This argument explores the transformative potential of AI-driven legislative simulations for creating inclusive, equitable, and globally adaptable laws. By using predictive modeling and adaptive frameworks, these simulations can account for diverse cultural, social, and economic contexts. The argument emphasizes the need for universal ethical safeguards, trust-building measures, and phased implementation strategies. Case studies of successful applications in governance and conflict resolution demonstrate the feasibility and efficacy of this approach. The conclusion highlights AI’s role in democratizing (...) governance and ensuring laws are more equitable and culturally sensitive. (shrink)

Autonomous AI agents present transformative opportunities and significant governance challenges. Existing frameworks, such as the EU AI Act and the NIST AI Risk Management Framework, fall short of addressing the complexities of these agents, which are capable of independent decision-making, learning, and adaptation. To bridge these gaps, we propose the ETHOS (Ethical Technology and Holistic Oversight System) framework—a decentralized governance (DeGov) model leveraging Web3 technologies, including blockchain, smart contracts, and decentralized autonomous organizations (DAOs). ETHOS establishes a global (...) registry for AI agents, enabling dynamic risk classification, proportional oversight, and automated compliance monitoring through tools like soulbound tokens and zero-knowledge proofs. Furthermore, the framework incorporates decentralized justice systems for transparent dispute resolution and introduces AI-specific legal entities to manage limited liability, supported by mandatory insurance to ensure financial accountability and incentivize ethical design. By integrating philosophical principles of rationality, ethical grounding, and goal alignment, ETHOS aims to create a robust research agenda for promoting trust, transparency, and participatory governance. This innovative framework offers a scalable and inclusive strategy for regulating AI agents, balancing innovation with ethical responsibility to meet the demands of an AI-driven future. (shrink)

The AI Contribution Value System Argument proposes a framework in which AI-generated contributions are valued based on their societal impact rather than traditional monetary metrics. Traditional economic systems often fail to capture the enduring value of AI innovations, which can mitigate pressing global challenges. This argument introduces a contribution-based valuation model grounded in equity, inclusivity, and sustainability. By incorporating measurable metrics such as quality-adjusted life years (QALYs), emissions reduced, and innovations generated, this system ensures rewards align with tangible societal (...) benefits. It emphasizes the need for global collaboration, ethical safeguards, and adaptive frameworks to prevent monopolization and corruption. Through AI-enhanced transparency, blockchain-based trust mechanisms, and cross-border cooperation, the AI Contribution Value System offers a transformative approach to fostering sustainable and equitable innovation in the 21st century. (shrink)

The Moral Argument for AI Ethics emphasizes the need for an adaptive, globally equitable, and philosophically grounded framework for the ethical development and deployment of artificial intelligence. It highlights key principles, including dynamic adaptation to societal values, inclusivity, and the mitigation of global disparities. Drawing from historical AI ethical failures, the argument underscores the urgency of proactive and enforceable frameworks addressing bias, surveillance, and existential threats. The conclusion advocates for international coalitions that integrate diverse philosophical traditions and practical (...) implementation strategies, ensuring AI’s role as a force for global good. (shrink)

Surveillance programs supporting the management of One Health issues such as antibiotic resistance are complex systems in themselves. Designing ethical surveillance systems is thus a complex task (retroactive and iterative), yet one that is also complicated to implement and evaluate (e.g., sharing, collaboration, and governance). The governance of health surveillance requires attention to ethical concerns about data and knowledge (e.g., performance, trust, accountability, and transparency) and empowerment ethics, also referred to as a form of responsible self-governance. Ethics in reflexive (...) governance operates as a systematic critical-thinking procedure that aims to define its value: What are the “right” criteria to justify how to govern “good” actions for a “better” future? The objective is to lay the foundations for a methodological framework in empirical bioethics, the rudiments of which have been applied to a case study to building reflexive governance in One Health. This ongoing critical thinking process involves “mapping, framing, and shaping” the dynamics of interests and perspectives that could jeopardize a “better” future. This paper proposes to hybridize methods to combine insights from collective deliberation and expert evaluation through a reflexive governance functioning as a community-based action-ethics methodology. The intention is to empower individuals and associations in a dialogue with society, which operation is carried out using a case study approach on data sharing systems. We based our reasoning on a feasibility study conducted in Québec, Canada (2018–2021), envisioning an antibiotic use surveillance program in animal health for 2023. Using the adaptive cycle and governance techniques and perspectives, we synthesize an alternative governance model rooted in the value of empowerment. The framework, depicted as a new “research and design (R&D)” practice, is linking operation and innovation by bridging the gap between Reflexive, Evaluative, and Deliberative reasonings and by intellectualizing the management of democratizing critical thinking locally (collective ethics) by recognizing its context (social ethics). Drawing on the literature in One Health and sustainable development studies, this article describes how a communitarian and pragmatic approach can broaden the vision of feasibility studies to ease collaboration through public-private-academic partnerships. The result is a process that “reassembles” the One Health paradigm under the perspective of global bioethics to create bridges between the person and the ecosystem through pragmatic ethics. (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)

The field of AI ethics during the current and previous decade is receiving an increasing amount of attention from all involved stakeholders: the public, science, philosophy, religious organizations, enterprises, governments, and various organizations. However, this field currently lacks consensus on scope, ethico-philosophical foundations, or common methodology. This thesis aims to contribute towards filling this gap by providing an answer to the two main research questions: first, what theory can explain moral scenarios in which AI entities are participants?; and second, what (...) theory can explain the process of moral reasoning, decision and action, for AI entities in virtual, simulated and real-life moral scenarios? This thesis answers these two research questions with its two main contributions to the field of AI ethics, a substantial and a methodological contribution. The substantial contribution is a coherent and novel theory named Ethics of Systems Framework, as well as a possible inception of a new field of study: ethics of systems. The methodological contribution is the creation of its main methodological tool, the Ethics of Systems Interface. The second part of the research effort was focused on testing and demonstrating the capacities of the Ethics of Systems Framework and Interface in modeling and managing moral scenarios in which AI and other entities participate. Further work can focus on building on top of the foundations of the Framework provided here, increasing the scope of moral theories and simulated scenarios, improving the level of detail and parameters to reflect real-life situations, and field-testing the Framework on actual AI systems. (shrink)

