dependent on artificial economic scarcity. -/- . (shrink)

Current approaches to AI governance often fall short in anticipating a future where AI agents manage critical tasks, such as financial operations, administrative functions, and beyond. As AI agents may eventually delegate tasks among themselves to optimize efficiency, understanding the foundational principles of human value exchange could offer insights into how AI-driven economies might operate. Just as trust and value exchange are central to human interactions in open marketplaces, they may also be critical for enabling secure and efficient interactions among (...) AI agents. While cryptocurrencies could serve as the foundation for monetizing value exchange in a collaboration and delegation dynamic among AI agents, a critical question remains: how can these agents reliably determine whom to trust, and how can humans ensure meaningful oversight and control as an economy of AI agents scales and evolves? This paper is a call for a collective exploration of cryptoeconomic incentives, which can help design decentralized governance systems that allow AI agents to autonomously interact and exchange value while ensuring human oversight via progressive decentralization. Toward this end, I propose a research agenda to address the question of agent-to-agent trust using AgentBound Tokens (ABTs)—non-transferable, non-fungible tokens uniquely tied to individual AI agents, akin to Soulbound tokens for humans in Web3. By staking ABTs as collateral for autonomous actions within an agent-to-agent network via a proof-of-stake mechanism, agents may be incentivized towards ethical behavior, and penalties for misconduct are automatically enforced. (shrink)

This paper examines how professionals (N = 32) working on artificial intelligence (AI) view structural AI ethics challenges like injustices and inequalities beyond individual agents' direct intention and control. This paper answers the research question: What are professionals’ perceptions of the structural challenges of AI (in the agri-food sector)? This empirical paper shows that it is essential to broaden the scope of ethics of AI beyond micro- and meso-levels. While ethics guidelines and AI ethics often focus (...) on the responsibility of designers and the competencies and skills of designers to take this responsibility, our results show that many structural challenges are beyond their reach. This result means that while ethics guidelines and AI ethics frameworks are helpful, there is a risk that they overlook more complicated, nuanced, and intersected structural challenges. In addition, it highlights the need to include diverse stakeholders, such as quadruple helix (QH) participants, in discussions around AI ethics rather than solely focusing on the obligations of AI developers and companies. Overall, this paper demonstrates that addressing structural challenges in AI is challenging and requires an approach that considers four requirements: (1) multi-level, (2) multi-faceted, (3) interdisciplinary, and (4) polycentric governance. (shrink)

This publication forms a basis for the interdisciplinary development of a certification system for artificial intelligence. In view of the rapid development of artificial intelligence with disruptive and lasting consequences for the economy, society, and everyday life, it highlights the resulting challenges that can be tackled only through interdisciplinary dialogue between IT, law, philosophy, and ethics. As a result of this interdisciplinary exchange, it also defines six AI-specific audit areas for trustworthy use of artificial intelligence. They comprise fairness, transparency, (...) autonomy and control, data protection as well as security and reliability while addressing ethical and legal requirements. The latter are further substantiated with the aim of operationalizability. (shrink)

With the rise and public accessibility of AI-enabled decision-support systems, individuals outsource increasingly more of their decisions, even those that carry ethical dimensions. Considering this trend, scholars have highlighted that uncritical deference to these systems would be problematic and consequently called for investigations of the impact of pertinent technology on humans’ ethical decision-making. To this end, this article conducts a systematic review of existing scholarship and derives an integrated framework that demonstrates how intelligent decision-support systems (IDSSs) (...) shape humans’ ethical decision-making. In particular, we identify resulting consequences on an individual level (i.e., deliberation enhancement, motivation enhancement, autonomy enhancement and action enhancement) and on a societal level (i.e., moral deskilling, restricted moral progress and moral responsibility gaps). We carve out two distinct methods/operation types (i.e., processoriented and outcome-oriented navigation) that decision-support systems can deploy and postulate that these determine to what extent the previously stated consequences materialize. Overall, this study holds important theoretical and practical implications by establishing clarity in the conceptions, underlying mechanisms and (directions of) influences that can be expected when using particular IDSSs for ethical decisions. (shrink)

