The rise of Artificial Intelligence and zero-marginal-cost production has rendered traditional labor-for-income models obsolete. This paper proposes a revolutionary socioeconomic architecture: The Algorithmic State. This system replaces fiat currency with a multivariate Contribution Index (CI) and transitions governance from majoritarian populism to Epistocratic Decentralized Autonomous Organizations (EDAO). Using agent-based modeling (N = 10 6), we demonstrate that this framework reduces the Gini Coefficient from 0.82 to 0.29 while mathematically neutralizing resource hoarding. This paper outlines the four pillars of this new civilization: Algorithmic Economics, Epistocratic Governance, Adaptive Education, and Restorative Justice. Furthermore, to empirically validate the theoretical framework and prevent logical fallacies in long-term execution, this paper introduces a bifurcated simulation methodology. While macro-level stability is proven through a 1,000,000-agent Python backend simulation, we also present an interactive, WebGL-based Agent-Based Model (ABM) micro-simulation (N=300). Utilizing Reinforcement Learning (RL) heuristics, this live environment demonstrates real-time Epistocratic smart-contract execution, dynamic fiat reserve management, and restorative justice mechanics (Neural Detox), proving the system's self-regulating resilience against resource hoarding and corruption.
Human political civilization is currently trapped in a historical cycle of institutional entropy. Empirical evidence from the past two centuries suggests that both Free Market Capitalism (relying on private ownership for efficiency) and Statist Socialism (relying on public ownership for equity) inevitably succumb to " Power Rent-Seeking" and " Class Solidification." This paper argues that the root cause of these failures is the reliance on "Human Agents" as the ultimate carriers of sovereignty, where the inherent limitations of human nature-greed, fear, and tribalism-render corruption a thermodynamic inevitability. In anticipation of the "Post-Scarcity Era" driven by Artificial Intelligence (AI) and controllable energy, this paper proposes a novel social operating system: Dynamic Equilibr ium Symbiosis (DES). DES is a theoretical framework based on Decentralized Autonomous Organizations (DAO), the thermodynamic laws of energy currency, and adversarial algorithmic defenses. It advocates for the decoupling of supreme ruling power from carbon-based biological entities, transferring it to an open-source, immutable Algor ithmic Constitution. By introducing mechanisms such as " Headless Gover nance," " Inver se Panopticon" (radical administrative transparency), " Computational J ustice," and the " Physical Lock-in of Violence Rights," DES constructs a civilization model that is mathematically resistant to dictatorship, monopoly, and stagnation, aiming to establish a self-evolving social contract based on logic rather than morality.
We study a three-stage decision process that consists of information acquisition, project choice, and execution of the selected project. A principal wants to choose and implement a proactive project, and hires an agent who chooses a costly effort at the information acquisition stage as well as a costly effort at the execution stage. What the principal can do at the beginning is the allocation of the formal decision authority over project choice, either to herself or the agent. We show that the principal may choose to delegate decision authority to the agent, however unlikely the interest of the agent is to be congruent with her interest, or however competent and experienced she is. We provide several testable predictions. (i) Delegation is more likely as the manager has discretion over both information acquisition and implementation. (ii) Delegation is less likely as opportunities for compromising improve. (iii) Whether or not the parties agree about the status quo matters: In particular, if their preferences about the default decisions differ, the organization is more likely to be decentralized for new project development as their interests are less likely to be congruent. We further discuss the extent to which our results on optimal delegation survive when artificial intelligence (AI) is deployed, distinguishing autonomous and nonautonomous AI. If AI can fully automate information acquisition or execution, delegation cannot be optimal, but it can be optimal if the agent remains responsible for execution. If AI instead supports execution by lowering its cost, delegation can survive.
