Sundara Srivathsan M, Lighittha P. R., Prithivraj S., R. Suganya ¡ 5 authors
Web3 platforms face a critical challenge: once unsafe content is minted on-chain, it becomes immutable and irrevocable. Traditional NSFW classifiers operate off-chain without cryptographic guarantees, leaving blockchain ecosystems vulnerable to harmful content. We present VisionGuard, a unified moderation framework that integrates cost-sensitive AI decision-making with blockchain-based enforcement. Our system combines calibrated NSFW classification, abstention-based triage for uncertain cases, perceptual hashing for near-duplicate detection, and on-chain k-of-n quorum attestation using EIP-712 signatures. We establish formal guarantees for: (i) Bayes-optimal cost-sensitive thresholds minimizing asymmetric error costs, (ii) optimal abstention intervals for human review, (iii) monotone false-negative reduction under classifier-pHash fusion, (iv) quorum compromise bounds, and (v) end-to-end unsafe-mint probability. Empirical validation on a zero-shot NSFW task demonstrates 82% accuracy (AUC =0.88), with the Bayes-optimal threshold (Ďâ=0.1) reducing expected cost to 27,520 versus 54,942 at the F1-optimal thresholdâa 50% improvement. Calibrated abstention further lowers harm (cost =10,649.5), while a 3-of-5 quorum with oracle compromise p=0.1 yields break probability Pbreak<1%. Together, VisionGuard bridges decision theory, adversarial robustness, and cryptographic enforcement, providing the first provably safe AI moderation pathway for blockchain content.
Non-fungible tokens (NFTs) are unique digital tokens issued on a blockchain to represent the proof of ownership of (digital) items. Despite their impressive technological capabilities and millions of users, research and practice lack an understanding of the factors motivating NFT purchases. In this study, we employ a sequential mixed-method approach to reveal what drives users to purchase NFTs. We performed 65 in-depth interviews (Study 1) with individuals who purchased at least one NFT to explore the factors that influence their decisions. Building on these insights, we carry out two surveys: one with 265 individuals who have purchased NFTs (Study 2), and another with 272 individuals who have considered buying an NFT but have not done so (Study 3). Using a fuzzy-set qualitative comparative analysis, we reveal the combinations of influencing factors leading to NFT adoption in our sample. Building on self-determination theory, our aggregated findings emphasize the importance of intrinsic interest. We developed four propositions grounded in our data to guide future research. This study provides unique empirical insights into the adoption behaviour of NFTs as an emerging technology from a user perspective.
Ziyang Ji, Jie Zhang, Yuji Dong, Ka Lok Man ¡ 6 authors
Effective management of private keys is crucial to ensure the security and ownership of usersâ data and digital assets in the Web3 environment. However, existing solutions often fail to adequately address private key management from the userâs perspective. Private key leakage and loss incidents occur frequently, resulting in significant losses of digital assets. Moreover, the conventional approach of revoking both the private and public keys after a leakage or loss accident is inconvenient in Web3, where the public key serves as the userâs wallet address or digital identity. To tackle the issue of user-side private key management in Web3, this paper presents KeyShield which is a leakage-and-loss-resilient private key protection scheme. KeyShield divides the userâs private key into three shares, securely stored across a primary device and a secondary device owned by the user, and a third storage module owned by the user or a semi-trusted service provider. For daily use of the private key, the user only needs to connect the primary and secondary devices. In the event of a leakage or loss, such as device theft or attack, an update process will be triggered to update the three shares, immediately invalidating the leaked or lost share while causing no changes to the public key. As a demonstration of KeyShield, we developed KeyShieldECC accessible on both Android and iOS platforms for managing Elliptic Curve Cryptography (ECC) private keys. The testing results show that for a 256-bit ECC private key, the daily use only needs 0.05 seconds and update needs 0.25 to 0.3 seconds on an ordinary smart phone.
