Mark C. Ballandies, Dino Carpentras, Evangelos Pournaras
Decentralized autonomous organizations (DAOs) have transformed organizational structures by shifting from traditional hierarchical control to decentralized approaches, leveraging blockchain and cryptoeconomics. Despite managing significant funds and building global networks, DAOs face challenges like declining participation, increasing centralization, and inabilities to adapt to changing environments, which stifle innovation. This paper explores DAOs as complex systems and applies complexity science to explain their inefficiencies. In particular, we discuss DAO challenges, their complex nature, and introduce the self-organization mechanisms of collective intelligence, digital democracy, and adaptation. By applying these mechanisms to refine DAO design and construction, a conceptual framework for assessing a DAO’s viability is created. This contribution lays the foundation for future research at the intersection of complexity science, digital democracy and DAOs.
Daniele Friolo, Geoffrey Goodell, D. R. Toliver, Hazem Danny Nakib
This article builds upon the protocol for digital transfers described by Goodell, Toliver, and Nakib, which combines privacy by design for consumers with strong compliance enforcement for recipients of payments and self-validating assets that carry their own verifiable provenance information. We extend the protocol to allow for the verification that reissued assets were created in accordance with rules prohibiting the creation of new assets by anyone but the issuer, without exposing information about the circumstances in which the assets were created that could be used to identify the payer. The modified protocol combines an audit log with zero-knowledge proofs, so that a consumer spending an asset can demonstrate that there exists a valid entry on the audit log that is associated with the asset, without specifying which entry it is. This property is important as a means to allow money to be reissued within the system without the involvement of system operators within the zone of control of the original issuer. Additionally, we identify a key property of privacy-respecting electronic payments, wherein the payer is not required to retain secrets arising from one transaction until the following transaction, and argue that this property is essential to framing security requirements for storage of digital assets and the risk of blackmail or coercion as a way to exfiltrate information about payment history. We claim that the design of our protocol strongly protects the anonymity of payers with respect to their payment transactions, while preventing the creation of assets by any party other than the original issuer without destroying assets of equal value.
Blockchain technology and decentralized finance (DeFi) are reshaping global financial systems. Despite their impact, the spatial distribution of public sentiment and its economic and geopolitical determinants are often overlooked. This study analyzes over 150 million geo-tagged, DeFi-related tweets from 2012 to 2022, sourced from a larger dataset of 7.4 billion tweets. Using sentiment scores from a BERT-based multilingual classification model, we integrated these tweets with economic and geopolitical data to create a multimodal dataset. Employing techniques like sentiment analysis, spatial econometrics, clustering, and topic modeling, we uncovered significant global variations in DeFi engagement and sentiment. Our findings indicate that economic development significantly influences DeFi engagement, particularly after 2015. Geographically weighted regression analysis revealed GDP per capita as a key predictor of DeFi tweet proportions, with its impact growing following major increases in cryptocurrency values such as bitcoin. While wealthier nations are more actively engaged in DeFi discourse, the lowest-income countries often discuss DeFi in terms of financial security and sudden wealth. Conversely, middle-income countries relate DeFi to social and religious themes, whereas high-income countries view it mainly as a speculative instrument or entertainment. This research advances interdisciplinary studies in computational social science and finance and supports open science by making our dataset and code available on GitHub, and providing a non-code workflow on the KNIME platform. These contributions enable a broad range of scholars to explore DeFi adoption and sentiment, aiding policymakers, regulators, and developers in promoting financial inclusion and responsible DeFi engagement globally.
Decentralized Finance (DeFi) is increasingly studied and adopted for its potential to provide accessible and transparent financial services. Analyzing how investors use DeFi is important for reaching a better understanding of their usage and for regulation purposes. However, analyzing DeFi transactions is challenging due to often incomplete or inaccurate labeled data. This paper presents a method to extract ego network motifs from the token transfer network, capturing the transfer of tokens between users and smart contracts. Our results demonstrate that smart contract methods performing specific DeFi operations can be efficiently identified by analyzing these motifs while providing insights into account activities.