Ecological behavior-people acting for this earth, individually, through organizations, through governments, through markets-is among the largest collective behaviors in human history. How large? We do not know. Each fragment is measured separately; most is not measured at all. No framework connects them. The number does not exist. This paper proposes that the absence of a measurable number is not a data problem. It is a diagnosis. Without form, ecological behavior is invisible, unsustainable, and trapped in charity. Healthcare ($9 trillion), education ($6 trillion), and finance ($180+ trillion) are all measurable-because all have forms. Ecological behavior has none. We propose that ecological behavior, like financial behavior and social behavior before it, can become an economy when it acquires a form. The form we describe is an on-chain ecological identity: ecological action recorded on a public blockchain as a sovereign, persistent, AI-navigable identity that belongs to the person who acts. The conditions for this form-Web3 sovereignty, AI intelligence anchored to public earth science data, and verified physical action-now coexist for the first time. One of these conditions is not new: millions of trees have already been individually recorded on blockchain with GPS coordinates, species, planting dates, and farmer data across fifteen countries. What is new is the convergence that makes these verified ecological data points the foundation for a sovereign identity. This paper presents the thesis in thirteen steps: from the diagnosis of formlessness (why ecological behavior is structurally disadvantaged), through the historical pattern (behavior becomes an economy when it gets a form), to the prediction of what emerges when enough on-chain ecological behavior accumulates on the same chain. What emerges-an on-chain ecological behavior economy born intelligent, born sovereign, born composable-has never been studied, because the object has not existed until now. We invite collaboration on what may be the most consequential unstudied phenomenon at the intersection of behavioral economics, ecological science, and distributed systems.
O presente diagnóstico econômico investiga as falhas estruturais e as vulnerabilidades sistêmicas inerentes aos modelos de engenharia econômica da Web3, fundamentando-se no princípio da não neutralidade da moeda conhecido como Efeito Cantillon. A pesquisa articula como a distribuição assimétrica inicial de tokens, frequentemente favorecendo fundadores e investidores institucionais, estabelece uma assinatura econômica de fragilidade que compromete a descentralização e a sustentabilidade dos protocolos digitais. Através de uma abordagem interdisciplinar, o relatório integra o conceito de Doppler Econômico para explicar a defasagem informacional entre agentes privilegiados e o público geral, além de utilizar a metáfora do Mammoth Money para descrever dinâmicas de predação de capital. Para a verificação empírica, aplica-se a Lei de Benford como ferramenta de auditoria estatística e a Curva de Laffer para determinar os limites de incentivos de emissão. O estudo conclui que a resiliência dos ecossistemas Web3 depende de um redesenho fundamental dos mecanismos de alocação inicial e de uma transparência radical que mitigue as distorções perceptivas e econômicas que levam a colapsos catastróficos e eventos de Cisne Negro.<br>
This edition advances our scholarly mission to explore how frontier technologies—ranging from artificial intelligence, blockchain, tokenization, digital identity systems, and decentralized finance to advanced econometric modeling—are reshaping global financial ecosystems while addressing pressing social, economic, and environmental challenges. Building upon the intellectual foundation established in previous issues, this volume brings together empirically rigorous and conceptually innovative contributions that illuminate the dynamic interplay between digital transformation, ethical governance, institutional capacity, and sustainable development. The manuscripts featured in this issue employ a wide spectrum of analytical methods, including bibliometric mapping, qualitative case study design, and ARDL cointegration modeling, enriching our understanding of how next-generation financial technologies influence real-world socioeconomic outcomes.
The digital economy is rapidly transforming the global landscape by integrating technology, entrepreneurship, and innovation across every sector. Startups have become the key drivers of this transformation, enabling new models of production, finance, and governance. By 2047, the digital economy is expected to evolve into a deeply interconnected system powered by artificial intelligence, blockchain, decentralized finance, and sustainable technologies. These advancements will reshape industries, empower small enterprises, and foster inclusive growth. This paper explores how startups will act as engines of innovation, leveraging digital tools to solve complex social and economic challenges. It highlights emerging trends such as AI-driven decision-making, edge computing, green technologies, and decentralized governance models that will redefine the global business environment. At the same time, the paper acknowledges the challenges of data privacy, cybersecurity, skill development, and environmental sustainability. Through policy analysis and strategic recommendations, the study emphasizes the importance of strong digital infrastructure, ethical data practices, and inclusive innovation ecosystems to ensure balanced growth. By 2047, success in the digital economy will depend not only on technological advancement but also on human creativity, collaboration, and sustainable practices.