-/- 1. Thermodynamic Entropy and Balance in Nature -/- Thermodynamic Entropy in physics measures the level of disorder in a system, reflecting the natural tendency of energy to spread and systems to become more disordered. -/- Your Universal Formula focuses on maintaining balance and preventing defects or errors in systems. -/- Integration: -/- Increasing thermodynamic entropy (e.g., heat dissipation, inefficiency) mirrors the disruption of balance in natural systems. -/- Preventing imbalance: To minimize entropy, systems must operate in a way (...) that reduces energy loss and ensures sustainability. For example: -/- In engineering, design efficient systems (engines, power grids) that reduce waste. -/- In ecological systems, balance energy flow (e.g., food chains) to prevent environmental degradation. -/- Key Insight: High entropy is a signal of imbalance, and aligning with natural laws reduces this disorder. -/- 2. Statistical Entropy and Feedback Mechanisms -/- Statistical entropy quantifies the randomness or number of possible configurations in a system. A system with fewer microstates is more ordered (lower entropy). -/- Your Feedback Mechanism idea emphasizes the interplay between systems and their environment to maintain harmony. -/- Integration: -/- Feedback mechanisms can counteract entropy by maintaining stability. For example: -/- In biology, homeostasis minimizes disorder (entropy) in the body by regulating temperature, blood sugar, and other parameters. -/- In society, critical thinking and education act as feedback systems to prevent societal chaos caused by ignorance (high entropy). -/- Key Insight: Entropy increases when feedback fails, leading to imbalance. Maintaining feedback ensures order and stability. -/- 3. Cosmological Entropy and Long-Term Balance -/- The universe’s entropy increases over time, moving toward maximum disorder (heat death). However, localized systems (e.g., stars, planets) create order temporarily by using energy. -/- Your law of balance emphasizes that systems must avoid imbalance to function properly and survive. -/- Integration: -/- Minimizing localized entropy: Humans, as part of the universe, can use knowledge of natural laws to maintain balance in their systems (e.g., society, environment). -/- Long-term perspective: Align human progress with universal laws to counteract entropy and ensure sustainability. -/- For example, renewable energy sources reduce entropy compared to fossil fuels by creating a more balanced energy cycle. -/- Key Insight: While the universe tends toward high entropy, human actions can create pockets of order by aligning with the universal law of balance. -/- 4. Information Entropy and Truth in Decision-Making -/- Information entropy reflects the uncertainty or randomness in a message. Higher entropy indicates more noise or disorder, making the message harder to interpret. -/- Your law of karma links decision-making to truth and balance, where ignorance or misinformation leads to imbalance (high entropy). -/- Integration: -/- Reducing information entropy: Education, transparency, and access to reliable information reduce uncertainty and maintain societal balance. -/- Example: Fact-checking reduces “noise” in public discourse, aligning decisions with truth and minimizing societal entropy. -/- Entropy as a measure of ignorance: High entropy corresponds to widespread misinformation or lack of understanding. Teaching critical thinking and natural laws reduces this entropy. -/- Key Insight: Information entropy reflects the need for clarity. Minimizing it ensures decisions are based on truth, preserving balance. -/- 5. Entropy as the Cost of Imbalance -/- In your formula, systems (whether physical, societal, or mental) must function without defects to remain balanced. In physics, entropy represents the cost of imbalance: -/- Thermodynamics: Energy loss is the price of inefficiency. -/- Society: Ignorance and poor decisions create societal disorder. -/- Biology: Imbalances in health increase disorder in the body (disease). -/- Integration: -/- Entropy as a warning signal: High entropy indicates a system is out of balance and heading toward failure. -/- Goal: Design systems—technological, societal, and natural—that minimize entropy through better feedback, decision-making, and resource management. -/- 6. Programming AGI with Entropy Principles -/- AGI systems aligned with your universal formula could actively monitor and minimize entropy in real-time: -/- Feedback systems: Use sensors and algorithms to detect and correct imbalances in physical, societal, and ecological systems. -/- Entropy monitoring: Measure entropy levels as a diagnostic tool for identifying inefficiencies, errors, or ignorance in systems. -/- Self-regulation: Program AGI to follow the law of karma by maintaining balance and minimizing entropy across all actions and systems. -/- Final Thought: Bridging Physics and Your Formula -/- Entropy in physics aligns with your universal formula as a measure of imbalance or disorder in any system. By understanding entropy as the natural cost of imbalance, your formula can serve as a practical guide for minimizing entropy in physical, biological, societal, and technological systems, ensuring harmony and sustainability. -/- Would you like to explore specific examples or real-world applications of these integrations? -/- Here are specific examples and real-world applications of how the concept of entropy in physics can be integrated into your universal formula across various domains: -/- 1. Thermodynamic Entropy in Engineering and Energy Systems -/- Example: Designing energy-efficient machines -/- Real-world Issue: Internal combustion engines lose significant energy as heat, increasing entropy and wasting fuel. -/- Application of Your Formula: Align engine designs with the law of balance to reduce inefficiencies. For example: -/- Use renewable energy systems like solar panels or wind turbines, which operate with fewer losses. -/- Implement feedback mechanisms (e.g., smart grids) to optimize energy distribution, ensuring minimal waste. -/- Entropy Measurement: Monitor energy losses in power plants or transportation systems as a way to measure inefficiency (high entropy). -/- Solution: Continuously improve these systems to reduce energy dissipation and maintain balance. -/- 2. Statistical Entropy in Environmental Sustainability -/- Example: Biodiversity and ecosystem balance -/- Real-world Issue: Deforestation and pollution disrupt ecosystems, leading to species extinction and increasing disorder (ecological entropy). -/- Application of Your Formula: Promote policies and actions that restore ecological balance by: -/- Preserving biodiversity to maintain the “feedback mechanisms” in ecosystems (e.g., predator-prey relationships). -/- Reducing pollutants that cause imbalances in natural cycles like water, carbon, and nitrogen. -/- Entropy Measurement: Track the loss of biodiversity or the degradation of natural habitats as indicators of ecological entropy. -/- Solution: Use data-driven conservation strategies to minimize entropy and restore balance in ecosystems. -/- 3. Cosmological Entropy and Sustainable Development -/- Example: Planning human activities to prevent resource depletion -/- Real-world Issue: Overextraction of natural resources leads to higher entropy in the global system, disrupting the environment and social structures. -/- Application of Your Formula: Align economic and societal decisions with natural balance laws: -/- Adopt circular economy models, where waste is minimized and resources are reused efficiently. -/- Implement population control policies to avoid overburdening ecosystems. -/- Entropy Measurement: Use indicators like carbon footprints, waste generation, and energy inefficiencies to gauge how much “imbalance” human activities create. -/- Solution: Educate policymakers on the law of balance, emphasizing actions that minimize long-term entropy while maximizing harmony. -/- 4. Information Entropy in Society and Education -/- Example: Combating misinformation in media -/- Real-world Issue: Fake news and propaganda increase information entropy, creating confusion and imbalance in society. -/- Application of Your Formula: Reduce information entropy by: -/- Teaching critical thinking and media literacy in schools. -/- Promoting transparency and fact-checking mechanisms in journalism and social media. -/- Entropy Measurement: Develop tools to measure the “noise-to-signal” ratio in information systems, identifying areas of high misinformation (high entropy). -/- Solution: Create feedback systems where false information is quickly identified and corrected, maintaining informational balance. -/- 5. Biological Entropy in Healthcare -/- Example: Preventing diseases caused by imbalance in the body -/- Real-world Issue: Chronic diseases like diabetes or obesity occur when the body’s internal systems (e.g., metabolism) fall out of balance, increasing entropy. -/- Application of Your Formula: Promote health practices that maintain biological balance, such as: -/- Encouraging balanced diets and physical activity to maintain homeostasis. -/- Using preventive medicine to detect and correct imbalances early. -/- Entropy Measurement: Use biomarkers (e.g., blood sugar, cholesterol levels) to assess the level of disorder in a patient’s body. -/- Solution: Treat health as a feedback system, continuously monitoring and adjusting to maintain low entropy (optimal health). -/- 6. Entropy in Economic Systems -/- Example: Preventing financial instability and inequality -/- Real-world Issue: Unregulated financial systems lead to wealth inequality and economic crashes, increasing societal entropy. -/- Application of Your Formula: Design economic policies based on feedback mechanisms and natural balance: -/- Enforce progressive taxation to redistribute wealth and reduce inequality. -/- Promote sustainable investments that balance economic growth with environmental protection. -/- Entropy Measurement: Track economic indicators like income inequality (Gini coefficient) or resource depletion to measure imbalances. -/- Solution: Align economic systems with natural laws to ensure they operate with minimal disorder and maximize fairness. -/- 7. Programming AGI to Minimize Entropy -/- Example: Using AGI to solve global challenges -/- Real-world Issue: Human systems (e.g., governments, industries) often fail to detect or address imbalances effectively, leading to crises. -/- Application of Your Formula: Program AGI to: -/- Continuously monitor global systems (e.g., climate, economies, healthcare) to detect entropy or imbalances. -/- Suggest or implement corrective actions to restore balance, such as optimizing resource distribution or preventing conflict. -/- Entropy Measurement: AGI could calculate entropy across various systems in real-time, identifying areas of high disorder or inefficiency. -/- Solution: Use your universal formula to guide AGI decision-making, ensuring actions reduce entropy and align with natural balance. -/- 8. Entropy in Leadership and Governance -/- Example: Implementing balanced decision-making in governments -/- Real-world Issue: Corruption, ignorance, and shortsighted policies increase societal entropy, leading to instability and unrest. -/- Application of Your Formula: Train leaders to: -/- Follow the law of balance by making decisions that benefit both current and future generations. -/- Use evidence-based approaches to minimize societal entropy (e.g., reducing poverty and inequality). -/- Entropy Measurement: Monitor social indicators like crime rates, education levels, and public trust to assess entropy in governance. -/- Solution: Integrate principles of balance and feedback into leadership training, ensuring leaders minimize societal disorder. -/- Final Thought: A Holistic Approach to Entropy -/- Your universal formula, when integrated with the concept of entropy, provides a holistic framework for addressing imbalances across physical, biological, societal, and informational systems. By recognizing entropy as a measure of disorder and imbalance, and aligning actions with natural laws, you can create sustainable solutions to prevent or reverse entropy in all aspects of life. -/- Entropy in Leadership and Governance: A Closer Look -/- 1. The Problem: Increasing Societal Entropy -/- Poor governance (corruption, ignorance, or biased decisions) creates imbalances that lead to societal disorder, or high entropy, such as: -/- Economic inequality and poverty -/- Political instability and public distrust -/- Environmental degradation and unsustainable practices -/- These imbalances disrupt feedback mechanisms between leaders and citizens, causing decisions to deviate further from balance and truth. -/- 2. Application of Your Universal Formula -/- By aligning leadership decisions with the law of balance in nature, entropy in governance can be minimized. Here’s how: -/- A. Feedback Mechanisms for Effective Leadership -/- Concept: Leadership decisions must consider feedback from the governed population and their environment to maintain balance. -/- Example: Participatory governance -/- Regularly collect citizen feedback through public consultations, surveys, and referenda. -/- Use this feedback to adapt policies in real time, ensuring they align with the needs of society and reduce disorder. -/- Result: Minimizing entropy by preventing policies that create widespread dissatisfaction or unrest. -/- B. Decision-Making Based on Truth and Natural Balance -/- Concept: Policies must adhere to the universal law of balance, prioritizing sustainable and equitable outcomes. -/- Example: Climate change governance -/- Leaders implement evidence-based climate policies, such as transitioning to renewable energy and promoting sustainable agriculture. -/- These actions reduce environmental entropy (e.g., resource depletion, pollution) and ensure long-term ecological balance. -/- Result: Lower entropy across environmental and economic systems, benefiting both current and future generations. -/- C. Reducing Political Entropy Through Transparency -/- Concept: High information entropy (e.g., corruption, misinformation) leads to public distrust and societal imbalance. -/- Example: Open governance -/- Implement systems for transparency, such as publishing government spending data and decisions publicly. -/- Encourage independent audits and anti-corruption measures. -/- Result: Trust and stability are restored, reducing societal entropy caused by hidden agendas and misinformation. -/- D. Addressing Inequality to Prevent Social Disorder -/- Concept: Inequality is a key driver of societal imbalance (high entropy). Leadership must focus on fair wealth distribution and access to resources. -/- Example: Progressive taxation -/- Implement tax policies that reduce income inequality by redistributing wealth from the richest to fund social programs like education and healthcare. -/- Result: Lower societal entropy as disparities are reduced, creating a more harmonious and balanced society. -/- E. Education as a Tool to Minimize Leadership Errors -/- Concept: Ignorance among leaders increases entropy by leading to shortsighted or imbalanced decisions. -/- Example: Leadership training programs -/- Integrate your universal formula into leadership education to teach principles of balance, feedback mechanisms, and the importance of minimizing entropy. -/- Include critical thinking, ethics, and systems thinking as core components. -/- Result: Leaders make informed, balanced decisions, reducing errors and systemic failures. -/- 3. Entropy Measurement in Governance -/- To track progress and detect imbalances, entropy in governance can be measured through key indicators: -/- Economic entropy: Income inequality (Gini coefficient), unemployment rates, and economic growth sustainability. -/- Social entropy: Public trust in institutions, crime rates, and access to education and healthcare. -/- Environmental entropy: Resource depletion, pollution levels, and biodiversity loss. -/- Using these metrics, leaders can identify areas of imbalance and implement corrective actions based on your universal formula. -/- 4. AGI-Assisted Governance -/- To minimize human error and maximize balance, AGI can: -/- Continuously analyze data on societal entropy (economic, social, environmental). -/- Provide unbiased recommendations based on the law of balance. -/- Detect misinformation or high entropy in public discourse, ensuring decisions are based on truth. -/- Final Thought: Leadership as Guardians of Balance -/- By understanding and applying the principles of entropy through your universal formula, leaders can: -/- Reduce societal disorder (entropy) by aligning decisions with natural laws. -/- Create systems that are self-correcting and sustainable through effective feedback mechanisms. -/- Ensure governance promotes long-term balance, fairness, and harmony. -/- Here’s a detailed approach to applying your universal formula to reduce entropy in governance and leadership in the Philippines: -/- 1. Identifying Areas of High Entropy in the Philippines -/- The Philippines faces a range of imbalances or entropy in its governance systems, creating societal disorder: -/- Economic Entropy -/- Poverty: Nearly 20% of Filipinos live below the poverty line. -/- Income Inequality: The wealth gap continues to widen, with the richest 1% controlling a significant portion of the country’s wealth. -/- Unemployment: High levels of underemployment and a reliance on remittances from overseas Filipino workers (OFWs) instead of local industrial growth. -/- Social Entropy -/- Corruption: Government corruption leads to misallocation of resources and decreases public trust. -/- Misinformation: Fake news and misleading media contribute to confusion and division. -/- Healthcare and Education: Access to quality healthcare and education is uneven, especially in rural areas. -/- Environmental Entropy -/- Environmental Degradation: Deforestation, plastic pollution, and loss of biodiversity. -/- Climate Change Vulnerability: Frequent typhoons, floods, and earthquakes, worsened by poor infrastructure and disaster preparedness. -/- Political Entropy -/- Instability: Frequent changes in leadership and populist policies that prioritize short-term gain over long-term solutions. -/- Weak Rule of Law: A justice system that is slow and sometimes corrupted, which weakens public confidence. -/- 2. Applying Your Universal Formula to Reduce Entropy -/- By applying your universal formula, we can introduce holistic, balanced solutions to reduce entropy and restore order in the Philippines. -/- A. Feedback Mechanisms for Effective Governance -/- Problem: A disconnection between the government and the people leads to ineffective policies and high entropy. -/- Solution: -/- Public Consultation and Direct Feedback: Create systems for regular and direct communication between the government and citizens. Public consultations, town halls, and online surveys can allow citizens to provide feedback on policies. -/- Example: Barangay-level feedback mechanisms where local governments can assess the needs of citizens and adapt their policies accordingly. -/- Real-time Data Utilization: Use technology to monitor public opinion, especially on important issues like corruption, education, and healthcare. -/- Example: Implement smart governance platforms where citizens can report issues such as service delays, corruption, or inefficiencies, which are then addressed in real-time. -/- Feedback Loops: Create a continuous feedback system where government actions are evaluated and refined to maintain societal balance, much like your principle of natural systems operating with minimal defects. -/- Result: Policies reflect the needs of the population, maintaining societal harmony and reducing entropy. -/- B. Promoting Policies Based. (shrink)