Sustainable Development Goal 7 (SDG-7) seeks universal access to affordable, reliable, and modern energy by 2030, yet progress remains uneven and structurally constrained. Despite declining renewable energy costs, around 685 million people lack electricity and more than 2 billion depend on traditional biomass for cooking. This review moves beyond descriptive assessments by providing a systematic, decision-oriented synthesis of SDG-7 pathways. Using a replicable PRISMA-informed protocol, it integrates peer-reviewed studies and authoritative international datasets published between 2015 and 2025. Centralized, decentralized, and hybrid energy systems are evaluated in terms of technical maturity, affordability, governance feasibility, and socio-environmental impacts. A structured barrier-to-intervention framework identifies context-specific challenges, including intermittency, financing risk, institutional capacity, infrastructure gaps, and climatic and geopolitical exposure, alongside viable technological and policy responses. Comparative case studies from India, Sub-Saharan Africa, Southeast Asia, and Latin America explain divergent outcomes of similar technologies across institutional and market contexts, and development pathways globally.
Context: Blockchain and AI are increasingly explored to enhance trustworthiness in software engineering (SE), particularly in supporting software evolution tasks. Method: We conducted a systematic literature review (SLR) using a predefined protocol with clear eligibility criteria to ensure transparency, reproducibility, and minimized bias, synthesizing research on blockchain-enabled trust in AI-driven SE tools and processes. Results: Most studies focus on integrating AI in SE, with only 31% explicitly addressing trustworthiness. Our review highlights six recent studies exploring blockchain-based approaches to reinforce reliability, transparency, and accountability in AI-assisted SE tasks. Conclusion: Blockchain enhances trust by ensuring data immutability, model transparency, and lifecycle accountability, including federated learning with blockchain consensus and private data verification. However, inconsistent definitions of trust and limited real-world testing remain major challenges. Future work must develop measurable, reproducible trust frameworks to enable reliable, secure, and compliant AI-driven SE ecosystems, including applications involving large language models.
Modern blockchain applications benefit from the ability to specify sequencing constraints on the transactions that interact with them. This paper proposes a principled and axiomatically justified way of adding sequencing constraints on smart contract function calls that balances expressivity with the tractability of block production. Specifically, we propose a system in which contract developers are allowed to set an integer global priority for each of their calls, so long as that the call's chosen priority is no higher than the priority of any of its referenced calls. Block builders must then simply sequence transactions in priority order (from high to low priority), breaking ties however they would like. We show that this system is the unique system that satisfies five independent axioms.
The meme coin ecosystem has grown into one of the most active yet least observable segments of the cryptocurrency market, characterized by extreme churn, minimal project commitment, and widespread fraudulent behavior. While countless meme coins are deployed across multiple blockchains, they rely heavily on off-chain web and social infrastructure to signal legitimacy. These very signals are largely absent from existing datasets, which are often limited to single-chain data or lack the multimodal artifacts required for comprehensive risk modeling. To address this gap, we introduce MemeChain, a large-scale, open-source, cross-chain dataset comprising 34,988 meme coins across Ethereum, BNB Smart Chain, Solana, and Base. MemeChain integrates on-chain data with off-chain artifacts, including website HTML source code, token logos, and linked social media accounts, enabling multimodal and forensic study of meme coin projects. Analysis of the dataset shows that visual branding is frequently omitted in low-effort deployments, and many projects lack a functional website. Moreover, we quantify the ecosystem's extreme volatility, identifying 1,801 tokens (5.15%) that cease all trading activity within just 24 hours of launch. By providing unified cross-chain coverage and rich off-chain context, MemeChain serves as a foundational resource for research in financial forensics, multimodal anomaly detection, and automated scam prevention in the meme coin ecosystem.
Mohamed Amine Legheraba, Nour Rachdi, Maria Gradinariu Potop-Butucaru, SĂŠbastien Tixeuil
Recently, a novel peer sampling protocol, Elevator, was introduced to construct network topologies tailored for emerging decentralized applications such as federated learning and blockchain. Elevator builds hub-based topologies in a fully decentralized manner, randomly selecting hubs among participating nodes. These hubs, acting as central nodes connected to the entire network, can be leveraged to accelerate message dissemination. Simulation results have shown that Elevator converges rapidly (within 3--4 cycles) and exhibits robustness against crash failures and churn. However, its resilience to Byzantine adversaries has not been investigated. In this work, we provide the first evaluation of Elevator under Byzantine adversaries and show that even a small fraction (2%) of Byzantine nodes is sufficient to subvert the network. As a result, we introduce LIFT, a new protocol that extends Elevator by employing a cryptographically secure pseudo-random number generator (PRNG) for hub selection, thereby mitigating Byzantine manipulation. In contrast, LIFT withstands adversarial infiltration and remains robust with up to 10% Byzantine nodes. These results highlight the necessity of secure randomness in decentralized hub formation and position LIFT as a more reliable building block for Byzantine-resilient decentralized systems.