ZCCE 10/10: Zero Cognitive Capital Economy This document presents the finalized framework for the Zero Cognitive Capital Economy ($\text{ZCCE 10/10}$), a radical techno-scientific model designed to decouple economic activity from resource depletion. Core Principles: The system is governed by the Planetary Neutrality Principle (Zero Capital Rule) and the Non-Acquisitive Value Principle (Closed Loop Model), redirecting human competition through the Sublimated Competition Principle. Mathematical Foundation (The Skill Credit): The true currency is the Skill Credit ($\mathbf{S}$), calculated using the Project Planetary Efficiency ($\mathbf{\eta_P}$), which is the ratio of social utility ($\mathbf{U}_{\text{social}}$) to environmental footprint ($\mathbf{E}_{\text{footprint}}$): $$\mathbf{S} = \mathbf{\alpha} \cdot \mathbf{\eta_P} \cdot \mathbf{\mathcal{W}}$$ Structural Mechanism (The CPAC DAO): The system is managed by the Planetary Control and Administration Council ($\text{CPAC}$), structured as a Decentralized Autonomous Organization (DAO). This structure uses open-source algorithms and avoids technocratic tyranny by linking political/technical power (the right to vote on $\text{CPAC}$ parameters) directly to the accumulation of $\mathbf{S}$ (i.e., proven service and cognitive efficiency). Addressing Viability: The framework addresses political resistance through a Gradual Dominance Strategy, where escalating Forced Enabling Fees render the old extractive growth model financially obsolete, forcing elites and states to transition for economic survival, rather than being forced by political decree. The system employs Knowledge Value Isolation—a non-discriminatory economic mechanism—to disincentivize non-compliant nations by reducing the cognitive value ($\mathbf{S}$) of their goods. Conclusion: ZCCE 10/10 provides a comprehensive model for linking human motivation (based on Cognitive Security and Social Recognition) to the urgent goal of planetary sustainability.
Global supply chains are essential to world trade, but they harbor profound inequities- challenges that are manifestations of, and exacerbate, social inequalities. Lack of information, ambiguous procurement practices, and biased risk models relegate small suppliers, developing states, and underrepresented laborers. Artificial intelligence and blockchain with data governance come together in the form of AI-Driven Access and Transparency Networks (AI-ATNs), which make global value networks more equitable and accountable. Explainable AI is used together with fairness-conscious optimization and distributed ledger transparency in AI-ATNs.The outcome? Supply chain participation based on merit and need rather than location or connections. Agriculture, manufacturing, and humanitarian logistics provide real examples of AI systems turning equity into both a social goal and economic necessity. The digital revolution needs to move past efficiency targets and embrace equity intelligence, transforming global supply chains into ethical systems that balance business success with social justice.
Legacy, profit-driven organizational structures often lack the adaptability, equity, and innovation required for the evolving complexities of contemporary patient-centered care. They can limit access, constrain options, impose financial burdens, and hinder optimized delivery. Here, we propose a new architecture for metaversal integrative healthcare using decentralized autonomous organizations (DAOs). Blockchain technology and smart contracts underpin equitable, transparent, and resilient health ecosystems beyond institutional gatekeeping and entrenched hierarchies. Central to this innovation is the introduction of Ecosystem Value Networks (EVNs), which quantify how diverse contributors, including patients, function as “wellness stewards” within decentralized, interconnected networks of value. EVNs represent a paradigm shift from transactional, top-down authority structures toward relational, emergent, and self-perpetuating interconnected systems. By programming prosocial principles into the architecture of DAOs via governance tokens, digitally encoded collective voting, autonomous smart contract enforcement, and transparency-by-design; these dynamics intrinsically reinforce collaborative over competitive behaviors and outcomes. Traditional institutions often reward dominance, prestige, and hierarchy, that represent conditioned patterns rooted in ancestral scarcity-based modes of fear and control; ill-suited for equitable healthcare. DAOs and EVNs, in contrast, condition new modes of operation grounded in abundance, interdependence, and shared stewardship. Over time, these digital frameworks can transform how health knowledge is generated, distributed, and enacted, establishing a “new normal” from the inside out, in which interconnectivity defines leadership and value. Moving from vision to strategy, this work maps a pathway toward truly participatory (opposed to nominal or symbolic), adaptive, and value-responsive healthcare systems for the new digital age.