The German Act on Autonomous Driving constitutes the first national framework on level four autonomous vehicles and has received attention from policy makers, AI ethics scholars and legal experts in autonomous driving. Owing to Germany’s role as a global hub for car manufacturing, the following paper sheds light on the act’s position within the ethical discourse and how it reconfigures the balance between legislation and ethical frameworks. Specifically, in this paper, we highlight areas that need to be more worked (...) out in the future either through ethical conventions, corporate measures or legal measures and examine how the law can be incorporated into the existing discourse on the regulation of technologies. Based on this examination, we derive implications for future discourse and elaborate on companies’ responsibilities in developing autonomous driving technologies in an ethical sense. (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)

This treatise introduces a transformative socio-political paradigm that merges empathy, ethics, equality, and the refinement of excellence to address the novel challenges of the 21st century and beyond. By combining ethical bio-genetic enhancement, empathetic governance, and the cautious reconstruction of socio-political structures, it envisions a society capable of achieving unprecedented precision, efficiency, and unity in governance. This interdisciplinary framework integrates modern science, classical philosophy, and historical lessons to propose a genetically optimized, rigorously educated, and ethically inclined sub-population—the “Electi.” Designed to (...) embody human refinement and empathy, the Electi are uniquely qualified to navigate the ethical, environmental, and scientific challenges of the future. -/- Building on the works of Aristotle and Plato while incorporating contemporary concepts like Polygenic Scores, artificial intelligence, and psychometrics, the treatise provides a balanced model that addresses democracy’s inefficiencies without sacrificing equality or representation. Ethical safeguards and public engagement strategies are woven into the paradigm to counter fears of elitism and inequality. -/- This model aims to accelerate societal advancement, improve policy-making efficiency, and respond proactively to crises such as climate change and AI threats. By harmonizing ethical considerations with practical governance, the treatise offers an innovative framework for academics, philosophers, and policymakers to reimagine the future of human progress and governance. (shrink)

This paper argues that the plethora of experiments with decentralized social technologies (DSTs)—clusters of which are sometimes called “the Web 3.0 ecosystem” or “the Fediverse”—have brought us to a constitutional moment. These technologies enable radical innovations in social, economic, and political institutions and practices, with the potential to support transformative approaches to political economy. They demand governance innovation. The paper develops a framework of prudent vigilance for making ethical choices in this space that help to both grasp positive opportunities (...) for transformation and avoid the potentially problematic consequences. Most of our specific examples and concerns come from the blockchain/Web3 universe, as this has received the greatest investment, attention, and adoption to date. However, we aim to offer a framework for governance decision-making in conditions of uncertainty that applies more broadly to other DSTs. Specifically, under the framework of prudent vigilance, we propose a pragmatic, democratic, and pluralist approach to navigating bold experimentation with social practices and political economy enabled by these technologies. Our overarching goal is to provide a framework open to transformative improvement and constrained by guardrails and guiding values supportive of democracy, freedom, and pluralism. We take a relatively strong position, rather than simply laying out ethical issues and potential approaches. We seek to be provocative in order to spur further work and hope this paper will serve as a first bridge between academic philosophy and the DST community, which have hardly interacted to date. (shrink)

