While the digital layer of social interaction continues to evolve, the recently proclaimed hopes in the development of digital identity could be both naïf and dangerous. Rather than just asking ourselves how we could digitize existing features of identity management, and corresponding financial transactions on a community or state level, we submit that truly useful and innovative digital identities need to be accompanied by some significant rethinking of the essential basics behind the organization of the world. Once digital technologies leave the realm of purely on-line or deeply local projects, the confrontation with the world of citizenship’s biases and the random distribution of rights and duties precisely on the presumption of the lack of any choice and absolute pre-emption of any disagreement comes into a direct conflict with all the benefits Distributed Ledger Technology purports to enable. Some proponents of Distributed Ledger Technology-based identity systems envisage ‘cloud communities’ with truly ‘self-sovereign’ individuals picking and choosing which communities they belong to. We rather see a clear risk that when implemented at the global scale, digital identity systems could be deeply harmful, reinforcing and amplifying the most repugnant aspects of contemporary citizenship. In this contribution we present a categorization of existing digital identity systems from a governance perspective, and discuss it on basis of three corresponding case studies which allow us to infer opportunities and limitations of Distributed Ledger Technology based identity. Subsequently, we put our findings in the context of existing preconditions of citizenship law, and conclude with a suggestion of a combination of several tests which we propose to avoid the plunge into a neo-feudal ‘brave new world’. We would like to draw attention to the perspective that applying digital identity without rethinking the totalitarian assumptions behind the citizenship status will result in perfecting the current inequitable system, which is a move away from striving towards justice and a more dignified future of humanity. We see the danger that those might be provided with plenty of opportunities who already do not lack such under current governance structures, while less privileged individuals will witness their already weak position becoming increasingly worse.
Christian Sillaber, Bernhard Waltl, Horst Treiblmaier, Ulrich Gallersdörfer · 5 authors
Abstract Smart contracts are seen as the major building blocks for future autonomous blockchain- and Distributed Ledger Technology (DLT)-based applications. Engineering such contracts for trustless, append-only, and decentralized digital ledgers allows mutually distrustful parties to transform legal requirements into immutable and formalized rules. Previous experience shows this to be a challenging task due to demanding socio-technical ecosystems and the specificities of decentralized ledger technology. In this paper, we therefore develop an integrated process model for engineering DLT-based smart contracts that accounts for the specificities of DLT. This model was iteratively refined with the support of industry experts. The model explicitly accounts for the immutability of the trustless, append-only, and decentralized DLT ecosystem, and thereby overcomes certain limitations of traditional software engineering process models. More specifically, it consists of five successive and closely intertwined phases: conceptualization, implementation, approval, execution, and finalization. For each phase, the respective activities, roles, and artifacts are identified and discussed in detail. Applying such a model when engineering smart contracts will help software engineers and developers to better understand and streamline the engineering process of DLTs in general and blockchain in particular. Furthermore, this model serves as a generic framework which will support application development in all fields in which DLT can be applied.
The evolution of Artificial Intelligence (AI) from centralized models toward decentralized architectures has fundamentally reshaped the paradigms of data management, ownership, and governance. In traditional AI ecosystems, data is consolidated within centralized repositories for model training and analytics, resulting in challenges related to privacy, latency, and compliance with regulatory frameworks. Decentralized AI architectures encompassing federated learning, edge AI, swarm intelligence, and blockchain-based frameworks offer a transformative alternative that aligns technological innovation with distributed data governance principles. These architectures enable AI systems to learn collaboratively across multiple nodes or organizations without transferring raw data, ensuring data sovereignty and compliance with global data protection mandates such as GDPR and CCPA. This review examines how decentralized AI architectures influence distributed data governance by promoting transparency, trust, and accountability in multi-party data ecosystems. The integration of AI with blockchain and distributed ledger technologies provides immutable audit trails and decentralized identity management, enabling verifiable governance across federated networks. Moreover, privacy-preserving techniques such as differential privacy, homomorphic encryption, and secure multiparty computation empower organizations to perform analytics on encrypted datasets while maintaining compliance with ethical and legal data-handling standards. Through a synthesis of academic research and real-world applications, the review highlights the significant advantages of decentralized AI, including enhanced privacy assurance, reduced systemic risks, and improved collaboration among data stakeholders. However, the transition toward decentralized intelligence introduces new challenges related to interoperability, communication overhead, and model convergence in distributed environments. Ensuring fairness, accountability, and explainability within federated systems remains a critical governance issue, as decentralized decision-making increases complexity in auditing and oversight. Furthermore, the governance of AI models themselves rather than just data poses emerging regulatory and ethical questions in globally interconnected ecosystems.
