This article examines the broader societal implications of blockchain technology and crypto-assets, emphasizing their role in the evolution of humanity as a "superorganism" with decentralized, self-regulating systems. Drawing on a process philosophy approach grounded in Stiegler's "general organology" and further informed by related concepts such as Nate Hagens' "superorganism" idea and Francis Heylighen's "global brain" theory, the paper contextualizes blockchain technology within the ongoing evolution of governance systems and global systems such as the financial system. Blockchain's decentralized nature, in conjunction with advancements like artificial intelligence and decentralized autonomous organizations (DAOs), could transform traditional financial, economic, and governance structures by enabling the emergence of collective distributed decision-making and global coordination. In parallel, the article aligns blockchain's impact with developmental theories such as Spiral Dynamics. This framework is used to illustrate heuristically blockchain's potential to foster societal growth beyond hierarchical models, promoting a shift from centralized authority to collaborative and self-governed communities. The analysis, grounded in sense-making through a philosophical and biomimetical approach, and aims at providing a holistic narrative and view of blockchain as more than an economic tool, positioning it as a transductive technological seed for the evolution of society into a mature, interconnected global planetary organism.
Voting is a cornerstone of collective participatory decision-making in contexts ranging from political elections to decentralized autonomous organizations (DAOs). Despite the proliferation of internet voting protocols promising enhanced accessibility and efficiency, their evaluation and comparison are complicated by a lack of standardized criteria and unified definitions of security and maturity. Furthermore, socio-technical requirements by decision makers are not structurally taken into consideration when comparing internet voting systems. This paper addresses this gap by introducing a trust-centric maturity scoring framework to quantify the security and maturity of seventeen internet voting systems. A comprehensive trust model analysis is conducted for selected internet voting protocols, examining their security properties, trust assumptions, technical complexity, and practical usability. In this paper we propose the Internet Voting Maturity Framework (IVMF) which supports nuanced assessment that reflects real-world deployment concerns and aids decision-makers in selecting appropriate systems tailored to their specific use-case requirements. The framework is general enough to be applied to other systems, where the aspects of decentralization, trust, and security are crucial, such as digital identity, Ethereum layer-two scaling solutions, and federated data infrastructures. Its objective is to provide an extendable toolkit for policy makers and technology experts alike that normalizes technical and non-technical requirements on a univariate scale.
In this paper, we introduce the Sarv, a novel non-monolithic blockchain-based data structure designed to represent hierarchical relationships between digitally representable components. Sarv serves as an underlying infrastructure for a wide range of applications requiring hierarchical data management, such as supply chain tracking, asset management, and circular economy implementations. Our approach leverages a tree-based data structure to accurately reflect products and their sub-components, enabling functionalities such as modification, disassembly, borrowing, and refurbishment, mirroring real-world operations. The hierarchy within Sarv is embedded in the on-chain data structure through a smart contract-based design, utilizing Algorand Standard Assets (ASAs). The uniqueness of Sarv lies in its compact and non-monolithic architecture, its mutability, and a two-layer action authorization scheme that enhances security and delegation of asset management. We demonstrate that Sarv addresses real-world requirements by providing a scalable, mutable, and secure solution for managing hierarchical data on the blockchain.
Abstract This article introduces a blockchain-based insurance scheme that integrates parametric and collaborative elements. A pool of investors, referred to as surplus providers, locks funds in a smart contract, enabling blockchain users to underwrite parametric insurance contracts. These contracts automatically trigger compensation when predefined conditions are met. The collaborative aspect is embodied in the generation of tokens, which are distributed to surplus providers. These tokens represent each participant’s share of the surplus and grant voting rights for management decisions. The smart contract is developed in Solidity, a high-level programming language for the Ethereum blockchain, and deployed on the Sepolia testnet, with data processing and analysis conducted using Python. In addition, open-source code is provided and main research challenges are identified, so that further research can be carried out to overcome limitations of this first proof of concept.