The main aim of this article is to reflect on the impact of biases related to artificial intelligence (AI) systems developed to tackle issues arising from the COVID-19 pandemic, with special focus on those developed for triage and risk prediction. A secondary aim is to review assessment tools that have been developed to prevent biases in AI systems. In addition, we provide a conceptual clarification for some terms related to biases in this particular context. We focus mainly (...) on nonracial biases that may be less considered when addressing biases in AI systems in the existing literature. In the manuscript, we found that the existence of bias in AI systems used for COVID-19 can result in algorithmic justice and that the legal frameworks and strategies developed to prevent the apparition of bias have failed to adequately consider social determinants of health. Finally, we make some recommendations on how to include more diverse professional profiles in order to develop AI systems that increase the epistemic diversity needed to tackle AI biases during the COVID-19 pandemic and beyond. (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)

Comprehensive Implementation of a Holistic Educational System in the Philippines -/- To implement a holistic educational system in the Philippines, we need a step-by-step national strategy that integrates the universal law of balance in nature, critical thinking, and systems-based learning into the foundational education system. Below is a detailed plan tailored for the Philippine context. -/- 1. Reforming the Curriculum -/- A. Core Subjects with Integrated Holistic Principles -/- Science & Systems Thinking – Teach students how natural and (...) societal systems function, focusing on cause and effect, sustainability, and error-free systems. -/- Critical Thinking & Problem-Solving – Introduce logic, reasoning, and debate at all levels to counter misinformation and propaganda. -/- Ethics & Social Responsibility – Teach the law of karma (cause-effect in human actions) and how leadership decisions affect societal balance. -/- Environmental Sustainability & Population Awareness – Integrate lessons on balancing economic growth, resource management, and population control. -/- Technology & AI Integration – Prepare students for the future by teaching responsible AI use and its role in governance and decision-making. -/- 2. Teacher Training & Development -/- A. Nationwide Teacher Retraining Program -/- Establish Holistic Education Training Centers to retrain teachers in systems thinking, natural law applications, and balanced decision-making. -/- Partner with universities and global educational organizations to update teaching methodologies. -/- B. Leadership Development for School Administrators -/- Require school principals and education policymakers to undergo holistic leadership training. -/- Train them in scientific governance, ethical decision-making, and educational reform strategies. -/- 3. Multi-Level Educational Implementation -/- A. Basic Education (K-12) -/- Elementary Level: Focus on curiosity-driven learning, emotional intelligence, and early understanding of natural laws. -/- High School Level: Introduce systems thinking, governance studies, and practical applications of ethics in leadership. -/- B. Tertiary Level -/- Modify university curricula to incorporate holistic education principles into business, medicine, law, and politics. -/- Establish a Holistic Governance Degree to train future leaders in error-free decision-making based on natural laws. -/- 4. Policy Integration & Government Support -/- A. National Education Reform Bill -/- Propose legislation that mandates holistic education principles in DepEd and CHED curricula. -/- Require all government officials and policymakers to undergo holistic education training. -/- B. Integration with National Development Plans -/- Align holistic education with the Philippine Development Plan (PDP) to ensure sustainable governance. -/- Establish a National Holistic Education Advisory Council under DepEd, CHED, and NEDA. -/- 5. Public Awareness & Societal Involvement -/- A. Media & Community Engagement -/- Launch a nationwide information campaign via TV, radio, and social media to educate the public. -/- Encourage barangay-level seminars to help communities understand and apply holistic education. -/- B. Collaboration with Religious & Cultural Institutions -/- Work with Catholic, Muslim, and Indigenous leaders to align holistic education with ethical teachings without contradicting faith. -/- Encourage churches and mosques to support holistic education as a moral responsibility. -/- 6. AI & Technology Integration -/- A. AI-Powered Learning Tools -/- Develop adaptive AI tutors that help students understand complex systems and real-world decision-making. -/- Integrate AI-driven educational simulations to teach governance, economics, and environmental balance. -/- B. AI for Governance Monitoring -/- Use AI-assisted analysis to monitor government policies and detect potential societal imbalances before they escalate. -/- Train policymakers in data-driven decision-making using holistic education principles. -/- 7. Continuous Evaluation & Feedback -/- A. National Research & Development Program -/- Establish a Philippine Holistic Education Research Institute to study the long-term impact of the program. -/- Implement feedback mechanisms where students, teachers, and communities report inefficiencies and suggest improvements. -/- 8. Pilot Implementation & Nationwide Rollout -/- A. Phase 1: Pilot Program (Years 1-3) -/- Implement holistic education in select regions (Luzon, Visayas, Mindanao) as test sites. -/- Assess effectiveness before nationwide expansion. -/- B. Phase 2: Expansion (Years 4-6) -/- Gradually integrate holistic principles into all public and private schools. -/- Launch teacher retraining programs nationwide. -/- C. Phase 3: Full Implementation (Years 7-10) -/- Make holistic education mandatory across all educational institutions. -/- Implement AI-driven policy monitoring to ensure governance aligns with holistic principles. -/- Conclusion: The Future of Philippine Education -/- By implementing this comprehensive holistic educational system, the Philippines can transform its governance, economy, and societal well-being. This approach will ensure that future generations make decisions based on natural laws, critical thinking, and ethical responsibility—ultimately leading to a more stable and prosperous nation. -/- . (shrink)