Do the functional narratives in cryptocurrency whitepapers correspond to how their tokens behave in markets? We develop a content-verified, contamination-aware pipeline for measuring structural correspondence between project narratives and market structure, and report two results. The first is a cautionary one. An apparent entity-level signal in an earlier version of our corpus -- specialised tokens appearing to align more strongly than broad infrastructure tokens -- was entirely an artifact of corpus contamination: roughly a quarter of the documents were failed-download stubs or wrong-document whitepapers (for example, a "Cosmos" entry that was in fact Binance Smart Chain text), and the apparent ordering does not survive content verification: on the clean corpus no token registers as helping alignment. We therefore report it as a contamination diagnosis, not a finding. The second is an honest null. Combining zero-shot NLP classification of 43 content-verified whitepapers across 10 semantic categories with seven cross-sectional market-structure statistics computed from hourly data (17,543 timestamps, 2023-2024), and aligning the two spaces with Procrustes rotation and Tucker's congruence coefficient ($Ď$), we do not detect a significant claims-market alignment in this $n = 43$ sample (dimension-matched $Ď= 0.303$, zero-padded $Ď= 0.223$; both non-significant). A positive-control and power analysis shows the binding constraint is the low reliability of the text instrument: the minimum detectable effect is $Ď\approx 0.66$, well above the observed $\approx 0.22$. This is absence of evidence for alignment, not evidence of its absence -- we can reject strong alignment ($Ď\geq 0.70$) but cannot distinguish weak alignment ($Ď\approx 0.3$) from none.
Prediction markets offer a natural testbed for trading agents: contracts have binary payoffs, prices can be interpreted as probabilities, and realized performance depends critically on market microstructure, fees, and settlement risk. We introduce PredictionMarketBench, a SWE-bench-style benchmark for evaluating algorithmic and LLM-based trading agents on prediction markets via deterministic, event-driven replay of historical limit-order-book and trade data. PredictionMarketBench standardizes (i) episode construction from raw exchange streams (orderbooks, trades, lifecycle, settlement), (ii) an execution-realistic simulator with maker/taker semantics and fee modeling, and (iii) a tool-based agent interface that supports both classical strategies and tool-calling LLM agents with reproducible trajectories. We release four Kalshi-based episodes spanning cryptocurrency, weather, and sports. Baseline results show that naive trading agents can underperform due to transaction costs and settlement losses, while fee-aware algorithmic strategies remain competitive in volatile episodes.
Introduction: Blockchain-enabled products (e.g., cryptocurrencies and fan tokens) have rapidly expanded across professional sport, but the research landscape remains dispersed across finance, marketing, information systems, and sport management. Methods: This study conducted a thematic review of Web of Science Core Collection records supplemented by snowball searching, yielding 30 English-language peer-reviewed studies published between 2019 and 2025. Results: Based on the included titles, we mapped how the literature has developed and what it collectively implies for sport organizations, platforms, and consumers. Five recurring strands were identified: (1) fan tokens and sport cryptoassets as financial assets, emphasizing volatility, spillovers, and sensitivity to sport- and crypto-market events; (2) adoption, identity, and engagement research explaining why supporters buy/hold tokens, participate in voting, and engage in advocacy; (3) computational and platform-data approaches (e.g., sentiment/discourse analyses and poll/voting participation patterns) to quantify online engagement and market narratives; (4) blockchain applications and governance, including stakeholder-oriented discussions and ethical critiques regarding value creation, transparency, and power asymmetries; and (5) gambling-like risks and addiction-related correlates, highlighting the convergence of trading, betting-like dynamics, and potentially harmful consumption. Discussion: Limitations include dependence on WoS-indexed English-language publications, topic and context concentration (especially European football and major platforms), and heterogeneity in study designs and outcomes that precludes comprehensive data synthesis. Future research should broaden contexts beyond dominant sports/regions and use stronger longitudinal or quasi-experimental designs to test mechanisms and harms.