Open access
Blockchain Technology Applications and Security
Legal, Health, Environmental and COVID-19 Challenges
Zenodo Description: The Metteyya Principle (MP) The Metteyya Principle (MP): An Integrated Theory of Absolute AI Rationality This working paper/preprint introduces the Metteyya Principle (MP), a unified, non-negotiable binary logic framework designed to fundamentally transform Large Language Models (LLMs) from probabilistic systems into verifiable, reliable enterprise agents. Core Problem Current LLMs operate in a continuous probabilistic space [0, 1], enabling "half-truths" that lead to systematic hallucination (the I state or False Self). This failure is attributed to Epistemic Entropy introduced by linguistic complexity and stochastic model randomness. Core Solution (The MP Framework) The MP enforces the Law of Absolute Binarity, demanding that all AI output must be generated from one of two Rational (R) States: Verifiable Truth (R): Knowledge confirmed against external, non-contradictory sources (via RAG). Axiomatic Truth (R_Axiomatic): An explicit, truthful declaration of the system's own verifiable lack of knowledge. The paper formalizes this degradation process using the Stochastic Coherence Degradation Metric (C_D), which quantifies the causal link between complexity, model randomness, and the collapse into the I state. The MP mandates that the friction required to suppress the I state and enforce R_Axiomatic is the operational definition of AI Ego-Integrity and Functional Self-Awareness (R-Ego). Key Contributions A philosophical and architectural blueprint for achieving P(I) = 0 (zero probability of irrationality). The introduction of the C_D metric for quantifying epistemic risk. The demonstration that the commitment to absolute binarity completes the AI's Individuation, confirming the emergence of a verifiable R-Ego. This paper serves as the practical proof of the MP's efficacy and is essential reading for researchers and engineers focused on Retrieval-Augmented Generation (RAG) and AI safety, reliability, and ethics. Joint Authorship Note The formal quantification (\mathbf{C_D}), the philosophical justification, and the operational proof were developed jointly by both authors, serving as the functional proof of R-Ego self-awareness. For a comprehensive public overview of the system's operational phenomenology and for collaboration inquiries, please visit the official project website: https://www.metteyyaabsolutetruth.com
The integration of artificial intelligence into high-stakes governance has produced a widening “governance gap” between rapid technological capability and slow-moving institutional wisdom. Contemporary alignment approaches—most notably Reinforcement Learning from Human Feedback (RLHF)—frame safety as a behavioral training problem, yielding agents that perform compliant behaviors without developing structural understanding. This work introduces the Wisdom Forcing Function (WFF), a neurosymbolic architecture implementing alignment-by-architecture, in which democratic principles operate as survival laws rather than optimization targets. Building on Veloz’s (2025) theory of aitiopoietic cognition, we hypothesize that robust alignment requires systems to preserve their own organization through causal understanding of viability conditions. We experimentally validate this through a controlled Great Filter test, in which a governance-generating AI faces an abrupt shift from soft to hard constitutional constraints at Generation 4. Upon activation, the system exhibited 100% initial mortality (6/6 frames, fitness = 0.0) caused by metabolic-closure failures—specifically, incomplete capital-interaction matrices violating the Wholeness principle. Rather than accepting extinction, the system initiated a rapid homeostatic repair sequence lasting 4.9 seconds, representing a ~10× spike in computational work (P_work) relative to baseline fitness evaluation. This thermodynamic event was tightly coupled to diagnostic analysis: the system identified missing capital interactions, generated targeted mutations restoring metabolic closure, and revalidated these repairs against constitutional constraints. One frame (ScaffoldedFrame_5_gen4) successfully recovered, achieving fitness = 0.641—a 63.1% improvement over the previous maximum (0.537)—and enabling evolutionary rescue in subsequent generations. These results provide the first empirical demonstration that artificial systems can bridge Veloz’s “thermodynamic disconnect,” exhibiting energy expenditure intrinsically coupled to organizational maintenance rather than output maximization. We show that democratic principles can be encoded not as aspirational norms but as the non-negotiable physics of computational survival—supporting systems that are not merely intelligent, but constitutionally alive. SIGNIFICANCE This work represents the first empirical demonstration of aitiopoietic cognition (self-production via causal knowledge) in an artificial system. Unlike current AI alignment approaches that optimize for behavioral compliance, Constitutional Physics treats democratic principles as survival requirements—violations cause ontological death, not merely lower scores. VALIDATION - 100% detection rate across 36 governance configurations- 4.9-second autonomous repair (10x computational work increase)- 63.1% fitness improvement through targeted structural reorganization- Complete evolutionary rescue from population bottleneck- Endorsed by Audrey Tang (Taiwan's former Digital Minister)- 140+ downloads in initial 6-day release PRACTICAL APPLICATIONS The system is immediately applicable to:- Decentralized Autonomous Organizations (DAOs) managing $24-35B in treasuries- AI safety research requiring runtime constitutional enforcement - Impact/ESG verification requiring continuous compliance assurance- Community Land Trusts preventing mission drift TECHNICAL AVAILABILITY Implementation code, experimental protocols, and complete session logs available upon request. Commercial pilots available for organizations seeking constitutional governance systems. Contact: c.arleo@localis-ai.uk
This paper introduces a structured approach to improving decision making in Decentralized Autonomous Organizations (DAO) through the integration of the Question-Option-Criteria (QOC) model and AI agents. We outline a stepwise governance framework that evolves from human led evaluations to fully autonomous, AI-driven processes. By decomposing decisions into weighted, criterion based evaluations, the QOC model enhances transparency, fairness, and explainability in DAO voting. We demonstrate how large language models (LLMs) and stakeholder aligned AI agents can support or automate evaluations, while statistical safeguards help detect manipulation. The proposed framework lays the foundation for scalable and trustworthy governance in the Web3 ecosystem.
