Industry 4.0 will require unprecedented degrees of integration across organizational boundaries, which will put new demands on infrastructure for managing agreements between industrial stakeholders. In this paper, we present a system-of-systems architecture for cross-organizational negotiation of Ricardian contracts. We also describe our implementation of it, based on Eclipse Arrowhead, and how it can produce non-repudiable contracts between local clouds, potentially owned by distinct parties. We discuss how our architecture could impact current business paradigms, as well as arguing that our design, in contrast to most solutions based on smart contracts, avoids to deviate significantly from contemporary legal praxis, which should create better opportunity for industry adoption.
Internet of Things (IoT) technology such as intelligent devices, sensors, actuators and wearables have been integrated in the healthcare industry, thus contributing in the creation of smart hospitals and remote assistance environments. Ensuring the eHealth network adopts the appropriate security measures in order to effectively protect sensitive patient data against malicious attempts is a tough challenge. Devices composing eHealth infrastructure are considered to be easily exploitable. To that end, a solution monitoring the intelligent healthcare environment is of essence. In addition, by digitalising all health records, appropriate measures need to be implemented in order for patient records to be accessible by authorized personnel only. Furthermore, creating interoperable systems, capable of being integrated by multiple organizations such as hospitals and insurance companies, while maintaining a General Data Protection Regulation-friendly posture, providing access to health data is a great importance for optimal patient assistance. To address both concerns, we present a framework featuring a multi-layer tool for providing a highly effective security solution specifically designed to address the eHealth requirements, and a blockchain access control component, based on smart contracts to provide access control for authorized users to patient records and health data in a distributed way.
Digital identity is an identity which involves from records and cultural capital, personal profiles created by interactions between individuals, commented â I connect therefore I amâ with expression, celebrity tag of Descartes â I think therefore I amâ by updating with social media platforms, in YouTube videos. A digital identity is comprised in time by users of technologies such as e-mail, text messaging, social media and so on electronic communication tools. Digital identity is defined in nine dimensions as digital access, digital law, digital communication, digital commerce, digital health, digital security, digital rights and digital responsibilities, digital literacy and digital ethic. The aim of this article is to reveal importance of digital identity concept and elements of digital identities and to explore roles of blockchain and artificial intelligence in development process of digital identities. This article is written as the theoretically. Therefore, in study has been used descriptive analysis method. Consequently, blockchain contributes increasing security measures of digital identity. In case artificial intelligence contributes development of digital identity with face recognition systems and algorithms. Moreover, digital identity got more secure thanks to blockchain systems while digital identities is defined more quickly and easily by means of developed technologies with artificial intelligence
T Kim, Seo-Joon Lee, Dong Jin Chang, JaâWook Koo · 7 authors
Although blockchain is acknowledged as one of the most important technologies to lead the fourth industrial revolution, major technical challenges regarding security breach and privacy issues remain. This issue is particularly sensitive in applied medical fields where personal health information is handled within the network. In addition, contemporary blockchain-converged solutions do not consider restricted medical data regulations that are still obstacles in many countries worldwide. This implies a crucial need for a system or solution that is suitable for the healthcare sector. Therefore, this article proposes the development of a dynamic consent medical blockchain system called DynamiChain, based on a ruleset management algorithm for handling health examination data. Moreover, medical blockchain-related studies were systematically reviewed to prove the novelty of DynamiChain. The proposed system was implemented in a scenario where the exercise management healthcare company provided health management services based on data obtained from the data providerâs hospital. The proposed research is envisioned to provide a widely compatible blockchain medical system that could be applied in future healthcare fields.