Machine learning has recently enabled large advances in artificial intelligence, but these results can be highly centralized. The large datasets required are generally proprietary; predictions are often sold on a per-query basis; and published models can quickly become out of date without effort to acquire more data and maintain them. Published proposals to provide models and data for free for certain tasks include Microsoft Research's Decentralized and Collaborative AI on Blockchain. The framework allows participants to collaboratively build a dataset and use smart contracts to share a continuously updated model on a public blockchain. The initial proposal gave an overview of the framework omitting many details of the models used and the incentive mechanisms in real world scenarios. In this work, we evaluate the use of several models and configurations in order to propose best practices when using the Self-Assessment incentive mechanism so that models can remain accurate and well-intended participants that submit correct data have the chance to profit. We have analyzed simulations for each of three models: Perceptron, Naïve Bayes, and a Nearest Centroid Classifier, with three different datasets: predicting a sport with user activity from Endomondo, sentiment analysis on movie reviews from IMDB, and determining if a news article is fake. We compare several factors for each dataset when models are hosted in smart contracts on a public blockchain: their accuracy over time, balances of a good and bad user, and transaction costs (or gas) for deploying, updating, collecting refunds, and collecting rewards. A free and open source implementation for the Ethereum blockchain and simulations written in Python is provided at https://github.com/microsoft/0xDeCA10B. This version has updated gas costs using newer optimizations written after the original publication.
Applications of Blockchain (BC) technology and Cyber-Physical Systems (CPS) are increasing exponentially. However, framing resilient and correct smart contracts (SCs) for these smart application is a quite challenging task because of the complexity associated with them. SC is modernizing the traditional industrial, technical, and business processes. It is self-executable, self-verifiable, and embedded into the BC that eliminates the need for trusted third-party systems, which ultimately saves administration as well as service costs. It also improves system efficiency and reduces the associated security risks. However, SCs are well encouraging the new technological reforms in Industry 4.0, but still, various security and privacy challenges need to be addressed. In this paper, a survey on SC security vulnerabilities in the software code that can be easily hacked by a malicious user or may compromise the entire BC network is presented. As per the literature, the challenges related to SC security and privacy are not explored much by the authors around the world. From the existing proposals, it has been observed that designing a complex SCs cannot mitigate its privacy and security issues. So, this paper investigates various Artificial Intelligence (AI) techniques and tools for SC privacy protection. Then, open issues and challenges for AI-based SC are analyzed. Finally, a case study of retail marketing is presented, which uses AI and SC to preserve its security and privacy.
Abstract This paper provides, from a business ethics perspective, a basic clustering of the morally (a) favorable, (b) unfavorable, and (c) ambivalent dimensions of blockchain technology and its various emergent applications. Instead of proffering specific assessments on particular aspects of blockchain‐based business models, we aim to offer an initial overview that charters the territory so that future research can bring about such moral assessments in an informed and orderly fashion. The main contribution of this paper lies in identifying several morally ambivalent dimensions of blockchain technology, which we finally link to two strands of business ethics research: ethical and legal aspects of legislation as well as a link to Habermasian corporate social responsibility theory arguing for transparent data production and consumption on the blockchain. We conclude that future research is necessary for moral assessment of the ambivalent cases, since their ethical evaluation changes depending on whether one analyzes them through the lenses of utilitarianism, contractarianism, deontology, and virtue ethics, respectively.