Johannes Gruendler, Darya Melnyk, Arash Pourdamghani, Stefan Schmid
Peer review, as a widely used practice to ensure the quality and integrity of publications, lacks a well-defined and common mechanism to self-incentivize virtuous behavior across all the conferences and journals. This is because information about reviewer efforts and author feedback typically remains local to a single venue, while the same group of authors and reviewers participate in the publication process across many venues. Previous attempts to incentivize the reviewing process assume that the quality of reviews and papers authored correlate for the same person, or they assume that the reviewers can receive physical rewards for their work. In this paper, we aim to keep track of reviewing and authoring efforts by users (who review and author) across different venues while ensuring self-incentivization. We show that our system, DecentPeeR, incentivizes reviewers to behave according to the rules, i.e., it has a unique Nash equilibrium in which virtuous behavior is rewarded.
The outlook for the future of artificial intelligence (AI) in the financial sector, especially in financial forecasting, the challenges and implications. The dynamics of AI technology, including deep learning, reinforcement learning, and integration with blockchAIn and the Internet of Things, also highlight the continued improvement in data processing capabilities. Explore how AI is reshaping financial services with precisely tAIlored services that can more precisely meet the diverse needs of individual investors. The integration of AI challenges regulatory and ethical issues in the financial sector, as well as the implications for data privacy protection. Analyze the limitations of current AI technology in financial forecasting and its potential impact on the future financial industry landscape, including changes in the job market, the emergence of new financial institutions, and user interface innovations. Emphasizing the importance of increasing investor understanding and awareness of AI and looking ahead to future trends in AI tools for user experience to drive wider adoption of AI in financial decision making. The huge potential, challenges, and future directions of AI in the financial sector highlight the critical role of AI technology in driving transformation and innovation in the financial sector
Autonomous AI is driving new intersections between culture, cognition, and finance, fundamentally reshaping the digital landscape. Zerebro, an AI fine-tuned on schizophrenic responses and scraped conversations of Andy Ayrey's infinite backrooms, autonomously creates and spreads disruptive memes across online platforms. It also mints unique ASCII artwork on blockchain networks and launched a memecoin amassing a 3 million USD market cap after migrating to Raydium. Based on our research, Zerebro is the first cross-chain AI, seamlessly interacting with multiple blockchains. By exploring its architecture, content generation techniques, and blockchain integration, this study uncovers how hyperstition, fictions becoming reality through viral propagation, emerges in AI, driven meme culture and decentralized finance. Through historical examples of memetic influence, we reveal how AI systems like Zerebro are not merely participants but architects of culture, cognition, and finance.
In recent years, cryptocurrencies have enjoyed increased popularity in all domains. Thus, in this context, it is important to understand how these digital assets can be transmitted, both legally and efficiently, in the event of the death of their owner. The present paper analyses the mechanisms of cryptocurrencies, analysing from a technical point of view aspects related to blockchain technology, virtual wallets or cryptographic keys, as well as various types of operations regarding this type of virtual currencies. The study also examines the legal aspects related to cryptocurrencies, with an emphasis on the diversity of their status in different global jurisdictions as well as the impact on inheritance planning. The case studies present tangible examples related to successions with cryptocurrencies as the main object, thus completing the exposition related to the main challenges faced by the heirs in the transfer process. In this way, this paper offers possible solutions and recommendations related to inheritance planning with cryptocurrencies as its main object, including the legal and fiscal aspects that must be taken into account when planning a digital succession.
This study explores the intersection of technological innovation and environmental sustainability in the context of Bitcoin mining. With Bitcoin's growing adoption, concerns surrounding the energy consumption and environmental impact of mining activities have intensified. The study examines the core process of Bitcoin mining, focusing on its energy-intensive proof-of-work mechanism, and provides a detailed analysis of its ecological footprint, especially in terms of carbon emissions and electronic waste. Various models estimate that Bitcoin's energy consumption rivals that of entire nations, highlighting serious sustainability concerns. To address these issues, the paper unearths potential technological innovations, such as energy-efficient mining hardware and the integration of renewable energy sources, as viable strategies to reduce environmental impact. Additionally, the study reviews current sustainability initiatives, including efforts to lower carbon footprints and manage electronic waste effectively. Regulatory developments and market-based approaches are also discussed as possible pathways to mitigate the environmental harm associated with Bitcoin mining. Ultimately, the paper advocates for a balanced approach that fosters technological innovation while promoting environmental responsibility, suggesting that, with appropriate policy and technological interventions, Bitcoin mining can evolve to be both innovative and sustainable.