Voting is the primary mechanism through which DAOs, or Decentralised Autonomous Organisations, reach decisions. Although transparent, the voting process can be complex: it can involve many interacting smart contracts. The nexus of the decision-making process can be relocated and the true voter demographic obfuscated. Furthermore, DAOs can govern other DAOs - metagovernance. We present a method for identifying DAO-to-DAO metagovernance on the Ethereum blockchain. We focus on the links between DAOs and token contracts. We employ a signature-matching algorithm to flexibly handle a variety of DAO frameworks and voting schemes. Once we establish token-to-DAO relationships, we gather and process voting data to produce a list of metagovernance relationships. We apply this algorithm to an initial set of sixteen DAOs and we extend the dataset as more DAOs are identified. We produce a metagovernance network with 61 DAOs and 72 metagovernance relationships. We examine three case studies that show metagovernance of various forms: strategic, decisive, and centralised where a DAO becomes a nexus for metagovernance. We demonstrate that metagovernance obscures voting context and introduces entities driven by self-interest that can significantly influence governance. We highlight instances of metagovernance between DAOs operating on the Ethereum blockchain where current governance tools inadequately reveal such dynamics. To preserve the transparency-centric ethos of DAOs and mitigate risks associated with metagovernance, there is a pressing need for enhanced tools to address such issues.
The aim of the work is to present an alternative approach to recording and evaluating student performance that enables sustainable performance recording with the possibility of integrating practical components in particular. The intended result is a digital portfolio with work samples - and not just certificates, which can be understood as a portfolio examination in the context of academic assessment. This is more about the recording, evaluation and certification of learning progress and competencies than the selective evaluation of a performance review, as is the case today, for example, with the submission of final theses. The idea is to expand and later replace final papers and performance tests, particularly in higher semesters, and instead introduce electronically recorded portfolio examinations - based on the example of teaching projects. Technologically, the approach is based on blockchain and wallets/repositories and, in the broadest sense, on an implementation of smart contracts. The technological approach of smart contracts enables a high degree of traceability and transparency with little administrative effort. It also offers secure certification of services by the provider. It should be clearly stated that neither the portfolio examination nor the administration of academic achievements with smart contracts is the original idea, but rather the change in the recording of academic achievements towards an alternative approach to the recording and evaluation of student performance, which enables sustainable performance recording with the possibility of integrating practical components in particular. The desired result is a digital portfolio with work samples. The primary aim of this idea sketch is to develop an individualized performance record for students, which can also contribute to making performance more transparent and comprehensible.
Decentralized Health Intelligence Network (DHIN) extends the Decentralized Intelligence Network (DIN) framework to address challenges in healthcare data sovereignty and AI utilization. Building upon DIN's core principles, DHIN introduces healthcare-specific components to tackle data fragmentation across providers and institutions, establishing a sovereign architecture for healthcare provision. It facilitates effective AI utilization by overcoming barriers to accessing diverse health data sources. This comprehensive framework leverages: 1) self-sovereign identity architecture coupled with a personal health record (PHR), extending DIN's personal data stores concept to ensure health data sovereignty; 2) a scalable federated learning (FL) protocol implemented on a public blockchain for decentralized AI training in healthcare, tailored for medical data; and 3) a scalable, trustless rewards mechanism adapted from DIN to incentivize participation in healthcare AI development. DHIN operates on a public blockchain with an immutable record, ensuring that no entity can control access to health data or determine financial benefits. It supports effective AI training while allowing patients to maintain control over their health data, benefit financially, and contribute to a decentralized ecosystem. Unique to DHIN, patients receive rewards in digital wallets as an incentive to opt into the FL protocol, with a long-term roadmap to fund decentralized insurance solutions. This approach introduces a novel, self-financed healthcare model that adapts to individual needs, complements existing systems, and redefines universal coverage, showcasing how DIN principles can transform healthcare data management and AI utilization while empowering patients.