Agreements, consensuses, protocols, resource-sharing, and fairness are all examples of social and political metaphors that define and shape new computational algorithms. The thought experiments and allegories about resource-sharing or agreement between nodes played a vital role in the development of "concurrent programming" (enabling processor power-sharing and process synchronization) and still later in the development of distributed computing (facilitating data access and synchronization). These paved the way for current concepts of consensus mechanisms, smart contracts, and other descriptions of cryptocurrencies, blockchain, distributed ledger, and hashgraph technologies, paradoxically reversing the relations between metaphor and artifact. New computing concepts and algorithmic processes, such as consensus mechanisms, trustless networks, and automated smart contracts or DAOs (Distributed Autonomous Organizations), aim to disrupt social contracts and political decision-making and replace economic, social, and political institutions (e.g., law, money, voting). Rather than something that needs a metaphor, algorithms are becoming the metaphor of good governance. Current fantasies of algorithmic governance exemplify this reversal of the role played by metaphors: they reduce all concepts of governance to automation and curtail opportunities for defining new computing challenges inspired by the original allegories, thought experiments, and metaphors. Especially now, when we are still learning how best to govern the transgressions and excesses of emerging distributed ledger technologies, productive relations between software and allegory, algorithms and metaphors, code and law are possible so long as they remain transitive. Against this tyranny of algorithms and technologies as metaphors and aspirational models of governance, we propose sandboxes and environments that allow stakeholders to combine prototyping with deliberation, algorithms with metaphors, codes with regulations.
Bitcoin is an innovative technological network, a new, non-governmental currency, and a worldwide group of users. In other words, Bitcoin is a complex sociotechnical system with a complex set of risks and challenges for anyone using it. We investigated how everyday users of Bitcoin develop trust in Bitcoin on one of the largest online communities devoted to Bitcoin: the Reddit.com r/bitcoin forum. Using qualitative content analysis, we examined how trust in Bitcoin develops based on contributions to this community. On r/bitcoin, trust in Bitcoin is driven by a pervasive ideology we call the "True Bitcoiner" ideology. This ideological viewpoint in centered on the interpretation of Bitcoin as functionally "trustless" and risk-free. Despite widespread evidence of emerging individual and system-level risks with using Bitcoin, participants continue to maintain this ideological perspective. This ideology consists of three primary beliefs: viewing Bitcoin's technology as more trustworthy than its people; rejecting 'corrupt' social hierarchies related to money; and the importance of accumulating or 'HODLing' quantities of Bitcoin as a strategy to create an ideal future. We conclude that this "True Bitcoiner" ideology is maintained despite contradictory evidence in the world because it allows participants to more easily interpret Bitcoin and make decisions by reducing perceived risk and uncertainty in the system. The role of this ideology on r/bitcoin demonstrates an expanded conceptualization of how trust is created and socially-mediated in socio-technical contexts.
Sociotechnical imaginaries are futures that people envision might be possible and desirable. They have a real impact on how systems are designed and what values they have embedded in their design. This article examines imaginaries about autonomous systems, decentralized systems, and decentralized autonomous systems. Through a discussion of the literature on autonomous and decentralized systems and how these imaginaries play out in the blockchain community based on my qualitative research, I demonstrate how decentralized autonomous systems are related to imaginaries about the organization of and the future of work. I identify three framings of imaginaries about autonomous systems: (1) autonomous technology as physical objects, (2) as mathematical rules, and (3) as artificial mangers. I also identify two sometimes conflicting framings of imaginaries about distributed and decentralized technology: these technologies as a new form of production and as freedom from control. These imaginaries intersect in decentralized autonomous systems, and I examine what they can tell us about the design and governance of such technologies. Lastly, I suggest ways of using the concept of imaginaries in participatory design.