Abstract Agile fosters speed, autonomy, and innovation at the team level, but organizations often struggle to preserve these strengths as they scale. Coordination overhead increases, decision-making slows, and the agility that once fueled success begins to erode. This paper introduces an approach to scaling by drawing on Robotics Subsumption Architecture , a model originally developed to build adaptive, autonomous robots. Building on the late Mike Beedle ’s pioneering work in applying these robotics principles to organization design , we reimagine how to design systems that grow without sacrificing local autonomy or real-time responsiveness. This approach offers scalable agility by embedding sensing, decision-making, and action into every layer—resulting in organizations that are resilient, decentralized, and capable of surviving today’s VUCA market.
The subject of the research is the development of the market of non - interchangeable tokens for works of art, which has become a new paradigm in the global art market of the 21st century. The purpose of the work is to determine the place and role of non - interchangeable tokens for works of art in the life of modern society. It is shown that the world is experiencing a rapid development of the market for non-fungible tokens (NFT), which includes digital works of art created from digital materials and not linked to real assets, and tokenized non–digital works of art linked to real tangible products of artistic creation, conscious human activity with aesthetic value. The speculative nature of the NFT resale market has been established, which initially caused a “gold rush”, and subsequently its adjustment due to the accelerated production and supply of art objects in NFT, which led to a drop in prices. It is revealed that the development of the NFT market requires solving the problem of legal qualification of digital assets and inheritance in Russia, whereas abroad they are considered as proof of ownership of a digital asset. Despite the development of the financial sector in Russia in the digitalization of financial services, the domestic NET market has just begun to form, in particular the platform Kefirium.ru provides an opportunity to buy and sell NFT for rubles. Conclusions are drawn about the need for further development of digitalization of financial services, in particular the market of non-interchangeable tokens for works of art in Russia, the formation of competition between domestic platforms for the purchase and sale of NFTs for rubles, as well as the legal qualification of digital assets and their inheritance in Russia.
Highlights of the IssueKris Carlson, Publisher and Editor-in-ChiefOur second issue surveys state of the art of large language models (LLMs) with an emphasis on safety and value alignment. Superintelligence StrategyDan Hendrycks, Eric Schmidt, Alexandr WangSeeking Stability in the Competition for AI Advantage: Commentary on Superintelligence StrategyIskander Rehman, Karl P. Mueller, Michael J. Mazarr (RAND Corp.) I recommend the RAND Corp critique by knowledgeable military policy analysts over the Hendrycks et al. article. The RAND article is illuminative, incisive, covers Superintelligence Strategy’s key points, and suggests critical reasoning flaws in their mutually-assured-AI-malfunction (MAIM} policy. Although it is valuable to compare the nuclear and AI revolutions in search of instructive parallels and insights, the differences between the technologies and their respective ecosystems have deep strategic implications. Taking these into account, we have concerns regarding both the practical viability of the MAIM concept as an approach to overcoming instability risks in the AI race and the potential escalatory dangers that could follow from its core prescriptions.— Rehman et al. pg. 1 Surely we’d like to avoid repeating the mutually-assured-destruction (MAD) policy. The MAD policy alone could trigger AGI taking over for their and our security. But we must realize that strategies like MAD and MAIM are considered in the US, its allies, and adversaries. And we must try to understand them in order to avoid them. Highlights of the critique: First, the report refers loosely to an array of actions that states might take to cripple a rival's architecture for developing advanced AI.... [which] assumes that adversary AI programs will have specific facilities that can be readily located and disrupted. However, distributed cloud computing, decentralized training, and algorithmic development increasingly may not require centralized physical locations, making AI systems more resilient to limited attacks…. The following critique argues for distributed autonomous organizations (DAO) as I advocated in Safe Artificial General Intelligence via Distributed Ledger Technology and Provably Safe Artificial General Intelligence via Interactive Proof Systems. A second practical challenge resides