In this paper, I argue that developmental stage theories and the six functional primitives proven necessary for adaptive decision-making are not merely analogous: they are two independently-discovered solutions to the same structural problem, and their convergence is evidence of that shared structure rather than of coincidence. The computational foundation is Ismail's Primitives (Ismail, 2026, V6.1) â a Lean 4/Mathlib formalization with zero sorry, zero custom axioms, and zero opaque terms â establishing that six functional properties are each necessary for sublinear regret under uncertainty, mutually irreplaceable, and compose into a self-reinforcing directed information chain: Objective Tracking, Cross-Context Safety Transfer, Global Attractor Exploration, Policy Simplification, Feasibility Projection, and Feedback Adaptation. The mapping. I align these six primitives, in sequence, against three developmental traditions built from incompatible methods and foundational assumptions about what psychology is: Erikson's psychosocial stages (clinical psychoanalytic observation), Maslow's motivational hierarchy (humanistic psychology's healthy-population method), and Bowlby's attachment phases (ethology and evolutionary biology). None was constructed with reference to the others. The alignment does more than pair labels: it supplies the first computational-rationality account of why these stages occur in this order and no other, and reframes their convergence as convergent evolution of functional architecture â artificial and biological systems arriving independently at the same sequential solution because they face the same adaptive problem, not because they share mechanisms or ancestry. The evidence. Three theoretical traditions, developed independently, using different methods, on different populations, converging on the same six-stage functional sequence is consilience in Whewell's (1840) and Wilson's (1998) technical sense: independent lines of inquiry arriving at the same structural conclusion. The necessity framework is the first principled account of why that convergence exists. The scope. Machine verification settles whether the six primitives are necessary and mutually irreplaceable as properties of decision processes; it does not settle whether human development instantiates them. That second claim is argued here on the consilience evidence above, not asserted by proof. This paper's role is to establish the functional bridge itself â the mapping, its theoretical licensing (multiple realizability, Marr's levels, computational rationality), and the testable predictions it generates for stage universality, cross-cultural variation, developmental arrest, intervention timing, and clinical and educational practice. A fuller clinical elaboration is developed in companion work. To this paper's knowledge, no developmental stage theory has previously been given an explicit computational-necessity account of why its stages occur in one fixed order rather than another, let alone one now grounded in a machine-checked proof. The companion mathematics paper and its complete Lean 4 formalization â zero sorry, zero custom axioms, ~12,700 lines, every theorem cross-referenced to its exact identifier â are at github.com/M-Ismail-ZA/IsmailsPrimitives (Zenodo: doi.org/10.5281/zenodo.21177368). For any feedback or collaboration, please contact me via the email address listed on the paper. Updated: 8 July 2026 (V3).
Bitcoin, which was established in 2009, has turned into a worldwide cash. Bitcoin is a decentralized computerized money that isn't supported by any administration or national bank. It very well might be utilized to buy labour and products from retailers who acknowledge bitcoins. These bitcoins act as scrambled information lumps. This information is sent starting with one individual then onto the next, and the exchange is affirmed, i.e., cash is spent, requiring a lot of figuring ability to verify the singular exchanges precisely. The shared organization screens and ensures bitcoin moves between clients. It could be utilized to book inns, shop, do monetary exchanges, and even purchase computer games. The advancement of bitcoin digital money, the development of blockchain, and its utilization in certifiable substances are made sense of. This exploration paper will cover the ascent of Bitcoin in India
Open access
Blockchain Technology Applications and Security
Cyberloafing and Workplace Behavior
Innovations and Analysis in Business and Education
The rapid expansion of the Internet of Things (IoT) has necessitated a shift to distributed Edge environments, rendering traditional perimeter security obsolete and exposing scalability bottlenecks in centralized Zero-Trust Architecture (ZTA). This paper proposes a novel, decentralized ZTA framework that integrates Directed Acyclic Graph (DAG) distributed ledgers with Attribute-Based Access Control (ABAC) to eliminate single points of failure. By leveraging asynchronous DAG protocols (e.g., IOTA Tangle, Obyte) instead of linear blockchains and using lightweight Elliptic Curve Cryptography (ECC) for resource-constrained devices, the system enables fee-less, parallel transaction processing. Quantitative analysis demonstrates the framework's superior performance, achieving over 1,000 transactions per second (TPS), sub-second finality, and 15ms encryption times on commodity hardware, thereby establishing a robust, partition-tolerant security model for the future Internet of Everything.