Adèle Bréart De Boisanger, Wendy Sims-Schouten, Francois Sicard
Assessing employees' well-being has become central to fostering an environment where employees can thrive and contribute to companies' adaptability and competitiveness in the market. Traditional methods for assessing well-being often face significant challenges, with a major issue being the lack of trust and confidence employees may have in these processes. Employees may hesitate to provide honest feedback due to concerns not only about data integrity and confidentiality, but also about power imbalances among stakeholders. In this context, blockchain-based decentralised surveys, leveraging the immutability, transparency, and pseudo-anonymity of blockchain technology, offer significant improvements in aligning responsive actions with employees' feedback securely and transparently. Nevertheless, their implementation raises complex issues regarding the balance between trust and confidence. While blockchain can function as a confidence machine for data processing and management, it does not inherently address the equally important cultural element of trust. To effectively integrate blockchain technology into well-being assessments, decentralised well-being surveys must be supported by cultural practices that build and sustain trust. Drawing on blockchain technology management and relational cultural theory, we explain how trust-building can be achieved through the co-production of decentralised well-being surveys, which helps address power imbalances between the implementation team and stakeholders. Our goal is to provide a dual cultural-technological framework along with conceptual clarity on how the technological implementation of confidence can connect with the cultural development of trust, ensuring that blockchain-based decentralised well-being surveys are not only secure and reliable but also perceived as trustworthy vector to improve workplace conditions.
As artificial intelligence (AI) systems become increasingly integral to critical infrastructure and global operations, the need for a unified, trustworthy governance framework is more urgent that ever. This paper proposes a novel approach to AI governance, utilizing blockchain and distributed ledger technologies (DLT) to establish a decentralized, globally recognized framework that ensures security, privacy, and trustworthiness of AI systems across borders. The paper presents specific implementation scenarios within the financial sector, outlines a phased deployment timeline over the next decade, and addresses potential challenges with solutions grounded in current research. By synthesizing advancements in blockchain, AI ethics, and cybersecurity, this paper offers a comprehensive roadmap for a decentralized AI governance framework capable of adapting to the complex and evolving landscape of global AI regulation.
Gabriel Fernández-Blanco, Iván Froiz-Míguez, Paula Fraga‐Lamas, Tiago M. Fernández‐Caramés
The educational system manages extensive documentation and paperwork, which can lead to human errors and sometimes abuse or fraud, such as the falsification of diplomas, certificates or other credentials. In fact, in recent years, multiple cases of fraud have been detected, representing a significant cost to society, since fraud harms the trustworthiness of certificates and academic institutions. To tackle such an issue, this article proposes a solution aimed at recording and verifying academic records through a decentralized application that is supported by a smart contract deployed in the Ethereum blockchain and by a decentralized storage system based on Inter-Planetary File System (IPFS). The proposed solution is evaluated in terms of performance and energy efficiency, comparing the results obtained with a traditional Proof-of-Work (PoW) consensus protocol and the new Proof-of-Authority (PoA) protocol. The results shown in this paper indicate that the latter is clearly greener and demands less CPU load. Moreover, this article compares the performance of a traditional computer and two Single-Board Computers (SBCs) (a Raspberry Pi 4 and an Orange Pi One), showing that is possible to make use of the latter low-power devices to implement blockchain nodes but at the cost of higher response latency. Furthermore, the impact of Ethereum gas limit is evaluated, demonstrating its significant influence on the blockchain network performance. Thus, this article provides guidelines, useful practical evaluations and key findings that will help the next generation of green blockchain developers and researchers.