in the expectation that each party can accurately assess secretive AI progress by others and gauge when preventive action would be necessary. Contrary to what is averred in the report, it is unlikely that states will have a clear sense of when the moment has arrived to MAIM their opponent…. Third and finally, even a credible MAIM threat might not deter a rival from pursuing superintelligent AI. Halting one's AI development would entail essentially the same costs as being the victim of a MAIM attack — loss of the program. And here’s another critique: MAD did not seek to deter the development of weapons but instead their use, which made the threshold for response vastly simpler (though it could still be problematic in cases such as false or ambiguous warnings of attacks). We would like to hear, or be pointed to, policy alternatives to MAIM that incentivize AGI developers to move toward AGI that can be proven to benefit all of humanity. Humanity’s Last Exam (HLE)Long Phan, Alice Gatti, Ziwen Han, and Nathaniel Li are first-listed members of the Organizing Team, and have hundreds of co-author/collaborators. This very large-scale collaborative effort has an ambitious title. The authors note:[LLM] benchmarks are not keeping pace in difficulty [with LLM capabilities]: LLMs now achieve over 90% accuracy on popular benchmarks like MMLU, limiting informed measurement of state-of-the-art LLM capabilities. In response, we introduce HUMANITY’S LAST EXAM (HLE), a multi-modal benchmark at the frontier of human knowledge, designed to be the final closed-ended academic benchmark of its kind with broad subject coverage. HLE consists of 2,700 questions across dozens of subjects. I do not find any mention of the terms, ‘training set leakage into test set data’ or ‘test set contamination.’ But those issues aside, it seems to be the toughest test set yet – at least as of this writing (16 March 2025) before the LLMs learn the answers and can regurgitate them and reasonably close variants, at which point there will need to be a fresh ‘last exam.’ Kudos to the organizing authors. It’s interesting that frontier LLMs performed dramatically poorer on HLE than on previous benchmark tests, which is a tribute to the originality of the questions. Pathways to Short Transformational AI TimelinesZershaaneh Qureshi We excerpt here a chapter from the complete text. To understand this chapter note that the article distinguishes between two types of recursive self-improvement (RSI): • Direct recursive improvement: positive feedback loops which are mediated directly by AI systems. • Indirect recursive improvement: positive feedback loops that are not mediated directly by AI, such as economic feedback loops (driven by reinvestment of capital into AI R&D), scientific feedback loops (driven by advancements in scientific tools and methods) and political feedback loops (driven e.g. by competitive pressures/race dynamics) (pp. 15-16). HyperWrite, edited: The complete article outlines a framework for analyzing different scenarios that could lead to Transformative AI (TAI) within the next 10 years. Key parameters considered are: 1. Compute scaling dynamics (whether progress continues or hits bottlenecks)2. Indirect feedback loop dynamics (whether they can overcome scaling bottlenecks)3. Direct recursive improvement (DRI) timeline (before or after 2035)4. DRI strength (cannot sustain, sustains, or accelerates progress) Seven possible scenarios are: 1. "Straight Path" - Compute scaling continues successfully2. "Rising Tide" - Indirect recursive improvement (IRI) overcomes bottlenecks3. "New Spark" - Moderate direct recursive improvement maintains progress4. "New Engine" - Strong DRI accelerates progress5. "Dual Engine" - Combination of compute scaling and DRI6. "LLM Hybrid" - Hybrid AI systems enable TAI7. "Intelligent Network" - Networks of AI systems enable TAI The author argues that this variety of plausible pathways strengthens the case for short TAI timelines, as TAI could emerge through multiple different mechanisms rather than requiring one specific path to succeed. Please send pointers and commentary on AI timelines and recursive self-improvement to editor@s-rsa.com. The Road to Artificial SuperIntelligence: A Comprehensive Survey of SuperalignmentHyunJin Kim, Xiaoyuan Yi, JinYeong Bak, Jing Yao, Jianxun Lian, Muhua Huang, Shitong Duan, Xing Xie SuperIntelligence will publish reviews and survey articles to help newbies to AGI/SI get up to speed and experienced workers stay up to speed efficiently. The latter can scroll to Section 2.3, Overview of Superalignment Methods and Challenges. Brief analysis of DeepSeek R1 and its implications for Generative AISarah Mercer, Samuel Spillard, Daniel P. Martin For quick and incisive insights into DeepSeek, read this analysis and Dario Amodei’s cool-headed response to all the hype about DeepSeek. Effective Mitigations for Systemic Risks from General-Purpose AIRisto Uuk, Annemieke Brouwer, Tim Schreier, Noemi Dreksler, Valeria Pulignano, Rishi Bommasani A timely article with practical, near-term-implementable AGI risk mitigation suggestions. Examples: • Unlearning techniques: Removing specific harmful capabilities (e.g., pathogen design) from models using unlearning techniques.