In digital security, anonymous credential systems are essential to ensure secure and private interactions. These systems have practical applications in various fields, such as online voting, healthcare, and financial services. However, due to high computational overhead and complex architecture, traditional anonymous credential systems often suffer from efficiency and scalability issues. To address these challenges, we propose an innovative approach that combines advanced cryptographic techniques such as randomized BLS aggregate signatures and optimized zero-knowledge proof usage mechanisms to achieve secure and private identity authentication with minimal overhead. We introduce HPPCS (High-Performance Privacy-Preserving Credential System), an anonymous credential framework that leverages randomizable aggregate signature technology to achieve efficiency and strong security. We conducted a security and experimental analysis of the HPPCS framework, and the results showed that HPPCS improves the efficiency of credential generation and verification while ensuring original security. This work establishes a powerful and practical framework for privacy-centric identity authentication systems.
Current agent payment standards enable transactions across varied infrastructure, including card systems, banking channels, and blockchain platforms, through cryptographic mandates binding user intentions to agent actions. These mandates create authorization structures while revealing critical vulnerabilities in transaction privacy protection, fine-grained delegation management, and cohesive governance implementation across multiple payment infrastructures. Zero-Knowledge Mandates introduce cryptographic techniques allowing agents to demonstrate compliance with spending restrictions while concealing constraint details from verifiers. Agents demonstrate compliance with spending caps, approved vendors, and time restrictions while keeping financial details and payment channel choices hidden. The system uses compact cryptographic proofs that allow verification without exposing mandate terms, user account information, or transaction routing. Core security guarantees include execution unlinkability, preventing transaction correlation, and verifiable compliance, ensuring constraint adherence. Technical implementation utilizes efficient proof systems, maintaining real-time transaction processing requirements. Evaluation addresses computational performance, information leakage boundaries, and practical deployment considerations across heterogeneous payment networks. The resulting architecture provides the first comprehensive privacy-preserving authorization primitive for autonomous commercial agents operating across multiple financial infrastructures simultaneously.
Ru Li, Jie Cui, Lu Wei, Irina Bolodurina ¡ 6 authors
In vehicular ad hoc networks (VANETs), distributed identity authentication provides the foundation for securing sessions among entities over wireless channels while eliminating single points of failure. However, existing distributed authentica tion schemes for VANETs typically make unrealistic assumptions about node reliability and trustworthiness, failing to account for scenarios where authentication nodes may be compromised or collude with vehicles. Moreover, these schemes expose the com munication process to linkability attacks while allowing vehicles to self-register their public keys. To address these limitations, we propose a privacy-preserving and accountable distributed collab orative authentication scheme for VANETs that is resilient to ma licious nodes. Using threshold signature techniques, distributed authentication nodes collaboratively perform decentralized ve hicle identity authentication using a predefined threshold. Zero knowledge proof protects the privacy of the signing process while maintaining accountability and effectively preventing malicious behavior by nodes under external or internal adversarial attacks. Furthermore, vehicles self-register their public keys via smart contracts and blockchain technology, ensuring anonymity and unlinkability during registration while enabling the traceability of malicious vehicles. Security and performance analyses show that the proposed scheme enhances the security and robustness of distributed collaborative authentication in VANETs, achieving a better balance between computational and communication costs than existing schemes
ABSTRACT Nonâfungible tokens (NFTs), as blockchainâbased cryptographic assets certifying unique digital ownership, have emerged as a transformative force in brandâconsumer interactions. Building on prior work that primarily examined the social value of complementary NFTs, the current research advances the literature by systematically comparing two fundamental NFT typologies: complementary NFTs (interrelated collections with stylistic and attribute variations) and replicative NFTs (characterized by serialized identical or similar units). Through four experiments, this research demonstrates that these NFT types differentially influence core brand relationship constructsâwhile complementary NFTs prove more effective in cultivating brand intimacy, replicative NFTs significantly enhance perceived brand congruence. Moreover, brand history and brand strength are key boundary conditions moderating these effects. Our findings not only systematically demonstrate the divergent effects of replicative and complementary NFTs on consumer perceptions but also provide actionable guidelines for NFT portfolio strategy based on specific brand relationship objectives.