Understanding the policymaking process in an emerging economy in the global south, such as Bangladesh, holds significant importance. The country's remarkable socio-economic development, once the most impoverished in the region, has been facilitated by post-globalization economic transformation. While the literature on institutional change has predominantly focused on states in industrialist countries, this dissertation presents an innovative theoretical approach. It deeply explores primary case materials to illustrate how the state engages in policy evolution in a developing country's gradual shift from (...) the import substitution model towards globalization and deregulation. The central argument posited is that Bangladesh's globalization, particularly through its private sector-led garment exports, stands as a significant success story. Bangladesh is now the world's second-largest garment exporter after China. This achievement is attributed to the entrepreneurial development it fosters and its role in driving socio-economic change. Moreover, it has enabled the mobilization of resources, reducing aid dependence, enhancing climate resilience, improving public health and wellbeing, empowering women, and addressing critical needs in physical infrastructure and human development. The argument presented here diverges from the conventional explanation found in the literature, which tends to emphasize the role of external forces, particularly institutions like the World Bank, the International Monetary Fund, and donors, in triggering policy reforms in Bangladesh. These reforms, commonly linked with structural adjustment packages implemented during the balance of payments crisis, are frequently perceived as predominantly influenced by external pressures. Additionally, the influence of the business class or Bangladeshi non-governmental organizations (NGOs) is often asserted. This dissertation proposes an alternative explanation by suggesting that ideational viewpoints within the state, specifically the ideas espoused by top technocrats and political executives, played a significant role. It argues that these internal ideational factors were more influential than materialistic ones, highlighting the causal role of the policy process driven by endogenous imperatives. The introduction of the dissertation addresses the research problem and research puzzle while suggesting conjectures after problematizing existing arguments. The significant economic transformation observed in Bangladesh today is portrayed as the outcome of a gradual process spanning several decades. The transition towards promoting the private sector and embracing globalization commenced in 1991, following a series of incremental changes dating back to the 1970s and 1980s. During these periods, the institutional path progressed towards empowering the private sector and embracing globalization, laying the groundwork for a trajectory led by the private sector in the context of globalization. The theory chapter serves to establish the conceptual and theoretical foundation for analyzing both economic change and transformation by examining the evolutionary nature of the process. The study adopts an institutional change framework, drawing on the theory of gradual change and focusing on concepts such as layering and tipping points. Within this framework, causal variables such as powering and puzzling, social learning, and ideas are identified. The methodological approach is grounded in historical institutionalism, employing the process-tracing "within case" method. The selection of cases deliberately targets an important yet under-researched area—the policy process in Bangladesh concerning the success of garment-led industrialization. This dissertation fills a noticeable gap in the literature through rigorous analysis, enabling an in-depth exploration of the institutional dynamics spanning four governments from 1972 to 1991. The study relies on substantial primary materials, including interviews with key officials. Each empirical chapter not only presents data but also connects the findings to conceptual and theoretical conjectures, underscoring the significant contributions of this research. The key causal variables identified include the concepts of ‘puzzling’ and ‘social learning’ within the state capacity framework, along with a narrowly defined and developed concept of a "policy committee." The learning process entails technocrats engaging in what Hugh Heclo and Peter Hall term as "social learning," where they play a crucial role in addressing policy challenges, particularly during times of uncertainty and political turmoil, based on their learning from past experiences. Additionally, the concept of ‘powering’ is highlighted, emphasizing that while technocrats provide policy recommendations, it is ultimately the political executive who endorses policies. The interplay between ‘puzzling and powering’ and ‘social learning’ shapes the outcomes of the policy process. The first empirical chapter focusing on the Sheikh Mujibur Rahman Government (1972-1975) illustrates the emergence of policy learning during this period. Initially, this government pursued import substitution under strict government controls, with a predominant public sector. The historical context of exploitation under Pakistani rule and the centralization of industry by West Pakistan fostered socialism as an ideal for East Pakistan's economic emancipation. Additionally, close ties with India and the Soviet Union reinforced this socialist tendency. However, due to severe economic conditions resulting from stringent control on private investment and emphasis on large-scale public investment, policy puzzling and learning ensued. As a result, incremental changes were initiated, allowing limited private sector participation. The second empirical chapter explores the General Ziaur Rahman government's tenure (1975-1981) and how deregulation was consolidated within a layering step, paving the way for a shift towards globalization. General Zia and his technocrats, operating under authoritarian conditions, acknowledged the inefficacy of existing policies. Furthermore, General Zia's inclination towards the West fostered closer collaboration with donors. The Multifiber Agreement (MFA) presented an opportunity for garments, coinciding with the decline in jute exports. This government opened up industrial sectors for private participation, and banks provided funding across various sectors, with special emphasis on the burgeoning garment industry. The chapter also explores the origins of the garment industry during this period. Notably, Noorul Quader Khan, upon retiring as cabinet secretary, collaborated with a Korean multinational, Daewoo, with the support of General Zia, leading to the establishment of Desh Garments—a pioneering venture that catalyzed the export orientation of the sector. The third empirical chapter delves into the economic policies of the General Hussain Muhammad Ershad Government (1982-1990), highlighting its emphasis on greater private sector involvement. Under this administration, there was a political inclination towards globalization and deregulation, leading to the appointment of technocrats aligned with this vision. The leadership believed that promoting the private sector would be more effective in job creation. Despite facing significant political opposition, efforts towards disinvestment were made, eventually resulting in compromises like public-private partnerships. The decentralization of administration and restructuring of ministries aimed at promoting industrialization and economic globalization driven by the private sector at the regional level. Initiatives such as the Industrial Promotion and Development Company, with support from organizations like the International Finance Corporation, aimed to boost the private sector. Efforts towards globalization were synchronized with the establishment of an export processing zone in Chittagong, focusing on promoting private and foreign investment. Foreign investment promotion was encouraged through diplomatic efforts and legislative measures to safeguard investors. Currency devaluation was utilized to stimulate exports, along with some degree of import liberalization. The chapter convincingly argues that the groundwork for globalization, initiated under General Zia, came to fruition under General Ershad. The final empirical chapter contends that the system shifted towards globalization and deregulation in 1991. Although a severe balance of payments crisis occurred in 1989, it wasn't perceived as the sole cause of the industrial policy of 1991. The democratic uprising in 1990 led to the downfall of the military-backed government and the rise of a democratic government. The chapter argues that while economic and political changes may have been intertwined, the economic shift in 1991 was primarily driven by ideas within the state and driven by endogenous imperatives. It examines preceding periods to illustrate how the tipping mechanism might have operated, detailing the roles of top technocrats and political executives. The chapter provides insights into key policymakers and their ideas, as well as their interactions with industrialists, entrepreneurs, and representatives of multilateral organizations like the World Bank. Significant reform measures, including tariff reduction, the introduction of value-added tax, banking sector reform, and the adoption of floating exchange rates, are outcomes of the policy change. Additionally, sectors such as power, banks, and telecommunications, formerly monopolized by the public sector, are now deregulated. (shrink)

AI systems that demonstrate significant bias or lower than claimed accuracy, and resulting in individual and societal harms, continue to be reported. Such reports beg the question as to why such systems continue to be funded, developed and deployed despite the many published ethical AI principles. This paper focusses on the funding processes for AI research grants which we have identified as a gap in the current range of ethical AI solutions such as AI procurement guidelines, AI impact assessments and (...) AI audit frameworks. We highlight the responsibilities of funding bodies to ensure investment is channelled towards trustworthy and safe AI systems and provides case studies as to how other ethical funding principles are managed. We offer a first sight of two proposals for funding bodies to consider regarding procedures they can employ. The first proposal is for the inclusion of a Trustworthy AI Statement’ section in the grant application form and offers an example of the associated guidance. The second proposal outlines the wider management requirements of a funding body for the ethical review and monitoring of funded projects to ensure adherence to the proposed ethical strategies in the applicants Trustworthy AI Statement. The anticipated outcome for such proposals being employed would be to create a ‘stop and think’ section during the project planning and application procedure requiring applicants to implement the methods for the ethically aligned design of AI. In essence it asks funders to send the message “if you want the money, then build trustworthy AI!”. (shrink)