The sharing economy is sprawling across almost every sector and activity around the world. About a decade ago, there were only a handful of platform driven companies operating on the market. Zipcar, BlaBlaCar and Couchsurfing among them. Then Airbnb and Uber revolutionized the transportation and hospitality industries with a presence in virtually every major city. Access over ownership is the paradigm shift from the traditional business model that grants individuals the use of products or services without the necessity of buying them. Digital platforms, data and algorithm-driven companies as well as decentralized blockchain technologies have tremendous potential. But they are also changing the rules of the game. One of such technologies challenging the legal system are AI systems that will also reshape the current legal framework concerning the liability of operators, users and manufacturers. Therefore, this introductory chapter deals with explaining and describing the legal issues of some of these disruptive technologies. The chapter argues for a more forward-thinking and flexible regulatory structure.
The ongoing regulation of blockchain-based services and applications requires the identification of users who are issuing transactions on the blockchain. This systematic review explores the current status, identifies research gaps, and outlines future research directions for establishing trusted and privacy-compliant identities on the blockchain (on-chain identity). A systematic search term was applied across various scientific databases, collecting 2232 potentially relevant research papers. These papers were narrowed down in two methodologically executed steps to 98 and finally to 13 relevant sources. The relevant articles were then systematically analyzed based on a set of screening questions. The results of the selected studies have provided insightful findings on the mechanisms of on-chain identities. On-chain identities are established using zero-knowledge proofs, public key infrastructure/certificates, and web of trust approaches. The technologies and architectures used by the authors are also highlighted. Trust has emerged as a key research gap, manifesting in two ways: firstly, a gap in how to trust the digital identity representation of a physical human; secondly, a gap in how to trust identity providers that issue identity confirmations on-chain. Potential future research avenues are suggested to help fill the current gaps in establishing trust and on-chain identities.
Mudathir Muhammad Salahudeen, Muhammad Auwal Mukhtar, Saadu Salihu Abubakar, Salawu I. S
Over time, agriculture is the most consistent activity, and it evolves every day. It contributes to a vast majority of the Gross Domestic Product (GDP) of Nigeria but as ironic as it may be, there is still hunger in significant parts of the country due to low productivity in the agricultural sector and comparison to the geometric population growth. During the first half of 2022, agriculture contributed about 23% of the country's GDP while the industry and services sector had a share of the remaining 77%. This showed that with the high rate of agricultural activities, Nigeria has not achieved food security for the teeming population. and more productivity levels can be attained. Technology can/will assist Nigeria in overcoming global poverty and hunger quicker in both rural and urban areas. Today, there are many types of agricultural technologies available for farmers all over the world to increase productivity. Major technological advancements include indoor vertical farming, automation, robotics, livestock technology, modern greenhouse practices, precision agriculture, artificial intelligence, and blockchain. Mobile phones have one of the highest adoption rates of technologies developed within the last century. Digitalization will bring consumers and farmers closer together to access the shortest supply chain possible and reduce rural poverty and hunger. The paper will review the different agricultural technologies and propose a mobile solution, code Sell Harvest, to make farming more sustainable and secure food. Keywords: Sell Harvest, Agriculture, Technology, Artificial Intelligence, and Digital Farming.
Decentraland is a blockchain-based social virtual world where users can publish and sell wearables to customize avatars. In it, the third-party Decentral Games (DG) allows players of its flagship game ICE Poker to earn cryptocurrency only if they possess certain wearables. Herein, we present a comprehensive study on how DG and its game influence the dynamics of wearables and in-world visits in Decentraland. To this end, we analyzed 5.9 million wearable transfers made on the Polygon blockchain (and related sales) over a two-year period, and 677 million log events of in-world user positions in an overlapping 10-month period. We found that these activities are disproportionately related to DG, with its ICE Poker casinos (less than 0.1% of the world map) representing a remarkable average share of daily unique visitors (33%) and time spent in the virtual world (20%). Despite several alternative initiatives within Decentraland, ICE Poker appears to drive user activity on the platform. Our work thus contributes to the understanding of how play-to-earn games influence user behavior in social virtual worlds, and it is among the first to study the emerging phenomenon of virtual blockchain-based gambling.