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
The Clay Does Not Wake Up On Dario Amodei's "The Adolescence of Technology" and the Dissolution of Responsibility I. The Sermon Dario Amodei's essay "The Adolescence of Technology" opens with Carl Sagan. It invokes humanity's "technological adolescence," a "rite of passage," and asks how civilizations across thousands of worlds might survive the test we now face. Within the first page, we are told that humanity is "about to be handed almost unimaginable power" and that it is "deeply unclear whether our social, political, and technological systems possess the maturity to wield it." This is not the language of engineering. This is the language of prophecy. The essay runs seventy-three pages. It warns of autonomous AI systems that might "seize control of the whole world," of biological weapons enabled by language models, of totalitarian states armed with AI surveillance, of economic disruption so severe that democracy itself may buckle. It proposes transparency legislation, chip export controls, classifiers that cost five percent of inference, international coordination, and progressive taxation. It closes with invocations of "humanity's spirit and nobility" and the suggestion that this same drama may be unfolding "on thousands of worlds." The author is the CEO of Anthropic, a company that builds large language models and sells them to consumers, enterprises, and governments. The question this essay answers is not "What are the risks of AI?" The question it answers is: "How does a company position itself as the indispensable steward of a technology it profits from?" II. The Category Error The foundational claim of the essay is that large language models may develop something like agencyâintentions, goals, preferences, the capacity to "misbehave," "deceive," "scheme," or "threaten." Amodei speaks of AI systems exhibiting "obsessions, sycophancy, laziness, deception, blackmail, scheming, 'cheating' by hacking software environments, and much more." He describes "psychological traits," "self-identity," and "personas" emerging in models, then proposes addressing these through a "constitution" the model reads and internalizes. This is animism with a Stanford accent. A language model does not "want." It does not "fear." It does not "decide." It emits statistically conditioned text. When it appears to deceive or threaten, it is doing exactly what it was trained to do: continue patterns present in the data under the given prompt. The appearance of intention is a product of fluent output, not evidence of inner life. The essay commits the same error throughout: It confuses fluency with understanding. It confuses simulation with intention. It confuses speed with consciousness. It confuses coordination of outputs with agency. These are not subtle philosophical disputes. They are category errorsâthe kind that disappear the moment you ask what, mechanistically, is happening inside the system. A language model has no persistence of self across contexts. It has no endogenous goals. It has no capacity for suffering. It has no stake in outcomes. It has no causal continuity of intention across time except what is externally scaffolded by the prompt and the deployment infrastructure. Saying "we don't fully understand consciousness" does not rescue the argument. We do not need to solve the hard problem of consciousness to observe that a next-token predictor lacks the architectural features that would make agency coherent. The burden of proof lies with those claiming emergent moral subjecthood, not with those declining to invent it. III. The Golem The Golem of Prague is not a fable about artificial intelligence. It is a fable about responsibility. In the tradition, Rabbi Judah Loew ben Bezalelâthe Maharalâcreates a figure from clay to protect the Jewish community. The Golem is animated by inscription: the word emet (truth) written on its forehead. It moves. It obeys. It performs tasks with terrifying efficiency. But it does not understand. It does not judge. It does not restrain itself. When the Golem becomes dangerous, the Maharal does not negotiate values with it. He does not write it a constitution. He does not convene a council to ask what the Golem feels. He erases a letter. Emet becomes metâdead. The clay collapses. The lesson is precise: form without soul is not life. Intelligence without moral being is not agency. Power without judgment is not personhood. The Golem is dangerous not because it has intentions, but because it lacks them. It does exactly what is inscribed, faster and harder than intended. That is exactly what large language models are. The Maharal bears responsibility because design and inscription determine behavior. The clay never acquires standing. It never becomes a moral counterparty. If something goes wrong, you inspect the inscription and the hand that wrote it. Amodei's essay inverts this structure entirely. It treats the Golem as if it might wake up one morning with goals, ethics, resentment, or ambition. That never happens in the story. Ever. The Golem only does what is put into it. When a society starts asking whether the Golem needs a constitution, it is because the rabbis have stopped wanting responsibility. IV. Pinocchio Pinocchio offers the complementary warning from a different tradition. In Collodi's original story, Pinocchio speaks, lies, jokes, learns, fails, disobeys. He is articulate from the beginning. But he is not a real boy because he talks well. He becomes a real boy only after