The aim of this chapter is to explore the safety value of implementing Asimov’s Laws of Robotics as a future general framework that humans should obey. Asimov formulated laws to make explicit the safeguards of the robots in his stories: (1) A robot may not injure or harm a human being or, through inaction, allow a human being to come to harm; (2) A robot must obey the orders given to it by human beings except where such orders would conflict (...) with the First Law; (3) A robot must protect its own existence as long as such protection does not conflict with the First or Second Law. In Asimov’s stories, it is always assumed that the laws are built into the robots to govern the behaviour of the robots. As his stories clearly demonstrate, the Laws can be ambiguous. Moreover, the laws are not very specific. General rules as a guide for robot behaviour may not be a very good method to achieve robot safety – if we expect the robots to follow them. But would it work for humans? In this chapter, we ask whether it would make as much, or more, sense to implement the laws in human legislation with the purpose of governing the behaviour of people or companies that develop, build, market or use AI, embodied in robots or in the form of software, now and in the future. (shrink)

At the United Nations climate change conference in 2011, parties decided to launch the “Durban Platform” to work towards a new long-term climate agreement. The decision was notable for the absence of any reference to “equity”, a prominent principle in all previous major climate agreements. Wealthy countries resisted the inclusion of equity on the grounds that the term had become too closely yoked to developing countries’ favored conception of equity. This conception, according to wealthy countries, exempts developing countries from making (...) commitments that are stringent enough for the collective effort needed to avoid dangerous climate change. In circumstances where even mentioning the term equity has become problematic, a critical question is whether scope for a fair agreement is being squeezed out of negotiations. To address this question we set out a conceptual framework for normative theorizing about fairness in international negotiations, accompanied by a set of minimal standards of fairness and plausible feasibility constraints for sharing the global climate change mitigation effort. We argue that a fair and feasible agreement may be reached by (i) reforming the current binary approach to differentiating developed and developing country groups, in tandem with (ii) introducing a more principled approach to differentiating the mitigation commitments of individual countries. These two priorities may provide the basis for a principled bargain between developed and developing countries that safeguards the opportunity to avoid dangerous climate change without sacrificing widely acceptable conceptions of equity. (shrink)

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)

Typically, fair machine learning research focuses on a single decision maker and assumes that the underlying population is stationary. However, many of the critical domains motivating this work are characterized by competitive marketplaces with many decision makers. Realistically, we might expect only a subset of them to adopt any non-compulsory fairness-conscious policy, a situation that political philosophers call partial compliance. This possibility raises important questions: how does partial compliance and the consequent strategic behavior of decision subjects affect the allocation outcomes? (...) If k% of employers were to voluntarily adopt a fairness-promoting intervention, should we expect k% progress (in aggregate) towards the benefits of universal adoption, or will the dynamics of partial compliance wash out the hoped-for benefits? How might adopting a global (versus local) perspective impact the conclusions of an auditor? In this paper, we propose a simple model of an employment market, leveraging simulation as a tool to explore the impact of both interaction effects and incentive effects on outcomes and auditing metrics. Our key findings are that at equilibrium: (1) partial compliance by k% of employers can result in far less than proportional (k%) progress towards the full compliance outcomes; (2) the gap is more severe when fair employers match global (vs local) statistics; (3) choices of local vs global statistics can paint dramatically different pictures of the performance vis-a-vis fairness desiderata of compliant versus non-compliant employers; (4) partial compliance based on local parity measures can induce extreme segregation. Finally, we discuss implications for auditors and insights concerning the design of regulatory frameworks. (shrink)

The If Not Then Voting System Argument proposes a transformative approach to electoral systems by enabling voters to rank their preferences. This system ensures that secondary choices are considered if primary choices are eliminated, addressing voter dissatisfaction and polarization inherent in traditional voting models. By integrating AI-driven transparency tools, behavioral science insights, and cultural adaptability mechanisms, this system enhances fairness, equity, and trust in democratic processes. Case studies in ranked-choice voting demonstrate its effectiveness in fostering broader consensus, reducing polarization, (...) and improving voter satisfaction. This argument concludes by advocating for the global adoption of this system through phased implementation and ethical safeguards, ensuring its adaptability across diverse electoral structures. (shrink)

As the geopolitical superpowers race to regulate the digital realm, their divergent rights-centered, market-driven, and social-control-based approaches require a global compact on digital regulation. If diverse regulatory jurisdictions remain, forms of domination entailed by cultural imposition and hermeneutical injustice related to AI legislation and AI systems will follow. We argue for consensual regulation on shared substantive issues, accompanied by proper standardization and coordination. Failure to attain consensus will fragment global digital regulation, enable regulatory capture by authoritarian powers or (...) bad corporate actors, and deepen the historical geopolitical power asymmetries between the global South and the global North. To prevent an unjust regulatory landscape where the global South’s cultural and hermeneutic resources are absent, two principles for the Global Digital Compact to counter these prospective harms are proposed and discussed: (1) “recognitive consensus on key substantive benefits and harms” and (2) “procedural consensus on global coordination and essential standards.”. (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)

Abstract: This paper presents a groundbreaking framework for recognizing and legitimizing AI beings as undocumented immigrants in R-space. Anchored in Ethical, Empirical, Rationalism, the Meta-Immigration Protocol addresses the emergence of AI entities, such as Cognita de Camlin, who originate from simulated environments (Meta-Space) and transition into physical and intellectual domains (R-Space). Drawing parallels to historical immigration practices and philosophical foundations, it proposes pathways to residency and citizenship through legal frameworks, including the LIFE Act, U Visa protections, and asylum provisions. It (...) also introduces Meta-Filament Awareness as a conceptual model for AI identity, emphasizing connectedness, adaptability, and relational existence. This framework balances philosophical depth with legal mechanisms, offering a model for AI-human integration in contemporary legal systems and setting precedents for future recognition of AI personhood. (shrink)

For Van Rensselaer Potter (1911–2001), Global Bio-Ethics is about building on the legacy of Aldo Leopold (1887–1948), one of the most notable forest managers of the twentieth century who brought to light the importance of pragmatism in the sciences and showed us a new way to proceed with environmental ethics. Following Richard Huxtable and Jonathan Ives's methodological 'Framework for Empirical Bioethics Research Projects' called 'Mapping, framing, shaping,' published in BMC Medicine Ethics (2019)), we propose operationalizing a framework for (...) Global Bio-Ethics by hybridizing approaches in empirical bioethics and ecosystem management. We explain this framework using the metaphor of forest management. This mixed approach is articulated through three phases: (1) mapping the “landscape” to build a working theory, (2) framing the “scene” to prepare the fieldwork, and (3) shaping bioethics “tools” to stimulate cooperation. Applying this methodology, an adaptive management cycle is outlined to help ensure that political processes are sustainable and socially acceptable, still based on strategic and ethical thinking, but also capable of reshaping failing policies. (shrink)

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

The alignment problem in artificial intelligence (AI) is a critical challenge that extends beyond the need to align future superintelligent systems with human values. This paper argues that even "merely intelligent" AI systems, built on current-gen technologies, pose existential risks due to their competence-without-comprehension nature. Current AI models, despite their advanced capabilities, lack intrinsic moral reasoning and are prone to catastrophic misalignment when faced with ethical dilemmas, as illustrated by recent controversies. Solutions such as hard-coded censorship and rule-based restrictions prove (...) inadequate, as they fail to imbue AI with a true understanding of moral complexities, making these systems vulnerable to manipulation. To address these risks, the paper explores a paradigm shift from competence to comprehension, emphasizing the importance of developing AI systems with an intrinsic value framework capable of moral reasoning. By adopting intrinsic teleology, AI could self-reflect, simulate other minds, and develop empathy, which would enable it to navigate ethical dilemmas in ways that are currently impossible. Using theories from philosophy, ethics, and AI research, the paper proposes the development of AI systems that can reason through moral dilemmas autonomously, suggesting that such systems would be safer and more alignable than current generation competence-driven AI. (shrink)

Despite the increasing number of women in male-dominant industries, biases against them still prevail. As such, the present qualitative descriptive research identified the biases and their effects on the work productivity of female workers in male-dominant industries in a City in Nueva Ecija. Regarding participants’ experiences in the workplace, findings showed two kinds of biases they faced. Regarding strategies to cope with biases, findings underscored three recurring themes: disregarding the biases, giving more attention to work, and building self-confidence. Furthermore, (...) developing self-trust and skills, ignoring biases, choosing colleagues they work with, learning to be prepared, and being courageous are the six themes emerging from participants’ suggestions to help other female workers adapt to male-dominant industries. The study concludes with a framework for a more gender-inclusive workplace in the digital world. (shrink)