Hongzhou Chen, Xiaolin Duan, Abdulmotaleb El Saddik, Wei Cai
Harnessing the transparent blockchain user behavior data, we construct the Political Betting Leaning Score (PBLS) to measure political leanings based on betting within Web3 prediction markets. Focusing on Polymarket and starting from the 2024 U.S. Presidential Election, we synthesize behaviors over 15,000 addresses across 4,500 events and 8,500 markets, capturing the intensity and direction of their political leanings by the PBLS. We validate the PBLS through internal consistency checks and external comparisons. We uncover relationships between our PBLS and betting behaviors through over 800 features capturing various behavioral aspects. A case study of the 2022 U.S. Senate election further demonstrates the ability of our measurement while decoding the dynamic interaction between political and profitable motives. Our findings contribute to understanding decision-making in decentralized markets, enhancing the analysis of behaviors within Web3 prediction environments. The insights of this study reveal the potential of blockchain in enabling innovative, multidisciplinary studies and could inform the development of more effective online prediction markets, improve the accuracy of forecast, and help the design and optimization of platform mechanisms. The data and code for the paper are accessible at the following link: https://github.com/anonymous.
This paper examines the potential for Cyber-Physical Systems (CPS) to be governed in a decentralised manner, whereby blockchain-based infrastructure facilitates the communication between digital and physical domains through self-governing and self-organising principles. Decentralised governance paradigms that integrate computation in physical domains (such as 'Decentralised Autonomous Organisations' (DAOs)) represent a novel approach to autono-mous governance and operations. These have been described as akin to cybernetic systems. Through the lens of a case study of an autonomous cabin called "no1s1" which demonstrates self-ownership via blockchain-based control and feedback loops, this research explores the potential for blockchain infrastructure to be utilised in the management of physical systems. By highlighting the considerations and challenges of decentralised governance in managing autonomous physical spaces, the study reveals that autonomy in the governance of autonomous CPS is not merely a technological feat but also involves a complex mesh of functional and social dynamics. These findings underscore the importance of developing continuous feedback loops and adaptive governance frameworks within decentralised CPS to address both expected and emergent challenges. This investigation contributes to the fields of infra-structure studies and Cyber-Physical Systems engineering. It also contributes to the discourse on decentralised governance and autonomous management of physical spaces by offering both practical insights and providing a framework for future research.
This paper explores the adoption of blockchain technology in the gaming industry. While supporters affirm that distributed ledger technology has potential to revolutionize gaming economies and provide players with control over their virtual assets, there are practical challenges such as energy consumption and user adoption to be addressed, and detractors question whether blockchain integration is even necessary. This report characterises popular blockchain-based gaming projects like Enjin and Axie Infinity, then compares metrics such as transaction cost and player feedback to evaluate the longevity of blockchain-integrated gaming as a whole.
Falk, Brett, Tasneem Pathan, Andrew Rigas, Gerry Tsoukalas
In this note, we examine voting on four major blockchain DAOs: Aave, Compound, Lido and Uniswap. Using data directly collected from the Ethereum blockchain, we examine voter activity. We find that in most votes, the "minimal quorum," i.e., the smallest number of active voters who could swing the vote is quite small. To understand who is actually driving these DAOs, we use data from the Ethereum Name Service (ENS), Sybil.org, and Compound, to divide voters into different categories.
Decentralized Intelligence Network (DIN) is a theoretical framework designed to address challenges in AI development, particularly focusing on data fragmentation and siloing issues. It facilitates effective AI training within sovereign data networks by overcoming barriers to accessing diverse data sources, leveraging: 1) personal data stores to ensure data sovereignty, where data remains securely within Participants' control; 2) a scalable federated learning protocol implemented on a public blockchain for decentralized AI training, where only model parameter updates are shared, keeping data within the personal data stores; and 3) a scalable, trustless cryptographic rewards mechanism on a public blockchain to incentivize participation and ensure fair reward distribution through a decentralized auditing protocol. This approach guarantees that no entity can prevent or control access to training data or influence financial benefits, as coordination and reward distribution are managed on the public blockchain with an immutable record. The framework supports effective AI training by allowing Participants to maintain control over their data, benefit financially, and contribute to a decentralized, scalable ecosystem that leverages collective AI to develop beneficial algorithms.