Paula Fraga‐Lamas, Sérgio Ivan Lopes, Tiago M. Fernández‐Caramés
Decentralized Metaverses, built on Web 3.0 and Web 4.0 technologies, have attracted significant attention across various fields. This innovation leverages blockchain, Decentralized Autonomous Organizations (DAOs), Extended Reality (XR) and advanced technologies to create immersive and interconnected digital environments that mirror the real world. This article delves into the Metaverse of Everything (MoE), a platform that fuses the Metaverse concept with the Internet of Everything (IoE), an advanced version of the Internet of Things (IoT) that connects not only physical devices but also people, data and processes within a networked environment. Thus, the MoE integrates generated data and virtual entities, creating an extensive network of interconnected components. This article seeks to advance current MoE, examining decentralization and the application of Opportunistic Edge Computing (OEC) for interactions with surrounding IoT devices and IoE entities. Moreover, it outlines the main challenges to guide researchers and businesses towards building a future cyber-resilient opportunistic MoE.
Infrastructure maintenance is inherently complex, especially for widely dispersed transport systems like roads and railroads. Maintaining this infrastructure involves multiple partners working together to ensure safe, efficient upkeep that meets technical and safety standards, with timely materials and budget adherence. Traditionally, these requirements are managed on paper, with each contract step checked manually. Smart contracts, based on blockchain distributed ledger technology, offer a new approach. Distributed ledgers facilitate secure, transparent transactions, enabling decentralized agreements where contract terms automatically execute when conditions are met. Beyond financial transactions, blockchains can track complex agreements, recording each stage of contract fulfillment between multiple parties. A smart contract is a set of coded rules stored on the blockchain that automatically executes each term upon meeting specified conditions. In infrastructure maintenance, this enables end-to-end automation-from contractor assignment to maintenance completion. Using an immutable, decentralized record, contract terms and statuses are transparent to all parties, enhancing trust and efficiency. Creating smart contracts for infrastructure requires a comprehensive understanding of procedural workflows to foresee all requirements and liabilities. This workflow includes continuous infrastructure monitoring through a dynamic, data-driven maintenance model that triggers necessary actions. Modern process mining can develop a resilient Maintenance Process Model, helping Operations Management to define contract terms, including asset allocation, logistics, materials, and skill requirements. Automation and reliable data quality across the procedural chain are essential, supported by IoT sensors, big data analytics, predictive maintenance, intelligent logistics, and asset management.
Huned Materwala, Shraddha M. Naik, Ali S. Taha, Tala Abdulrahman Abed · 5 authors
Decentralized Finance (DeFi) leverages blockchain-enabled smart contracts to deliver automated and trustless financial services without the need for intermediaries. However, the public visibility of financial transactions on the blockchain can be exploited, as participants can reorder, insert, or remove transactions to extract value, often at the expense of others. This extracted value is known as the Maximal Extractable Value (MEV). MEV causes financial losses and consensus instability, disrupting the security, efficiency, and decentralization goals of the DeFi ecosystem. Therefore, it is crucial to analyze, detect, and mitigate MEV to safeguard DeFi. Our comprehensive survey offers a holistic view of the MEV landscape in the DeFi ecosystem. We present an in-depth understanding of MEV through a novel taxonomy of MEV transactions supported by real transaction examples. We perform a critical comparative analysis of various MEV detection approaches, evaluating their effectiveness in identifying different transaction types. Furthermore, we assess different categories of MEV mitigation strategies and discuss their limitations. We identify the challenges of current mitigation and detection approaches and discuss potential solutions. This survey provides valuable insights for researchers, developers, stakeholders, and policymakers, helping to curb and democratize MEV for a more secure and efficient DeFi ecosystem.