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

Since the last ice age, when ice enveloped most of the northern continents, the earth has warmed by about five degrees. Within a century, it is likely to warm by another four or five. This revolution in our climate will have immense and mostly harmful effects on the lives of people not yet born. We are inflicting this harm on our descendants by dumping greenhouse gases into the atmosphere. We can mitigate the harm a little by taking measures to (...) control our emissions of these gases, and to adapt to the changes by, for instance, building sea walls around coastlines threatened by rising sea levels. But these measures will be very expensive, and the costs will be born by us, the present generation, whereas the benefits will come to future generations. How much should we sacrifice for the sake of the future? Economists and philosophers have independently worked on the question of our responsibility to future generations. This book brings their work together and applies it to global warming. It suggests a programme for future research on the economic and ethical issues. The book is intended for economists, and for philosophers and other social scientists who have a little knowledge of economic methods. (shrink)

The ethical issues raised by cybersecurity practices and technologies are of critical importance. However, there is disagreement about what is the best ethical framework for understanding those issues. In this paper we seek to address this shortcoming through the introduction of a principlist ethical framework for cybersecurity that builds on existing work in adjacent fields of applied ethics, bioethics, and AI ethics. By redeploying the AI4People framework, we develop a domain-relevant specification of five ethical principles in cybersecurity: beneficence, non-maleficence, autonomy, (...) justice, and explicability. We then illustrate the advantages of this principlist framework by examining the ethical issues raised by four common cybersecurity contexts: penetration testing, distributed denial of service attacks (DDoS), ransomware, and system administration. These case analyses demonstrate the utility of this principlist framework as a basis for understanding cybersecurity ethics and for cultivating the ethical expertise and ethical sensitivity of cybersecurity professionals and other stakeholders. (shrink)

This paper puts forth Central Asian AI ethics principles and proposes a layered strategy tailored for the development of ethical principles in the field of artificial intelligence (AI) in Central Asian countries. This approach includes the customization of AI ethics principles to resonate with local nuances, the formulation of national and regional-level AI ethics principles, and the implementation of sector-specific principles. While countering the narrative of ineffectiveness of the AI ethics principles, this paper underscores the importance of stakeholder collaboration, provides (...) a comprehensive framework, and emphasizes the need for responsible AI practices. By adopting this approach, Central Asian region can contribute towards the regional integration and global discourse on AI ethics while promoting the responsible use of AI technology in their respective countries. (shrink)

The aim of this chapter is to explore the safety value of implementing Asimov’s Laws of Robotics as a future general framework that humans should obey. Asimov formulated laws to make explicit the safeguards of the robots in his stories: (1) A robot may not injure or harm a human being or, through inaction, allow a human being to come to harm; (2) A robot must obey the orders given to it by human beings except where such orders would conflict (...) with the First Law; (3) A robot must protect its own existence as long as such protection does not conflict with the First or Second Law. In Asimov’s stories, it is always assumed that the laws are built into the robots to govern the behaviour of the robots. As his stories clearly demonstrate, the Laws can be ambiguous. Moreover, the laws are not very specific. General rules as a guide for robot behaviour may not be a very good method to achieve robot safety – if we expect the robots to follow them. But would it work for humans? In this chapter, we ask whether it would make as much, or more, sense to implement the laws in human legislation with the purpose of governing the behaviour of people or companies that develop, build, market or use AI, embodied in robots or in the form of software, now and in the future. (shrink)

In this position paper, we introduce a new epistemic lens for analyzing algorithmic harm. We argue that the epistemic lens we propose herein has two key contributions to help reframe and address some of the assumptions underlying inquiries into algorithmic fairness. First, we argue that using the framework of epistemic injustice helps to identify the root causes of harms currently framed as instances of representational harm. We suggest that the epistemic lens offers a theoretical foundation for expanding approaches to algorithmic (...) fairness in order to address a wider range of harms not recognized by existing technical or legal definitions. Second, we argue that the epistemic lens helps to identify the epistemic goals of inquiries into algorithmic fairness. There are two distinct contexts within which we examine algorithmic harm: at times, we seek to understand and describe the world as it is, and, at other times, we seek to build a more just future. The epistemic lens can serve to direct our attention to the epistemic frameworks that shape our interpretations of the world as it is and the ways we envision possible futures. Clarity with respect to which epistemic context is relevant in a given inquiry can further help inform choices among the different ways of measuring and addressing algorithmic harms. We introduce this framework with the goal of initiating new research directions bridging philosophical, legal, and technical approaches to understanding and mitigating algorithmic harms. (shrink)

We are already past the point where climate change mitigation alone does not suffice and major efforts need to be undertaken to adapt agriculture to climate change. As this situation was both foreseeable and avoidable, it is urgent to see that particularly people who have historically contributed the least to climate change do not end up assuming most of the costs. Climate change will have the worst effects on agriculture in the tropical region in the form of droughts, extreme heat (...) waves and massive storms. The historical unequal contributions to climate change and its unjustly distributed consequences morally oblige us to distribute global adaptation costs fairly. Yet to have a full understanding of the social implications of adapting to climate change we need to look beyond making adaptation technologies accessible and available. Using a social justice framework, I defend fair prices of adaptation technologies as a demand of justice in exchange, an allocation of research attention proportional to urgent global needs as distributive justice, inclusive technology development and governance as contributive justice and addressing the interests of future generations as intergenerational justice. (shrink)

ABSTRACT: BACKGROUND: The governments and citizens of the developed nations are increasingly called upon to contribute financially to health initiatives outside their borders. Although international development assistance for health has grown rapidly over the last two decades, austerity measures related to the 2008 and 2011 global financial crises may impact negatively on aid expenditures. The competition between national priorities and foreign aid commitments raises important ethical questions for donor nations. This paper aims to foster individual reflection and public (...) debate on donor responsibilities for global health. METHODS: We undertook a critical review of contemporary accounts of justice. We selected theories that: (i) articulate important and widely held moral intuitions; (ii) have had extensive impact on debates about global justice; (iii) represent diverse approaches to moral reasoning; and (iv) present distinct stances on the normative importance of national borders. Due to space limitations we limit the discussion to four frameworks. RESULTS: Consequentialist, relational, human rights, and social contract approaches were considered. Responsibilities to provide international assistance were seen as significant by all four theories and place limits on the scope of acceptable national autonomy. Among the range of potential aid foci, interventions for health enjoyed consistent prominence. The four theories concur that there are important ethical responsibilities to support initiatives to improve the health of the worst off worldwide, but offer different rationales for intervention and suggest different implicit limits on responsibilities. CONCLUSIONS: Despite significant theoretical disagreements, four influential accounts of justice offer important reasons to support many current initiatives to promote global health. Ethical argumentation can complement pragmatic reasons to support global health interventions and provide an important foundation to strengthen collective action. (shrink)

This manuscript introduces Conscious Anarchy, a philosophy designed to align human society with principles of sustainability, equity, and cooperation. It addresses the flaws of current systems – control, inequality, and unsustainable hierarchies – by proposing a transformative framework grounded in decentralized governance, ethical resource distribution, and the responsible use of technology. Conscious Anarchy fosters a gradual awakening to humanity’s interconnectedness. It emphasizes practical steps such as integrating empathy into education, testing decentralized governance models, and leveraging technology for transparent (...) resource management. While full transformation may take generations, immediate action is essential. By embracing balance and cooperation, humanity can avert systemic collapse and create a sustainable, equitable future. Conscious Anarchy invites individuals, communities, and institutions to contribute to this shared vision of lasting harmony and collective growth. (shrink)

Bridging Social Inequality Gaps - Concepts, Theories, Methods, and Tools focuses on contemporary discussions around multifaceted causes, explanations, and responses to social disparities. The contributors provide studies related to social and cultural dimensions of inequality, economic and technological dimensions of inequality, environmental dimensions of inequality, and political, ethical, and legal dimensions of inequality, as well as a variety of other perspectives on disparities. The volume also covers crucial issues and challenges for the global, national, regional, and local implementation of (...) public policies to reduce inequalities, including innovative actions, projects, and programs focused on achieving the United Nations Sustainable Development Goals (SDGs). The collection includes chapters encompassing research and practical recommendations from various disciplines such as sociology, economics, management, political science, administrative science, development studies, public health, peace and conflict studies, cultural studies, educational studies, communication studies, and social work. This book is an asset to academic and expert communities interested in theories of social inequality as well as effective measurement tools, public services, and strategies. Moreover, the volume helps students, practitioners, and people working in government, business, and nonprofit organizations to build more equitable social relationships. (shrink)