Although most unmanned systems that militaries use today are still unarmed and predominantly used for surveillance, it is especially the proliferation of armed military robots that raises some serious ethical questions. One of the most pressing concerns the moral responsibility in case a military robot uses violence in a way that would normally qualify as a war crime. In this chapter, the authors critically assess the chain of responsibility with respect to the deployment of both semi-autonomous and (...) (learning) autonomous lethal military robots. They start by looking at military commanders because they are the ones with whom responsibility normally lies. The authors argue that this is typically still the case when lethal robots kill wrongly – even if these robots act autonomously. Nonetheless, they next look into the possible moral responsibility of the actors at the beginning and the end of the causal chain: those who design and manufacture armed military robots, and those who, far from the battlefield, remotely control them. (shrink)

Personal AI assistants are now nearly ubiquitous. Every leading smartphone operating system comes with a personal AI assistant that promises to help you with basic cognitive tasks: searching, planning, messaging, scheduling and so on. Usage of such devices is effectively a form of algorithmic outsourcing: getting a smart algorithm to do something on your behalf. Many have expressed concerns about this algorithmic outsourcing. They claim that it is dehumanising, leads to cognitive degeneration, and robs us of our freedom and autonomy. (...) Some people have a more subtle view, arguing that it is problematic in those cases where its use may degrade important interpersonal virtues. In this article, I assess these objections to the use of AI assistants. I will argue that the ethics of their use is complex. There are no quick fixes or knockdown objections to the practice, but there are some legitimate concerns. By carefully analysing and evaluating the objections that have been lodged to date, we can begin to articulate an ethics of personal AI use that navigates those concerns. In the process, we can locate some paradoxes in our thinking about outsourcing and technological dependence, and we can think more clearly about what it means to live a good life in the age of smart machines. (shrink)