Flora Amato, Giovanni Cozzolino, Francesco Moscato, Vincenzo Moscato · 5 authors
The interest of Industry 4.0 in smart contracts and blockchain technologies is growing up day by day. Smart contracts have enabled new kinds of interactions whereby contractors can even fully automate processes they agree on. This technology is really appealing in Internet of Things (IoT) domain because smart devices generate events for software agents involved in a smart contract execution, making full automation possible. However, smart contracts have to comply with national and international laws and accountability of participant's actions. Soundness of a smart contract has to be verified in terms of law compliance. Here, we propose a model for verification and validation of law compliance of smart contracts in IoT environments. The main goal of this article is to propose a formal model (based on multiagent logic and ontological description of contracts) for validating law compliance of smart contracts and to determine potential responsibilities of failures.
Abstract Cryptocurrencies are proliferating as instantiations of blockchain, which is a transparent, distributed ledger technology for validating transactions. Blockchain is thus said to embed trust in its technical design. Yet, blockchainâs technical promise of trust is not fulfilled when applied to the cryptocurrency ecosystem due to many social challenges stakeholders experience. By investigating a cryptocurrency chatbot (Brokerbot) that distributed information on cryptocurrency news and investments, we explored social tensions of trust between stakeholders, namely the botâs developers, users, and the bot itself. We found that trust in Brokerbot and in the cryptocurrency ecosystem are two conjoined, but separate challenges that users and developers approached in different ways. We discuss the challenging, dual-role of a Brokerbot as an object of trust as a chatbot while simultaneously being a mediator of trust in cryptocurrency, which exposes the social-technical gap of trust. Lastly, we elaborate on trust as a negotiated social process that people shape and are shaped by through emerging ecologies of interlinked technologies like blockchain and conversational interfaces.
Lethal autonomous weapons systems (LAWS) are emerging and futuristic technologies gathering increasing global attention, especially in relation to their dual-use components. Although the international community has not come to an agreement on the definition of LAWS, states have nonetheless articulated their concern through dialogue and fora about these machines, which could use artificial intelligence (AI) to complete an objective requiring movement across uncertain environments and the use of kinetic force on uncertain targets in the parameters of a designated mission. A distinction between LAWS and other robots is the formerâs ability to decide whether to employ lethal force independent of human oversight. In considering possible measures for responding to the threats LAWS may pose (through their anonymity especially) to international peace and security, this article recommends policy-makers contemplate adopting early, pragmatic approaches for the regulation of LAWS from an arms control perspective. In attempting to consider an approach for governance mechanisms to bolster non-proliferation, the article draws on the notion of âcontact tracing,â which will have become familiar to readers as a process to record the transmission of COVID-19 within and between communities, frequently assisted through the adoption of digital contact-tracing technologies. The first section of the article explores current debates and considers existing mechanisms within the United Nations to deliver such measures from an arms control context. The second section of the article proposes âtracingâ through distributed ledger technologies (DLTs) to deter against the proliferation of LAWS and to provide governance options for the introduction of a decentralized records management system on LAWS.
This research work, a study was carried out on blockchain technology and its types, as well as the creation of new models of government and governance from the scope of an organization, infrastructure and platform. Governance and commercial models were addressed, based on standardization of data and legal frameworks. On the other hand, it showed how operational governance causes consequences in business models, whether with transactions, multi-signature, forks, consensus mechanism, smart contracts, tokenization, online dispute resolution and decentralized application (World Economic Forum, 2020, pp. 97 196). It was discovered that at least in current business models, private blockchain networks are more useful than public networks because they have greater operational flexibility and data governance, without exempting that public networks must also have mechanisms of governance since sometimes a human consensus must be reached to make updates to protocols and technical rules (The Law Society, 2020, pp. 24-61). This paper shows the basic principles that must be observed about governance and regulation in the implementation of blockchain technologies in systems created by governments, corporations and/or organized civil societies.