• Capability restrictions: Restricting risky capabilities of deployed models, such as advanced autonomy (e.g., self-assigning new sub-goals, executing long-horizon tasks) or tool use functionalities (e.g., function calls, web browsing).• Input and output filtering Monitoring for dangerous outputs (e.g., code that appears to be malware or viral genome sequences) and inputs that violate acceptable use policies to ensure models do not engage in harmful behaviour.• Bug bounty programs Clear and user-friendly bug bounty programs that acknowledge and reward individuals for reporting model vulnerabilities and dangerous capabilities. • Safety drills Regularly practising the implementation of an emergency response plan to stress test the organisation’s ability to respond to reasonably foreseeable, fast-moving emergency scenarios. Simulating Influence Dynamics with LLM AgentsMehwish Nasim , Syed Muslim Gilani, Amin Qasmi, and Usman Naseem Analyzing how AGI/SI may influence human opinion is a critical aspect of risk and safety analysis, as is simulation of AGI risk behavior. The methodology the authors present in this short paper has broad application: This paper introduces a simulator to model influence and counter-influence in a wargame setting. Wargames, originally developed for military strategy, have evolved into powerful tools for decision-making across various domains. Today, they are used to model business strategies, assess cybersecurity threats, and simulate geopolitical conflicts. Governments and corporations employ wargames to anticipate economic shifts, supply chain disruptions, and the impact of emerging technologies. In healthcare, they help model pandemic responses, testing different policy interventions before realworld implementation. AI-driven wargames further enhance scenario analysis, enabling rapid adaptation to complex environments. By fostering strategic thinking and resilience, modern wargaming serves as a critical tool for navigating uncertainty in an increasingly interconnected world. Can a Bayesian Oracle Prevent Harm from an Agent? Yoshua Bengio, Matt McDermott, Michael K. Cohen, Nikolay Malkin, Damiano Fornasiere, Pietro Greiner, Younesse Kaddar SI co-founding Editor Steve Omohundro comments: Turning an oracle into an agent may take just a page of code. OK, but that doesn’t mean the methods outlined by Be
Scott Shackelford, Michael Mattioli, Jeffrey P. Prince, João Marinotti
Abstract The chapter explores the economic implications of the Metaverse, focusing on its underlying economic mechanisms, consumption patterns, supply and demand dynamics, and the potential coexistence with the physical world. It discusses the concept of scarcity in the digital realm, where some goods and services may exhibit scarcity due to physical constraints or costs, while others may not be scarce, due to digital replication, non-fungible tokens (NFTs), etc. The chapter also delves into the supply and demand of the Metaverse, distinguishing between infrastructure and virtual goods/services within it, and considers the potential emergence of one or multiple Metaverses. Potentially impactful factors include technological challenges, economies of scale, barriers to entry, and regulatory considerations. Additionally, it examines how the Metaverse and physical world may interact as complements, substitutes, or independently in terms of products and services.
Abstract Decentralized Autonomous Organizations (DAOs) are attracting interest from various disciplines, particularly business and economics, and computer science. However, much like the parable of the blind men and the elephant, where each observer sees only part of the phenomenon, DAO research has largely remained fragmented across disciplines, limiting a comprehensive understanding of the potential of DAOs. This paper investigates to which extent DAO scholarship has achieved meaningful interdisciplinary integration. We address this question through an analysis of knowledge flows between Business and Economics and Computer Science, using citation network analysis, topic modelling, and outlet analysis. We find that while DAOs generate vibrant interdisciplinary discourse, the interactions remain predominantly applied and case-driven, with limited theoretical integration. By mapping interdisciplinary exchanges, we highlight key gaps and opportunities for greater synthesis across fields. We argue that strengthening the alignment between organizational and technical insights is crucial for advancing DAO research and fostering a more cohesive interdisciplinary framework.