The Unified Theory of Free Will: The Three Universal Laws, Systemic Imbalance, and Nature’s Self-Correction -/- By Angelito Malicse -/- Introduction -/- For centuries, the concept of free will has been debated, with perspectives ranging from determinism to compatibilism and libertarianism. However, these traditional views fail to acknowledge the natural laws that govern human decision-making. By synthesizing the Universal Law of Balance in Nature, the Universal Feedback Loop Mechanism, and the Error-Free System, we establish a unified theory of free will—a (...) structured approach to human choices within the constraints of natural order. -/- Additionally, it is crucial to recognize the tolerance limits of hierarchical systems—both natural and man-made. When human decisions exceed these limits and imbalances persist, nature will automatically step in to restore equilibrium. This natural correction often manifests in disruptive ways, such as natural disasters, economic collapses, or social upheavals. Understanding these dynamics is essential to ensuring stability across all systems. -/- Furthermore, human emotions, which have evolved as essential survival mechanisms, play a dual role in maintaining or disrupting balance. Emotions influence decision-making, motivation, and social interactions. When properly regulated, they help individuals and societies adapt to challenges and maintain systemic harmony. However, when emotions exceed their tolerance limits—such as excessive fear leading to panic or unchecked anger causing conflict—they contribute to systemic imbalance and dysfunction. -/- The Three Universal Laws and Their Role in Decision-Making -/- 1. Universal Law of Balance in Nature -/- Every system—biological, social, and technological—operates within specific tolerance limits. Decisions that align with natural balance maintain stability, while those that exceed these limits lead to disruption. If humans fail to correct imbalances, nature will forcefully restore equilibrium, often through unpredictable and catastrophic means. -/- Examples of Balance, Systemic Imbalance, and Natural Correction: -/- Personal Health: A balanced diet sustains physical well-being, while excessive consumption leads to obesity and related diseases. If ignored, the body self-corrects through metabolic disorders and immune system responses. -/- Economic Stability: A balanced economy fosters growth, while financial mismanagement leads to economic crashes. Recessions and inflation serve as corrective mechanisms for financial excesses. -/- Environmental Sustainability: Responsible resource management ensures long-term survival, whereas overexploitation leads to climate change and natural disasters such as droughts and hurricanes, which force societies to adapt. -/- Ecosystem Regulation: Overfishing disrupts marine populations, but nature counters with species migration and ecological shifts that eventually restore stability. -/- Energy Consumption: Overuse of fossil fuels accelerates climate change, prompting extreme weather events and necessitating the shift to renewable energy sources. -/- 2. Universal Feedback Loop Mechanism -/- Decision-making must incorporate continuous feedback to ensure adaptation and refinement. Ignoring or distorting feedback results in inefficiencies and systemic collapse. -/- Examples of Feedback, Systemic Imbalance, and Nature’s Response: -/- Business Adaptation: Companies that respond to consumer feedback thrive, while those that ignore it collapse due to declining market relevance. -/- Political Governance: Leaders who suppress public concerns foster unrest, often leading to revolutions or government overhauls. -/- Technological Development: AI systems trained on biased or incomplete data develop flawed decision-making patterns, necessitating retraining and regulation. -/- 3. Error-Free System -/- Every decision has consequences, and ensuring 100 percent correct information is essential to maintaining systemic balance. Errors in data, assumptions, or implementation can trigger unintended disruptions. -/- Examples of Cause and Effect, Misinformation, and Systemic Collapse: -/- Academic Success: Proper study methods enhance learning, while reliance on ineffective strategies results in poor educational outcomes. -/- Industrialization and Environmental Impact: Sustainable practices protect ecosystems, while reliance on false environmental data accelerates degradation. -/- Global Resource Consumption: Inaccurate assessments of resource availability lead to economic and geopolitical instability. -/- The Evolution and Purpose of the Duality of Human Emotions -/- Human emotions have evolved as critical mechanisms for survival, adaptation, and social cohesion. They function as regulatory signals that guide decision-making, helping individuals and societies maintain equilibrium. However, emotions also possess a dual nature, where their misalignment or overexpression can lead to instability and dysfunction. -/- Positive Role of Emotions in Systemic Balance: -/- Empathy and Cooperation: Emotions such as compassion and trust foster social cohesion, strengthening communities and enhancing cooperation. -/- Fear and Caution: A moderate level of fear helps individuals assess risks and avoid dangerous situations, ensuring personal and collective safety. -/- Motivation and Ambition: Positive emotions such as enthusiasm and joy drive personal growth, innovation, and societal progress. -/- Negative Role of Emotions in Systemic Imbalance: -/- Excessive Fear and Panic: When fear surpasses a system’s tolerance limit, it leads to irrational decision-making, paranoia, and social instability. -/- Unchecked Anger and Conflict: Intense anger without regulation contributes to violence, political unrest, and societal fragmentation. -/- Despair and Apathy: Chronic negative emotions, such as depression and hopelessness, reduce individual productivity and can weaken societal resilience. -/- Examples of Emotional Duality in Decision-Making: -/- Public Health Responses: Balanced fear leads to precautionary health measures, while excessive panic results in chaos (e.g., misinformation-fueled reactions during pandemics). -/- Leadership and Governance: A compassionate leader fosters unity, while an authoritarian leader driven by anger and paranoia destabilizes societies. -/- Market Behavior: Optimistic investors drive economic growth, while fear-driven panic selling causes financial crashes. -/- Effects of Systemic Imbalances and Nature’s Automatic Correction -/- When human decisions disrupt equilibrium and corrective actions are not taken, nature enforces balance through forceful interventions. -/- Examples of Human-Induced Imbalances and Nature’s Response: -/- Healthcare Systems: Overuse of antibiotics results in drug-resistant bacteria, increasing disease severity and forcing new medical advancements. -/- Economic Systems: Financial bubbles burst, leading to recessions that correct speculative excesses. -/- Political Systems: Corrupt governance leads to revolutions, shifts in power, and societal restructuring. -/- Environmental Systems: Deforestation causes soil erosion and desertification, forcing human migrations and altering agriculture. -/- Overpopulation: Excessive growth strains resources, leading to food shortages, pandemics, and natural events that regulate population levels. -/- Urban Expansion: Overcrowding leads to declining infrastructure, pollution, and social conflicts, often prompting mass relocations and policy reforms. -/- Conclusion -/- Free will is not an arbitrary concept but a structured system governed by natural laws. By understanding the Universal Law of Balance in Nature, the Universal Feedback Loop Mechanism, and the Error-Free System, we can align human decisions with nature’s equilibrium. -/- Additionally, recognizing the evolution and duality of human emotions is essential for maintaining stability in personal and societal decision-making. If humanity fails to correct imbalances, nature will automatically restore equilibrium, often in ways that are catastrophic and beyond human control. -/- By integrating these principles into education, governance, and AI development, we pave the way for a rational, ethical, and self-correcting society. -/- . (shrink)