Background. Expert observers and artificial intelligence (AI) progression metrics indicate AI will exceed human intelligence within a few decades. Whether general AI that exceeds human capabilities (AGI) will be the single greatest boon in history or a disaster is unknown. No proofs exist that AGI will benefit humans or that AGI will not harm or eliminate humans. Objective. I propose a set of logically distinct conceptual components that are necessary and sufficient to 1) ensure that most known AGI scenarios will not harm humanity and 2) robustly align AGI values and goals with human values. Methods. By systematically addressing each pathway category to malevolent AI we can induce the methods/axioms required to redress the category. Results and Discussion. Distributed ledger technology (DLT, blockchain) is integral to this proposal, e.g. to reduce the probability of hacking, provide an audit trail to detect and correct errors or identify components causing vulnerability or failure and replace them or shut them down remotely and/or automatically, and to separate and balance key AGI components via decentralized apps (dApps). Smart contracts based on DLT are necessary to address evolution of AI that will be too fast for human monitoring and intervention. The proposed axioms. 1) Access to technology by market license. 2) Transparent ethics embodied in DLT. 3) Morality encrypted via DLT. 4) Behavior control structure with values (ethics) at roots. 5) Individual bar-code identification of all critical components. 6) Configuration Item (from business continuity/disaster recovery planning). 7) Identity verification secured via DLT. 8) Smart automated contracts based on DLT. 9) Decentralized applications - AI software code modules encrypted via DLT. 10) Audit trail of component usage stored via DLT. 11) Social ostracism (denial of societal resources) augmented by DLT petitions.
Long Finance's Distributed Futures research programme has produced a report entitled “To Be, To Have, To Know: Smart Ledgers & Identity Authentication”, the latest in a series of exciting projects in the programme. The event offered the opportunity to join the discussion on the findings of the report, which showed how identity management and authentication systems can make use of leading technology, such as smart ledgers, as well as to explore the social, economic, and political implications of their use.
The research provides alternative models for practical identity management and authentication, and suggests considerations for policy makers, regulators, businesses, and individuals, both for the present and looking forward.
This chapter addresses the myth of decentralized governance of public blockchains, arguing that certain people who create, operate, or reshape them function much like fiduciaries of those who rely on these powerful data structures. Explicating the crucial functions that leading software developers perform, the chapter compares the role to Tamar Frankel’s conception of a fiduciary, and finds much in common, as users of these technologies place extreme trust in the leading developers to be both competent and loyal (ie, to be free of conflicts of interest). The chapter then frames the cost-benefit analysis necessary to evaluate whether, on balance, it is a good idea to treat these parties as fiduciaries, and outlines key questions needed to flesh out the fiduciary categorization. For example, which software developers are influential enough to resemble fiduciaries? Are all users of a blockchain ‘entrustors’ of the fiduciaries who operate the blockchain, or only a subset of those who rely on the blockchain? Finally, the chapter concludes with reflections on the broader implications of treating software developers as fiduciaries, given the existing accountability paradigm that largely shields software developers from liability for the code they create.
This paper interprets the principles of good governance and corporate governance in the context of distributed ledger technologies, namely blockchain, analyzing specifically how these principles apply to a blockchain-enabled energy market. With blockchain, governance becomes decentralized and automated, creating a new, tech- nical bureaucracy. However, a programmed decision tree does not inevitably produce a digitized democracy and a functional marketplace. While blockchain governance decisions have been predominantly technical, they increasingly embroil legal, moral, cultural and even philosophical considerations. As a result, governance is increasingly recognized as a critical challenge in the future development of blockchain-enabled marketplaces. Future, multidisciplinary research by lawyers, engineers, political scientists and philosophers should venture further into develop- ing good governance principles for blockchain, focusing on equity and inclusion.
In recent years, there is growing interest in the ways the European aviation industry can leverage the multi-source data fusion towards augmented domain intelligence. However, privacy, legal and organisational policies together with technical limitations, hinder data sharing and, thus, its benefits. The current paper presents the ICARUS data policy and assets brokerage framework, which aims to (a) formalise the data attributes and qualities that affect how aviation data assets can be shared and handled subsequently to their acquisition, including licenses, IPR, characterisation of sensitivity and privacy risks, and (b) enable the creation of machine-processable data contracts for the aviation industry. This involves expressing contractual terms pertaining to data trading agreements into a machine-processable language and supporting the diverse interactions among stakeholders in aviation data sharing scenarios through a trusted and robust system based on the Ethereum platform.