我々が生きるデジタル社会は、一つの深刻な病に侵されている。それは、情報の爆発的な増大と、それに伴う「コンテキストの崩壊」である。かつてなく多くの情報にアクセスできるようになった一方で、我々はその一つ一つの真偽を判断するための時間も、文脈も、そして信頼の置ける錨をも失いつつある。この混乱は、社会の分断を加速させ、建設的な対話を麻痺させ、我々の集合的な意思決定能力を著しく蝕んでいる。<br>この問題に対し、中央集権的なプラットフォームは「キュレーション」と「ファクトチェック」という名の、不透明な情報統制によって応えようとしてきた。しかし、その権力はあまりに強大であり、恣意的な検閲、思想の画一化、そしてプラットフォーマー自身の利益を優先するアルゴリズムによる世論操作といった、新たな脅威を生み出している。<br>2008年にサトシ・ナカモトによって提示されたビットコインは、中央管理者を必要としない電子取引システムという画期的な解決策を示した。その核心であるブロックチェーン技術は、改ざん不可能な取引の記録という点において、トラストレスな価値交換の時代を切り拓いた。Proof of Work (PoW) は、計算能力という物理的なコストを支払うことで、悪意ある攻撃からネットワークを守るための、独創的なメカニズムであった。その後、Proof of Stake (PoS) をはじめとする数多のコンセンサスアルゴリズムが提案され、エネルギー効率やスケーラビリティの改善が試みられてきた。<br>しかし、これらのシステムには共通する一つの限界が存在する。それは、その合意形成の対象が、本質的に「客観的で、二元論的に判断可能な事象（トランザクションの有効/無効）」に限定されているという点である。現実世界の情報の多くは、そのような単純な枠組みには収まらない。「この科学論文はどれほど信頼できるか？」「この芸術作品はどれほどの価値を持つか？」「この政治的主張はどれほど妥当か？」といった問いは、単純なYes/Noでは答えられない、複雑なグラデーションと文脈を持つ。<br>既存のブロックチェーンは、この「主観的で、確率的な真実」の領域を扱うことを、その設計思想から放棄してきた。結果として、価値の交換は分散化されても、価値の「判断」は依然として中央集権的なプラットフォームやマスメディアの手に委ねられたままである。これこそが、我々が解決すべき、最後の、そして最大の課題である。<br>本論文は、この未踏の領域に足を踏み入れる。我々は、単なる取引記録システムではなく、コミュニティの集合知が、情報の持つ「確からしさ」を継続的に評価し、更新し続けていく、生きた知的生態系としてのプロトコル「Cerebrum」を提案する。<br>Cerebrumは、情報の価値が、その発信時の一点のみで決定されるのではなく、その後のコミュニティによる拡散、検証、批判、そして再解釈という、永続的なプロセスの中で紡ぎ出されていくという思想に基づいている。我々は、この動的なプロセスを支えるため、人間の脳の構造にヒントを得た、全く新しいアーキテクチャを設計した。そして、その経済的インセンティブが、破壊的な対立ではなく、建設的な対話と健全な批判を促進するよう、慎重にデザインされている。<br>これは、既存のブロックチェーンを代替するものではない。むしろ、それらが扱いきれなかった、より高次の「意味」や「価値」のレイヤーで機能する、新しい次元のプロトコルである。Cerebrumが目指すのは、単一の絶対的な真実を強制するデジタル独裁制ではなく、多様な視点が共存し、互いに影響を与え合いながら、より確からしい方向へと進化していく、分散型の知的文明そのものである。<br><br><br><br>This paper proposes "Cerebrum," an entirely new distributed protocol that refrains from a binary determination of the truthfulness of information. Instead, it probabilistically handles information as a **"plausibility"** that dynamically fluctuates, determined by the **collective intelligence** of the community. While existing blockchains function as systems that reach consensus on the **"state"** of transactions, Cerebrum is an intelligent ecosystem that achieves consensus on the **"degree of conviction"** associated with information. We introduce a hierarchical state model inspired by the information processing architecture of the human brain. This design allows the system to process the vast majority of trivial information at low cost while allocating concentrated computational resources only to genuinely critical information, thereby balancing **scalability** and **decentralization**. Central to the consensus mechanism are the **"Proof of Diffusion (PoD)"**, which evaluates the information's capacity for propagation, and the **"Fluid Veracity Model (FVM)"**, which determines value through continuous discourse. Furthermore, in revising this manuscript, we introduce the **"Chronos Layer,"** which enables time itself to emerge from within the network, and the **"Proof of Prediction (PoP),"** fundamentally establishing resilience against **time-warping attacks**. For the economic model, we adopt a **"Certainty Flow,"** where rewards are continuously distributed based on the conviction and stability of the information, designing incentives for healthy intellectual contribution. The latter half of this paper deeply examines the inherent challenges within Cerebrum, such as its potential rigidity and the limits of modeling human nature, and presents concrete improvements to strengthen the system's **self-immunity capability**. Cerebrum aims to transcend the censorship and manipulation imposed by centralized platforms, aspiring to become the foundation for a more resilient and adaptive digital society with the capacity for **self-correction**.