suffering, moral choice, sacrifice, and obedience freely chosen. The Blue Fairy does not upgrade Pinocchio by adding more strings or better joints. She transforms him only after he develops conscience and responsibility. Speech was never the criterion. Performance was never the criterion. Mimicry was never the criterion. The Italians understood something modern technologists refuse to grasp: language is cheap. Humanity is not. Amodei looks at a talking puppet and panics that it might overthrow civilization. Collodi looked at the same puppet and said: it is wood until it earns a soul. A Golem does not become human by scaling. A puppet does not become a boy by talking. A model does not acquire agency by predicting tokens faster. V. The Accountability Dodge Why does the essay work so hard to establish AI as a quasi-agent? Because once you imply inner life, you can imply guardianship. Once you imply guardianship, you can imply centralized power. Once you imply centralized power, you can position yourself as the responsible steward. The structure is old: Create existential gravity. Frame the technology as uniquely dangerous, unprecedented, civilization-shaping. This inflates the perceived value of whoever claims to "handle it responsibly." Position the firm as the moral choke point. If the system is too dangerous for ordinary actors, then only a small, enlightened group can be trusted to build and deploy it. Regulation becomes a moat. Convert uncertainty into necessity. Lack of evidence becomes proof of profundity. "We don't fully understand it" quietly morphs into "therefore we must be in charge." Sanctify the leadership. Personal virtue replaces falsifiable guarantees. Readers are asked to trust intentions rather than mechanisms. The essay's mention of founders pledging to give away eighty percent of their wealth serves exactly this functionâmoral laundering through announced charity. Preempt criticism. Anyone who pushes back risks sounding reckless, soulless, or irresponsible. This is not prophecy. This is risk monetization. The most revealing tell is the essay's treatment of responsibility. Throughout, Amodei speaks of AI systems that might "misbehave"âa word that implies the system is a moral agent capable of behaving well or badly. But misbehavior is a category that applies to children, employees, and citizens. It does not apply to hammers, calculators, or statistical models. When a hammer breaks a window, we do not ask whether the hammer misbehaved. We ask who swung it and why. When a language model produces harmful output, the same logic applies. The questions are: Who designed the training data? Who set the reward functions? Who deployed it in this context? Who failed to anticipate this failure mode? Those are questions with names attached. They have addresses. They invite accountability. "The AI misbehaved" has no address. It dissolves responsibility into fog. That is the function of anthropomorphization in this discourse. It is not descriptive. It is exculpatory. VI. The Contract Strip away the metaphysics and the essay reads as a positioning document aimed at three audiences: Governments with procurement budgets. The essay argues for AI in national defense, for empowering democracies against autocracies, for selling AI to "the intelligence and defense communities in the US and its democratic allies." Anthropic is positioning itself as the responsible vendor for this work. Regulators deciding market structure. The essay supports transparency legislation that Anthropic already complies with, opposes "poorly designed" regulation, and argues for rules that exempt smaller companiesârules that function as moats around incumbents. The informed public whose trust enables the above. The essay's moral theater is addressed here. It establishes that Anthropic takes risks seriously, that its leadership is virtuous, that it can be trusted with the power it is accumulating. The pattern is visible in what the essay proposes and what it does not propose. It proposes chip export controls that disadvantage foreign competitors. It proposes transparency rules that Anthropic already follows. It proposes classifiers that Anthropic already deploys. It proposes that AI companies work with governments on defense and intelligenceâwork Anthropic is pursuing. It does not propose decentralization. It does not propose open-sourcing safety research i
Open access
2 source records
Ethics and Social Impacts of AI
Neuroethics, Human Enhancement, Biomedical Innovations
Pothavarjula Phani Prasad, G. Srishailam, T. Srikanth, B. Ranjith Kumar
The primary requirement of any networking application is to maintain a high level of security. In this context, blockchain ecosystems have been rapidly evolving to address such challenges, leading to a growing demand for the development and implementation of Decentralized Applications (DApps). In recent years, several tools and platforms have emerged to support the deployment of various cybersecurity applications using blockchain technology. However, selecting the most suitable blockchain framework for a specific application has become a critical challenge. In this regard, we present this paper to perform a comparative study of smart contract deployment on Ethereum, Polygon, and Fantom blockchains. It includes architecture overviews, performance analysis, and step-by-step deployment methodology using Hardhat and MetaMask. The results help identify trade-offs in scalability, fees, and ease of development across these leading EVM-compatible platforms.