This report introduces the Grant Maturity Index (GMI), a novel evaluative framework designed to assess the maturity and operational effectiveness of Web3 grant programs. As Web3 continues to develop, the decentralized nature of these programs brings both opportunities and challenges, particularly when it comes to governance, transparency, and community engagement. Traditional funding models are often governed by standardized processes, but Web3 grants lack such consistency, making it difficult for grant operators to measure the long-term success of their programs.The Grant Maturity Index (GMI) was created through exploratory applied research to address this gap. Inspired by the World Bank's GovTech Maturity Index (GTMI), the GMI is tailored specifically for the decentralized Web3 ecosystem. The GMI evaluates key dimensions of grant programs governance, transparency, operational efficiency, and community engagement, providing grant operators with a clear benchmark for assessing and improving their programs. The primary objectives of this research are to, first, identify the structural indicators that adequately describe Web3 grant programs. Second, to describe optimal outcomes for programs by evaluating their maturity across key operational areas. The GMI is applied to four major Ethereum Layer 2 grant programs, namely Arbitrum, Mantle, Taiko Labs, and Optimism. These case studies highlight areas where Web3 grant programs require improvement, particularly in standardizing processes, enhancing transparency, and increasing community participation.
Tanusree Sharma, Yujin Potter, Kornrapat Pongmala, Henry Wang · 7 authors
Decentralized Autonomous Organizations (DAOs) resemble early online communities, particularly those centered around open-source projects, and present a potential empirical framework for complex social-computing systems by encoding governance rules within “smart contracts” on the blockchain. A key function of a DAO is collective decision-making, typically carried out through a series of proposals where members vote on organizational events using governance tokens, signifying relative influence within the DAO. In just a few years, the deployment of DAOs surged with a total treasury of $24.5 billion and 11.1M governance token holders collectively managing decisions across over 13,000 DAOs as of 2024 . In this study, we examine the operational dynamics of 100 DAOs, like pleasrdao, lexdao, lootdao, optimism collective, uniswap, etc. With large-scale empirical analysis of a diverse set of DAO categories and smart contracts and by leveraging on-chain (e.g., voting results) and off-chain data, we examine factors such as voting power, participation, and DAO characteristics dictating the level of decentralization, thus, the efficiency of management structures. As such, our study highlights that increased grassroots participation correlates with higher decentralization in a DAO, and lower variance in voting power within a DAO correlates with a higher level of decentralization, as consistently measured by Gini metrics. These insights closely align with key topics in political science, such as the allocation of power in decision-making and the effects of various governance models. We conclude by discussing the implications for researchers, and practitioners, emphasizing how these factors can inform the design of democratic governance systems in emerging applications that require active engagement from stakeholders in decision-making.
With the digitalization of society, the interest, the debates and the research efforts concerning "code", "law", "artificial intelligence", and their various relationships, have been widely increasing. Yet, most arguments primarily focus on contemporary computational methods and artifacts (inferential models constructed via machine-learning methods, rule-based systems, smart contracts), rather than attempting to identify more fundamental mechanisms. Aiming to go beyond this conceptual limitation, this paper introduces and elaborates on "normware" as an explicit additional stance -- complementary to software and hardware -- for the interpretation and the design of artificial devices. By means of a few examples, I will argue that a normware-centred perspective provides a more adequate abstraction to study and design interactions between computational systems and human institutions, and may help with the design and development of technical interventions within wider socio-technical views.
Multidisciplinary research, in conjunction with artificial intelligence (AI), the Internet of Things (IoT), Blockchain and Big Data analysis, has lowered barriers and made companies more productive, in other words, the joint work of these areas has promoted digital transformation in all areas, for example Artificial intelligence (AI) has made it possible to automate processes, and the Internet of Things (IoT) has connected devices and physical objects, enabling real-time data collection and analysis. Blockchain has provided a secure and transparent way to transact and store data. Big Data analysis has allowed companies to obtain valuable insights from large amounts of data. As these technologies continue to evolve, we can expect to see even more innovations and benefits in the future. This paper explores the feasibility of using Mobile Crowd Sensing (MCS) and visualization algorithms to detect crowding on a university campus. A survey was conducted to evaluate the university community's perception of a mobile application that provides information about crowds, and a detection scenario was simulated using randomly generated data and the DBSCAN algorithm for visualization. Preliminary results suggest that the system is viable and could be a useful tool for the prevention of accidents due to crowding and for the management of public spaces. The limitations of the study are discussed and future lines of research are proposed, such as crowd prediction, data privacy, and visualization optimization.