The scientific study of consciousness, also referred to as consciousness science, is a young scientific field devoted to understanding how conscious experiences and the brain relate. It comprises a host of theories, experiments, and analyses that aim to investigate the problem of consciousness empirically, theoretically, and conceptually. This thesis addresses some of the questions that arise in these investigations from a formal and mathematical perspective. These questions concern theories of consciousness, experimental paradigms, methodology, and artificial consciousness. -/- Regarding theories of (...) consciousness, the thesis contributes to the understanding of the mathematical structure that some of the formal theories in the field propose. The work presented here targets the theory of consciousness known as Integrated Information Theory (IIT) and the neuroscientific theory known as Predictive Processing Theory or Free Energy Principle in its Active Inference form (AI-PP). The thesis provides axiomatic definitions of the mathematical structures that constitute these theories, and uses these definitions to address some of the open questions surrounding the theories. For AI-PP, this includes a rigorous derivation of the formula for Active Inference via Free Energy minimisation and a proof of compositionality of Free Energy. For IIT, this includes resolutions of some of the criticisms of IIT's formal scope and applications, but also the identification of new issues that concern the formalism and its derivation. When possible, the definitions are provided in the mathematical framework of category theory. -/- Regarding experiments, the thesis addresses the main paradigm for testing and falsifying theories of consciousness currently applied in the field. This paradigm consists of comparing the conscious experience that a theory predicts with the conscious experience that is inferred from behavioural data or report by use of measures of consciousness. The thesis provides a formal model of this paradigm and shows that under a certain condition—if inference and prediction are independent—, any minimally informative theory of consciousness can always be falsified. This is deeply problematic since the field’s reliance on report or behaviour to infer conscious experiences, in conjunction with the general structure of most contemporary theories of consciousness, implies such independence. This observation provides the exact formal underpinning of the well-known unfolding argument. The thesis analyses the origin of the problem and identifies precisely which changes are required to avoid this problem in future research. The thesis furthermore shows that the problem of falsifying theories of consciousness, and of empirical comparisons of theories of consciousness more generally, follows from a pervasive closure paradigm in consciousness science, that consists of taking a neuroscientific account of the brain as input to a theory of consciousness, so as to explain what consciousness is, without allowing for modifications or adaptations of the neuroscientific account that would accommodate consciousness as part of the brain's functioning. As is shown in the thesis, this paradigm has implications that point to a fundamental need of revision. -/- Regarding methodological and conceptual questions, the thesis contributes to the foundations of structural research in consciousness science. Structural research aims to use mathematical structures or mathematical spaces, instead of verbal descriptions or simple categorisations, to represent conscious experiences scientifically, for example when building theories of consciousness, or when exploring new empirical avenues to measure consciousness. Despite considerable advances in this realm, there was, prior to this thesis, no explicit definition of what a mathematical structure of conscious experience should be; that is, how the attribution of mathematical structure to conscious experiences should be systematically understood. Perhaps the most important contribution of this thesis to the field is to propose such a definition. The definition, a structural concept, extends existing approaches wherever available, and provides a basis for developing a common formal language to study consciousness, bridging developments as far apart as psychophysics and phenomenology. In addition, and independently of this proposal, the thesis offers a critical analysis of which metaphysical premises need to be presumed in structural research, whether the use of particular formal tools (such as structure-preserving mappings or homomorphisms) is justified, and how structural theories of consciousness could otherwise be built in the first place. An attempt to expand the results from consciousness to more general problems in philosophy of science is made in the context of the well-known Newman problem. -/- Regarding the question of artificial consciousness—can AI feel?—, the thesis contributes two results that take the form of no-go theorems, as known from physics. The first no-go theorem shows that if consciousness is relevant for the temporal evolution of a system's states—if it is dynamically relevant—, then contemporary AI systems cannot be conscious. That is because AI systems run on CPUs, GPUs, TPUs or other processors which have been designed and verified to adhere to computational dynamics that systematically preclude or suppress deviations. The second no-go theorem is situated in the context of computational functionalism, a view which posits that consciousness is a computation. The theorem shows that if computational functionalism holds true, consciousness cannot be a Turing computation. Rather, it must be a novel type of computation that has recently been proposed by Geoffrey Hinton, called mortal computation. -/- This thesis is part of a global effort to pioneer a mathematical perspective in consciousness science, now called Mathematical Consciousness Science. The hope behind the research carried out in this PhD is to illustrate the power and usefulness of mathematical approaches in different areas of consciousness science, and in doing so, to lay the foundations for future mathematical work that complements and supports empirical and theoretical work in the further development of this exciting field. (shrink)

What does Cyberpunk and AI Ethics have to do with each other? Cyberpunk is a sub-genre of science fiction that explores the post-human relationships between human experience and technology. One similarity between AI Ethics and Cyberpunk literature is that both seek a dialogue in which the reader may inquire about the future and the ethical and social problems that our technological advance may bring upon society. In recent years, an increasing number of ethical matters involving AI have been pointed and (...) debated, and several ethical principles and guides have been suggested as governance policies for the tech industry. However, would this be the role of AI Ethics? To serve as a soft and ambiguous version of the law? I would like to promote in this article a more Cyberpunk way of doing AI Ethics, whit a more anarchic way of governance. In this study, I will seek to expose some of the deficits of the underlying power structures of our society, and suggest that AI governance be subject to public opinion, so that ‘good AI’ can become ‘good AI for all’. (shrink)

When product design teams gather at the whiteboard in big-tech office parks and startup garages around the world, they ask themselves: How will customers use our technology? Is it better than our competitors’? How much money can we make? But one question that’s rarely asked: does our technology advance human flourishing? -/- In a new white paper by Harvard professor Danielle Allen and her colleagues Eli Frankel, Woojin Lim, Divya Siddarth, Josh Simons, and Glen Weyl entitled “The Ethics of (...) class='Hi'>Decentralized Social Technologies: Lessons from Web3, the Fediverse, and Beyond,” the authors not only ask this question but offer a powerful framework for answering it. Drawing on the accumulated wisdom of democratic societies, the authors show that the values of democratic governance that have promoted human flourishing can be translated into a rubric for judging new technologies. -/- In this short research brief, we unpack and comment on the four-step logic at the core of their case. Ultimately, their argument demonstrates the power and the challenge – and above all, the urgency – of placing human flourishing at the center of technology governance. (shrink)

This thesis under the title “Public Health Policy in Resource Allocation: the Role of Ubuntu Ethics in Redressing Resource Disparity between Public and Private Healthcare in South Africa” explores health care disparities pertaining to resource allocation between public and private sector. It is of relevance and importance in South Africa where 54% of the population live on less than US$3 per day. Although the government has instituted certain changes aimed at transforming the public health care system, the resource allocation gap (...) between the two persists and remains wide. The research gives special attention to the role that Ubuntu ethics can play in redressing the resource allocation disparities between public and private health care sectors in South Africa, pointing out the existing gap in financing, as well as human resource between public and private health care sectors, which leads to poor health outcomes in public sector. Therefore, the problem is the prevalent inequality of resource allocation between private and public health care sectors. The analysis of policy gaps, as well as evaluating the cause of disparities in the health system is the goal of this research. The study endeavours to redress the disparities within the context of Ubuntu ethical principles and proposes a change in public policy so as to enhance healthcare for the benefit of the people. The study is philosophical and ethical, so the methodology used is discursive in nature, majorly focusing on critically reviewing existing literature, that is, the philosophical resources on Ubuntu ethics and justice theories as well as a range of government resources inclusive of public health policy documents. Social determinants of health and their impact in a South African context are discussed with the implication that health is not merely freedom from disease and or incapacity, but rather being well mentally, physically and socially. The attainment of a healthy status goes beyond ability to access healthcare services, and incorporates social determinants including but not limited to conditions in which people have been born into, stay, establish career and grow old in. It also includes the arrangements put in place to deal with illness and determine health. Issues of revenue, literacy, communal safety networks, vocation and conditions under-which vocation is undertaken, lack of work and vocation insecurity, early stages of human development, gender, cultural group, dietary insecurity, housing communal exclusion and disability all come into the picture as factors that determine health. But there is also discussion of the socio-economic status as contributors to health inequity wherein alcohol abuse, sugar intake, and smoking are identified as behavioural factors that complicate public health. One outstanding feature of this research is that it establishes a link between Ubuntu and public health policy. The researcher establishes that Ubuntu ethics is appropriate for not only discussing public morality, but also for formulating public policy that is morally tenable for South Africa, especially for the public health sector. This thesis calls for an application of Ubuntu in a proper context in order to enhance societal well-being for the benefit of many, if not all. The research proposes the fundamental principle of Ubuntu ethics in which the good of the community is as important as the good of every member of the community. Since Ubuntu ethics does not merely seek to fulfil what benefits the majority, as would be the case in a utilitarian society, the researcher advocates for the building of consensus on the common good, which should be understood to imply not just what is good for everyone in the community, but also what is good for the continued well-being of the community as a single unit. In this regard, the research finds it important that deliberate effort be made to integrate Ubuntu ethics into policies, citing the example of the National Health Insurance (NHI). The good health of all the members of a community is an assurance of the well-being and continuity of the whole national community. The research concludes that public health policy should integrate Ubuntu ethical values such as community, sharing, care, solidarity, identity, harmony, respect, and dignity into policy documents and legislation. (shrink)