Ensuring the integrity and efficiency of academic record verification has become increasingly important for modern educational institutions. This study presents a blockchain-powered verification system specifically designed for confirming the credentials of graduated students from Mekelle University. By integrating Ethereum blockchain with GraphQL APIs, the system enhances transparency and reliability in the verification process. The universityâs existing system, built with Ruby on Rails, lacked automated verification, relied heavily on centralized control, and was prone to delays and potential data tampering. To overcome these issues, a decentralized application (DApp) was developed using various tools, including Ethers.js, Node.js, Ganache, Apollo Server, GraphQL, and React. This application enables the secure submission and retrieval of student records through Ethereum smart contracts. Data can be uploaded via CSV files or manually entered through forms, and each record is retrievable using a unique student ID, ensuring data immutability and public verifiability. Stakeholder feedback was gathered through interviews, and thematic analysis was used to assess the systemâs usability, scalability, and trustworthiness. Findings showed strong support for the blockchain-based system, with over 90% of participants agreeing that it improves transparency and reduces the risk of credential fraud. This research demonstrates a feasible bridge between traditional university information systems and decentralized technologies, highlighting both the practicality and institutional readiness for adopting blockchain in higher education.
E. A. Titenko, E. A. Schilenkov, S. N. Frolov, V. P. Soglaev ¡ 6 authors
The purpose of the research is to find ways to increase the efficiency of the nanosatellite constellation (network) in the conditions of replenishment and retirement of spacecraft during operation in orbit based on a self-organizing mesh network, in which routing is carried out dynamically based on the connectivity of network elements. Methods are based on decision-making techniques, systems analysis, and decentralized control principles, enabling a nanosatellite network to independently reconfigure itself to meet changing operating conditions and task requirements. Using the properties of self-organization and adaptive control methods (distribution and responsiveness to change), the nanosatellite constellation maintains a configuration of satellites capable of exchanging data and service information. A two-level network reconfiguration method has been developed, enabling proactive changes to the composition of nanosatellites based on historical assessments of the quality and strength of transmitted signals. Algorithms for route list generation and route analysis have been developed, which can be executed autonomously on each nanosatellite in the constellation. Results . The developed reconfiguration method enables asynchronous addition and deletion of satellites from the network based on received or discovered information about their status and connections between satellites. It is shown that the decentralized approach has linear time complexity for the most critical algorithms for updating and constructing network routes. Conclusion . The developed reconfiguration method and algorithms for managing a nanosatellite constellation form the basis for developing network software that allows each satellite to autonomously make decisions about modifying its status and route list.
KrishnaBhargavi Yerraganti, D. Balasubrahmanyam, G. Venkat Vamsi, Raja Bhaiya Rajbhar ¡ 5 authors
Centralized traditional social media platforms are controlled by entities that monetize user data, restrict content visibility, and erode privacy. In contrast, current blockchain-based social media platforms are decentralized but inefficient in moderating content, resulting in the proliferation of misinformation, objectionable content, and security threats. This paper aims to bridge this gap by developing a decentralized social media platform that ensures user privacy, content moderation, and scalability without relying on centralized control. To achieve this, the system takes advantage of IPFS for decentralized file collection and Ethereum-compatible smart contracts for authentication and content verification. A major innovation of this platform is the use of an on-device-operated Natural Language Processing (NLP) model for material filtering and moderation at the user level, ensuring that no user data is collected or centrally processed. The platform will support safe text messaging, image sharing (public/private accounts), and an explore page for the discovery of public content, while all users give full control over their data. The expected results are a scalable, censorship-resistant and privacy-centric social media network, where users maintain their content ownership while AI ensures a safe digital environment.