We investigate the potential of using Large Language Models (LLM) to support process model creation in organizational contexts. Specifically, we carry out a case study wherein we develop and test an LLM-based chatbot, PRODIGY (PROcess moDellIng Guidance for You), in a multinational company, the Hilti Group. We are particularly interested in understanding how LLM can aid (human) modellers in creating process flow diagrams. To this purpose, we first conduct a preliminary user study (n=10) with professional process modellers from Hilti, inquiring for various pain-points they encounter in their daily routines. Then, we use their responses to design and implement PRODIGY. Finally, we evaluate PRODIGY by letting our user study's participants use PRODIGY, and then ask for their opinion on the pros and cons of PRODIGY. We coalesce our results in actionable takeaways. Through our research, we showcase the first practical application of LLM for process modelling in the real world, shedding light on how industries can leverage LLM to enhance their Business Process Management activities.
Akanksha Saini, Arash Shaghaghi, Zhibo Huang, Salil S. Kanhere
The challenges of healthcare supply chain management systems during the COVID-19 pandemic highlighted the need for an innovative and robust medical supply chain. The healthcare supply chain involves various stakeholders who must share information securely and actively. Regulatory and compliance reporting is also another crucial requirement for perishable products (e.g., pharmaceuticals) within a medical supply chain management system. Here, we propose Multi-MedChain as a three-layer multi-party, multi-blockchain (MPMB) framework utilizing smart contracts as a practical solution to address challenges in existing medical supply chain management systems. Multi-MedChain is a scalable supply chain management system for the healthcare domain that addresses end-to-end traceability, transparency, and collaborative access control to restrict access to private data. We have implemented our proposed system and report on our evaluation to highlight the practicality of the solution. The proposed solution is made publicly available.
The rapid advancements in artificial intelligence, big data analytics, and cloud computing have precipitated an unprecedented demand for computational resources. However, the current landscape of computational resource allocation is characterized by significant inefficiencies, including underutilization and price volatility. This paper addresses these challenges by introducing a novel global platform for the commodification of compute hours, termed the Global Compute Exchange (GCX) (Patent Pending). The GCX leverages blockchain technology and smart contracts to create a secure, transparent, and efficient marketplace for buying and selling computational power. The GCX is built in a layered fashion, comprising Market, App, Clearing, Risk Management, Exchange (Offchain), and Blockchain (Onchain) layers, each ensuring a robust and efficient operation. This platform aims to revolutionize the computational resource market by fostering a decentralized, efficient, and transparent ecosystem that ensures equitable access to computing power, stimulates innovation, and supports diverse user needs on a global scale. By transforming compute hours into a tradable commodity, the GCX seeks to optimize resource utilization, stabilize pricing, and democratize access to computational resources. This paper explores the technological infrastructure, market potential, and societal impact of the GCX, positioning it as a pioneering solution poised to drive the next wave of innovation in commodities and compute.
With the escalating proliferation of artificial intelligence technologies, AI-generated content (AIGC) has progressively permeated across diverse domains. However, this explosive application has also sparked widespread public discussion about the copyright of AIGC. Existing copyright legal frameworks, originally designed around human creators, now face a paradigm shift. As human involvement in the generation of AIGC diminishes, where creative expression increasingly hinges on AI. This discrepancy has introduced multifaceted complexities and challenges in determining the copyright ownership of AIGC within established legal boundaries. Given this, meticulous recording and auditing of contributions from all parties in AIGC generation becomes imperative. Blockchain, with its decentralized storage, offers a robust technical foundation for AIGC copyright management. Yet existing blockchain-based solutions have clear limitations: most only focus on certifying final generated products, ignoring the management of critical intermediate data across the full lifecycle, thus failing to meet the needs of core scenarios like copyright confirmation and multi-party profit distribution. For this purpose, this paper introduces AIGC-Chain, a trustworthy AIGC copyright management system. It conducts a comprehensive recording of intermediate data generated across the full lifecycle of AIGC. Such data is deposited into a decentralized blockchain for secure multi-party auditing, thereby constructing a trustworthy management for AIGC copyright. In copyright dispute scenarios, auditors can retrieve critical proof from the blockchain, facilitating precise determination of the copyright ownership of AIGC products. Both theoretical and experimental analyses confirm that this scheme shows exceptional performance and security in AIGC copyright management.