Given Bitcoin’s apparent lack of non-monetary uses, Luther (2018) argues that its emergence as a medium of exchange invalidates the regression theorem, or at least severely limits its relevance to identifying which commodities could emerge as media of exchange in the absence of State intervention. However, this view misinterprets both the regression theorem itself and the problem it was developed to address. The goal of the regression theorem was not to identify which commodities could become monies, but to provide a subjectivist explanation of the purchasing power of money. To do this, it requires only that some individuals valued the good in question before its use as a medium of exchange, not that it had some objective pre-monetary use.
Blockchain technologies are gradually being found an application in many areas, especially in FinTech. As a result, a lot of blockchain platforms have emerged with the support of smart contracts that are intended to automate party interactions. However, it has been shown that they are prone to attacks and errors which lead to money loss. To date, there has been a wide range of approaches for making smart contracts safer that included analysis tools, reasoning models, and safer and more rigorous programming languages. In this paper, we provide an overview of smart contract programming languages design principles, related vulnerabilities, and future research areas. The provided overview is meant to outline the to date state of languages and to become a possible basis for future proceedings, and show approaches, used by the community, to reach safe and usable language for smart contracts. We have split all found vulnerabilities by source of their arising. Various languages’ characteristics such as abstraction level, paradigm, Turing completeness and main features are summarized in the table. Additional information about languages is provided, e.g. model of execution and tools for static analysis.
Security, privacy, transparency, consent, and data sharing are major challenges that healthcare institutions must address today. The explosion of the Internet of Things (IoT), the enactment of the General Data Protection Regulation (GDPR), the growing trend of patients self-managing their diseases, and the eagerness of patients to share their self-collected health data with primary and secondary health organisations further increase the complexity of these challenges. Smart contracts, based on blockchain technology, can be a legitimate approach for addressing these challenges. Smart contracts define rules and penalties in an agreement, enforce those rules, and render them irrevocable. This paper presents a state-of-the-art review (as of May 2018) of the possible usages of smart contracts in healthcare and focuses on data sharing between patients, doctors, and institutions.
Given the ubiquity of artificial intelligence (AI) in modern societies, it is clear that individuals, corporations, and countries will be grappling with the legal and ethical issues of its use. As global problems require global solutions, we propose the establishment of an international AI regulatory agency that --- drawing on interdisciplinary expertise --- could create a unified framework for the regulation of AI technologies and inform the development of AI policies around the world. We urge that such an organization be developed with all deliberate haste, as issues such as cryptocurrencies, personalized political ad hacking, autonomous vehicles and autonomous weaponized agents are already a reality, affecting international trade, politics, and war.
In this era of increasing cyber dependency in business dealings there is huge potential in the adoption of Distributed Ledger Technologies (DLT) particularly in the context of smart contract in the commercial world. The phenomenon of smart contract operates independently without the cumbersome need to engage any intermediary and is capable of executing specific task.(Thake, 2018) People relates it more to a piece of code (known as a software agent) that is designed to execute certain tasks if pre-defined conditions are met. Such tasks are often embedded within, and performed on a distributed ledger.â€(Stark, 2016) However, if one accepts the contention that smart contract is not merely as a set of computer code but a smart legal contract which contains obligations and legal terms that are enforceable, hence, in programming or writing smart contract, one must ensure that the software developers who design smart contract take note of the legal rules and principles behind the specific type of contract in question. It has been argued that there is too much dependency on the programming aspect in the creation of smart contracts by programmers and computer scientists. (Khalil et al., 2017)
Smart contracts play an advent role in automated business participation by rendering collaboration processes more time-efficient, cost-effective and establishing more transparency. Smart contracts facilitate trust-less systems, without the need for intervention from third-party intermediaries. Existing smart-contract languages mainly focus on technical utility and do not take into consideration social and legally relevant issues, e.g., lack of semantics, ontological completeness, and so on. In this research, we address the gap by developing with rigorous means a smart contract's language that aims to be legally relevant, and that comprises socio-technical utility for cross-organizational business collaboration. The proposed language seeks to retain the strengths of the already existing languages of different generations while eluding their limitations. We aim to identify and implement abstract grammar patterns for a smart-contract language that has the expected application utility and verifiability. We evaluate the developed language based on automating industry-collaboration cases with our novel smart-contract language to test the suitability, utility, and expressiveness.