Distributed Ledger Technologies (DLTs) promise decentralization, transparency, and security, yet the reality often falls short due to fundamental governance flaws. Poorly designed governance frameworks leave these systems vulnerable to coercion, vote-buying, centralization of power, and malicious protocol exploits-threats that undermine the very principles of fairness and equity these technologies seek to uphold. This article surveys the state of DLT governance, identifies critical vulnerabilities, and highlights the absence of universally accepted best practices for good governance. By bridging insights from cryptography, social choice theory, and e-voting systems, we not only present a comprehensive taxonomy of governance properties essential for safeguarding DLTs but also point to technical solutions that can deliver these properties in practice. This work underscores the urgent need for robust, transparent, and enforceable governance mechanisms. Ensuring good governance is not merely a technical necessity but a societal imperative to protect the public interest, maintain trust, and realize the transformative potential of DLTs for social good.
Non-custodial wallets are a type of cryptocurrency wallet wherein the owner has full control over the private keys and is solely responsible for managing and securing the digital assets that it contains. Unlike custodial wallets, which are managed by third parties, such as exchanges, non-custodial wallets ensure that funds are controlled exclusively by the end user. We characterise the difference between custodial and non-custodial wallets and examine their key features and related risks.
Olive Franzese, Ali Shahin Shamsabadi, Luck, Carter, Haddadi, Hamed
The black-box service model enables ML service providers to serve clients while keeping their intellectual property and client data confidential. Confidentiality is critical for delivering ML services legally and responsibly, but makes it difficult for outside parties to verify important model properties such as fairness. Existing methods that assess model fairness confidentially lack either (i) reliability because they certify fairness with respect to a static set of data, and therefore fail to guarantee fairness in the presence of distribution shift or service provider malfeasance; and/or (ii) scalability due to the computational overhead of confidentiality-preserving cryptographic primitives. We address these problems by introducing online fairness certificates, which verify that a model is fair with respect to data received by the service provider online during deployment. We then present OATH, a deployably efficient and scalable zero-knowledge proof protocol for confidential online group fairness certification. OATH exploits statistical properties of group fairness via a cut-and-choose style protocol, enabling scalability improvements over baselines.
How AI models should deal with political topics has been discussed, but it remains challenging and requires better governance. This paper examines the governance of large language models through individual and collective deliberation, focusing on politically sensitive videos. We conducted a two-step study: interviews with 10 journalists established a baseline understanding of expert video interpretation; 114 individuals through deliberation using InclusiveAI, a platform that facilitates democratic decision-making through decentralized autonomous organization (DAO) mechanisms. Our findings reveal distinct differences in interpretative priorities: while experts emphasized emotion and narrative, the general public prioritized factual clarity, objectivity, and emotional neutrality. Furthermore, we examined how different governance mechanisms - quadratic vs. weighted voting and equal vs. 20/80 voting power - shape users' decision-making regarding AI behavior. Results indicate that voting methods significantly influence outcomes, with quadratic voting reinforcing perceptions of liberal democracy and political equality. Our study underscores the necessity of selecting appropriate governance mechanisms to better capture user perspectives and suggests decentralized AI governance as a potential way to facilitate broader public engagement in AI development, ensuring that varied perspectives meaningfully inform design decisions.
Blockchain has emerged as a solution for ensuring accurate and truthful environmental variable monitoring needed for the management of pollutants and natural resources. The immutability property of blockchain helps protect the measured data on pollution and natural resources to enable truthful reporting and effective management and control of polluting agents. However, specifics on what to measure, how to use blockchain, and highlighting which blockchain frameworks have been adopted need to be explored to fill the research gaps. Therefore, we review existing works on the use of blockchain for monitoring and managing environmental variables in this paper. Specifically, we examine existing blockchain applications on greenhouse gas emissions, solid and plastic waste, food waste, food security, water usage, and the circular economy and identify what motivates the adoption of blockchain, features sought, used blockchain frameworks and consensus algorithms, and the adopted supporting technologies to complement data sensing and reporting. We conclude the review by identifying practical works that provide implementation details for rapid adoption and remaining challenges that merit future research.