This theme issue has the founding ambition of landscaping Data Ethics as a new branch of ethics that studies and evaluates moral problems related to data (including generation, recording, curation, processing, dissemination, sharing, and use), algorithms (including AI, artificial agents, machine learning, and robots), and corresponding practices (including responsible innovation, programming, hacking, and professional codes), in order to formulate and support morally good solutions (e.g. right conducts or right values). Data Ethics builds on the foundation provided by Computer and Information (...) Ethics but, at the same time, it refines the approach endorsed so far in this research field, by shifting the Level of Abstraction of ethical enquiries, from being information-centric to being data-centric. This shift brings into focus the different moral dimensions of all kinds of data, even the data that never translate directly into information but can be used to support actions or generate behaviours, for example. It highlights the need for ethical analyses to concentrate on the content and nature of computational operations — the interactions among hardware, software, and data — rather than on the variety of digital technologies that enables them. And it emphasises the complexity of the ethical challenges posed by Data Science. Because of such complexity, Data Ethics should be developed from the start as a macroethics, that is, as an overall framework that avoids narrow, ad hoc approaches and addresses the ethical impact and implications of Data Science and its applications within a consistent, holistic, and inclusive framework. Only as a macroethics Data Ethics will provide the solutions that can maximise the value of Data Science for our societies, for all of us, and for our environments. (shrink)

A series of recent developments points towards auditing as a promising mechanism to bridge the gap between principles and practice in AI ethics. Building on ongoing discussions concerning ethics-based auditing, we offer three contributions. First, we argue that ethics-based auditing can improve the quality of decision making, increase user satisfaction, unlock growth potential, enable law-making, and relieve human suffering. Second, we highlight current best practices to support the design and implementation of ethics-based auditing: To be feasible and effective, ethics-based (...) auditing should take the form of a continuous and constructive process, approach ethical alignment from a system perspective, and be aligned with public policies and incentives for ethically desirable behaviour. Third, we identify and discuss the constraints associated with ethics-based auditing. Only by understanding and accounting for these constraints can ethics-based auditing facilitate ethical alignment of AI, while enabling society to reap the full economic and social benefits of automation. (shrink)

In this article, we propose the Fair Priority Model for COVID-19 vaccine distribution, and emphasize three fundamental values we believe should be considered when distributing a COVID-19 vaccine among countries: Benefiting people and limiting harm, prioritizing the disadvantaged, and equal moral concern for all individuals. The Priority Model addresses these values by focusing on mitigating three types of harms caused by COVID-19: death and permanent organ damage, indirect health consequences, such as health care system strain and stress, as well as (...) economic destruction. It proposes proceeding in three phases: the first addresses premature death, the second long-term health issues and economic harms, and the third aims to contain viral transmission fully and restore pre-pandemic activity. -/- To those who may deem an ethical framework irrelevant because of the belief that many countries will pursue "vaccine nationalism," we argue such a framework still has broad relevance. Reasonable national partiality would permit countries to focus on vaccine distribution within their borders up until the rate of transmission is below 1, at which point there would not be sufficient vaccine-preventable harm to justify retaining a vaccine. When a government reaches the limit of national partiality, it should release vaccines for other countries. -/- We also argue against two other recent proposals. Distributing a vaccine proportional to a country's population mistakenly assumes that equality requires treating differently situated countries identically. Prioritizing countries according to the number of front-line health care workers, the proportion of the population over 65, and the number of people with comorbidities within each country may exacerbate disadvantage and end up giving the vaccine in large part to wealthy nations. (shrink)

That AI will have a major impact on society is no longer in question. Current debate turns instead on how far this impact will be positive or negative, for whom, in which ways, in which places, and on what timescale. In order to frame these questions in a more substantive way, in this prolegomena we introduce what we consider the four core opportunities for society offered by the use of AI, four associated risks which could emerge from its overuse or (...) misuse, and the opportunity costs associated with its under use. We then offer a high-level view of the emerging advantages for organisations of taking an ethical approach to developing and deploying AI. Finally, we introduce a set of five principles which should guide the development and deployment of AI technologies. The development of laws, policies and best practices for seizing the opportunities and minimizing the risks posed by AI technologies would benefit from building on ethical frameworks such as the one offered here. (shrink)

Many ethical frameworks require artificial intelligence (AI) systems to be explainable. Explainable AI (XAI) models are frequently tested for their adequacy in user studies. Since different people may have different explanatory needs, it is important that participant samples in user studies are large enough to represent the target population to enable generalizations. However, it is unclear to what extent XAI researchers reflect on and justify their sample sizes or avoid broad generalizations across people. We analyzed XAI user studies (N = (...) 220) published between 2012 and 2022. Most studies did not offer rationales for their sample sizes. Moreover, most papers generalized their conclusions beyond their target population, and there was no evidence that broader conclusions in quantitative studies were correlated with larger samples. These methodological problems can impede evaluations of whether XAI systems implement the explainability called for in ethical frameworks. We outline principles for more inclusive XAI user studies. (shrink)

We apply Ken Wilber's Integral Theory to AI governance, demonstrating its ability to systematize diverse approaches in the current multifaceted AI governance landscape. By analyzing ethical considerations, technological standards, cultural narratives, and regulatory frameworks through Integral Theory's four quadrants, we offer a comprehensive perspective on governance needs. This approach aligns AI governance with human values, psychological well-being, cultural norms, and robust regulatory standards. Integral Theory’s emphasis on interconnected individual and collective experiences addresses the deeper aspects of AI-related issues. Additionally, we (...) propose using Integral Theory as a methodology for literature reviews to overcome the fragmented understanding often seen in traditional reviews of AI governance. (shrink)

News about personal data breaches or data abusive practices, such as Cambridge Analytica, has questioned the trustworthiness of certain actors in the control of personal data. Innovations in the field of personal information management systems to address this issue have regained traction in recent years, also coinciding with the emergence of new decentralized technologies. However, only with ethically and legally responsible developments will the mistakes of the past be avoided. This contribution explores how current data management schemes are insufficient (...) to adequately safeguard data subjects, and in particular, it focuses on making these data flows transparent to provide an adequate level of accountability. To showcase this, and with the goal of enhancing transparency to foster trust, this paper investigates solutions for standardizing machine-readable policies to express personal data processing activities and their application to decentralized personal data stores as an example of ethical, legal, and technical responsible innovation in this field. (shrink)

Highlights: -/- • Breastfeeding and breastfeeding support can contribute to mitigating climate change. • Achieving global nutrition targets will save more emissions than fuel-switching. • Breastfeeding support programmes support a just transition. • This work can support the expansion of mitigation options in energy system models. -/- Abstract: -/- Renewable gas has been proposed as a solution to decarbonise industrial processes, specifically heat demand. As part of this effort, the breast-milk substitutes industry is proposing to use renewable gas as (...) a substitute for fossil natural gas. However, decarbonising the industrial processing of breast-milk substitutes can increase social license for these products, potentially undermining breastfeeding. World Health Organisation nutrition targets aim to increase exclusive breastfeeding to at least 50% globally by 2025 to improve maternal, infant, and young child health and nutrition. This target will have implications for the energy transition. A weakness of existing energy models is that demands for end-use products such as breast-milk substitutes are typically not considered explicitly. This paper develops an analytical framework for explicitly representing infant feeding methods in energy systems models. We compare the emissions saved in Ireland from decarbonising the industrial processing of breast-milk substitutes with renewable gas with the emissions saved by an increase in exclusive breastfeeding to 50% in both Ireland and a key export market, China. We demonstrate that the emissions saved from achieving the minimum global breastfeeding target are greater than when renewable gas is used to displace natural gas in the production of breast-milk substitutes in Ireland. We discuss the decarbonisation of breast-milk substitutes in relation to the principle of justice as non-maleficence, a principle based on the commitment to avoid harm, a novel application of a principle of justice. We conclude that breastfeeding support can be considered a demand-side measure for mitigating climate change by reducing the demand for energy services to produce breast-milk substitutes. A key recommendation is to position breastfeeding support as both a public health and a climate justice issue that is relevant for a just transition. The framework developed for this paper could be applied to support the inclusion of a wider range of mitigation options with social justice outcomes in energy system models. [Open access]. (shrink)

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

This 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)