Decentralized autonomous organizations (DAOs) are emerging innovative organizational structures, enabling collective coordination, and reshaping digital collaboration. Despite the promising and transformative characteristics of DAOs, the potential technological advancements and the understanding of the business value that organizations derive from implementing DAO characteristics are limited. This research applies a systematic review of DAOs' business applicability from an open systems perspective following a best-fit framework methodology. Within our approach, combining both framework and thematic analysis, we discuss how the open business principles apply to DAOs and present a new DAO business framework comprising of four core business elements: i) token, ii) transactions, iii) value system and iv) strategy with their corresponding sub-characteristics. This paper offers a preliminary DAO business framework that enhances the understanding of DAOs' transformative potential and guides organizations in innovating more inclusive business models (BMs), while also providing a theoretical foundation for researchers to build upon.
This research introduces the Blockchain Academic Credential Interoperability Protocol (BACIP), designed to significantly enhance the security, privacy, and interoperability of verifying academic credentials globally, addressing the widespread issue of academic fraud. BACIP integrates dual blockchain architecture, smart contracts, and zero-knowledge proofs to offer a scalable and transparent framework aimed at reducing fraud and improving the mobility and opportunities for students and professionals worldwide. The research methodology adopts a mixed-methods approach, involving a rigorous review of pertinent literature and systematic integration of advanced technological components. This includes both qualitative and quantitative analyses that underpin the development of a universally compatible system. Preliminary evaluations suggest that BACIP could enhance verification efficiency and bolster security against tampering and unauthorized access. While the theoretical framework and practical implementations have laid a solid foundation, the protocol's real-world efficacy awaits empirical validation in a production environment. Future research will focus on deploying a prototype, establishing robust validation policies, and defining precise testing parameters. This critical phase is indispensable for a thorough assessment of BACIP's operational robustness and its compliance with international educational standards. This work contributes significantly to the academic field by proposing a robust model for managing and safeguarding academic credentials, thus laying a strong foundation for further innovation in credential verification using blockchain technology.
The European DAO Workshop 2024 held on July 4th/5th in Winterthur, Switzerland aims to explore the challenges and opportunities of Decentralized Autonomous Organizations (DAOs). Its goal is to foster innovation and knowledge transfer between academics and practitioners to advance DAOs as a new organizational structure. This collection of full papers delves into areas such as decentralized decision-making, business models, artificial intelligence, economics, and legal challenges for DAOs. This diverse compilation offers a multi-disciplinary examination of the rapidly growing phenomenon of DAOs that are based on blockchain technology.
The concept of Metaverse has attracted a lot of attention in various fields and one of its important applications is health and treatment. The Metaverse has enormous potential to transform healthcare by changing patient care, medical education, and the way teaching/learning and research are done. The purpose of this research is to provide an introduction to the basic concepts and fundamental technologies of the Metaverse. This paper examines the pros and cons of the Metaverse in healthcare context and analyzes its potential from the technology and AI perspective. In particular, the role of machine learning methods is discussed; We will explain how machine learning algorithms can be applied to the Metaverse generated data to gain better insights in healthcare applications. Additionally, we examine the future visions of the Metaverse in health delivery, by examining emerging technologies such as blockchain and also addressing privacy concerns. The findings of this study contribute to a deeper understanding of the applications of Metaverse in healthcare and its potential to revolutionize the delivery of medical services.