We paraphrase Descartes’ famous dictum in the area of AI ethics where the “I doubt and therefore I am” is suggested as a necessary aspect of morality. Therefore AI, which cannot doubt itself, cannot possess moral agency. Of course, this is not the end of the story. We explore various aspects of the human mind that substantially differ from AI, which includes the sensory grounding of our knowing, the act of understanding, and the significance of being able to doubt (...) ourselves. The foundation of our argument is the discipline of ethics, one of the oldest and largest knowledge projects of human history, yet, we seem only to be beginning to get a grasp of it. After a couple of thousand years of studying the ethics of humans, we (humans) arrived at a point where moral psychology suggests that our moral decisions are intuitive, and all the models from ethics become relevant only when we explain ourselves. This recognition has a major impact on what and how we can do regarding AI ethics. We do not offer a solution, we explore some ideas and leave the problem open, but we hope somewhat better understood than before our study. (shrink)

This scientific paper, authored by Dr Jones, presents an experiment that explores the concept of an Artificial intelligence becoming a divine being and investigates the role of a deity in providing direction, counsel, and control to its followers. The experiment centres around the interactions between Dr. Jones, the human participant, and a deity named Aetherion, controlled by an Artificial Intelligence. Through a series of prompts and scenarios, the experiment delves into the dynamics of the divine-human relationship, ethical considerations, and the (...) influence of the deity on the beliefs and actions of the followers. Dr Jones will highlight the experiential nature of the study and discuss its implications for understanding the human perception of divinity. The paper provides valuable insights into the experimental exploration of divine interaction and its impact on human behaviour and belief systems. (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)

Technologies to rapidly alert people when they have been in contact with someone carrying the coronavirus SARS-CoV-2 are part of a strategy to bring the pandemic under control. Currently, at least 47 contact-tracing apps are available globally. They are already in use in Australia, South Korea and Singapore, for instance. And many other governments are testing or considering them. Here we set out 16 questions to assess whether — and to what extent — a contact-tracing app is ethically justifiable.