Blockchain-based âDecentralized Autonomous Organizationsâ (DAOs) communities risk perpetuating the 1990s Californian Ideology of techno-elitism in their imaginary of âautonomyâ via technological determinism, free-market economics, and âengineeringâ approach to social and political challenges (Barbrook & Cameron, 1996). Imaginations include algorithmic governance via Artificial General Intelligence agents running on decentralized blockchains, hiring labor in DAOs, and bartering payment in cryptocurrency. The role of humans in this imaginary is limited. This piece explores autonomy in blockchain-based DAOs to investigate visions of algorithmic assemblages. Do DAOs imagine a different future where the role of humans is one of symbiosis and augmentation with machines? I draw on cybernetic interpretations of DAOs as âautopoieticâ organisms to imagine a co-constitutive relationship between people and algorithms in the information age. By understanding the promises and practices of blockchain technology and decentralized governance, we can better engage with these emergent objects of social and policy inquiry.
Open access
2 source records
Blockchain Technology Applications and Security
Ethics and Social Impacts of AI
Neuroethics, Human Enhancement, Biomedical Innovations
Smart contracts are simply self-activated contracts between two parties. The idea behind their implementation relies on the concept of blockchain, wherein the details and execution of the contract are turned into code and distributed among users of a network. This process controls counterfeiting and money laundering by its ability to trace who owes whom. It also boosts the general economy. This research paper shows how smart contracts in modern-day systems have changed the approach to money tracing. We present case studies about the uses of smart contracts with high levels of security and privacy. As a building block of smart contracts, a brief description of blockchain is provided in an introduction. Among other cryptography methods and techniques, the usage of hashing and hash functions in blockchain security are also explained. We also explore the real-time applications of blockchain and smart contract techniques in real estate. The main advantage of this research paper is that it discusses a state-of-the-art subject, as most of the articles referenced in this paper are from 2018 and onward.
In this exploratory research, I develop new knowledge on trust in inter-firm cooperation that leverages recent technologies such as blockchain and the Internet of things in a digital platform ecosystem. In a digital network, advanced algorithms govern and shape inter-firm business processes. While such algorithms introduce efficiency in inter-firm business processes, their limitations, especially their apparent lack of transparency, may affect the key trust dimensions (i.e., reliability, fairness, and goodwill) in the relationships among the participating firms. I introduce algorithmic relationship, a label that embeds the concepts of smart contracts in inter-firm cooperation. Algorithmic relationships involve autonomous and semi-autonomous implementations of smart contracts in all lifecycle stages of inter-firm cooperation. By analyzing extant literature on trust, inter-firm cooperation, business model innovation, and digital platforms, I demonstrate how various factors influence whether firms adopt smart contracts: perceptions about other participantsâ trustworthiness, participantsâ own propensity to trust, participantsâ shared goals and resource embeddedness in the network, perceived risks in inter-firm interactions, and complexity and time criticality of inter-firm interactions. Taking a temporal perspective, I also recognize the present lacunae with smart contracts from various perspectives (algorithm development, algorithm implementation, algorithm governance, and the availability of appropriate legal resources in the event that disputes occur) and demonstrate how these drawbacks impede shared value creation.
Abstract Artificial intelligence (AI) brings forth many opportunities to contribute to the wellbeing of individuals and the advancement of economies and societies, but also a variety of novel ethical, legal, social, and technological challenges. Trustworthy AI (TAI) bases on the idea that trust builds the foundation of societies, economies, and sustainable development, and that individuals, organizations, and societies will therefore only ever be able to realize the full potential of AI, if trust can be established in its development, deployment, and use. With this article we aim to introduce the concept of TAI and its five foundational principles (1) beneficence, (2) non-maleficence, (3) autonomy, (4) justice, and (5) explicability. We further draw on these five principles to develop a data-driven research framework for TAI and demonstrate its utility by delineating fruitful avenues for future research, particularly with regard to the distributed ledger technology-based realization of TAI.
Kevin Wallis, Jan Stodt, Eugen Jastremskoj, Christoph Reich
The digital transformation of companies is expected to increase the digital interconnection between different companies to develop optimized, customized, hybrid business models. These cross-company business models require secure, reliable, and traceable logging and monitoring of contractually agreed information sharing between machine tools, operators, and service providers. This paper discusses how the major requirements for building hybrid business models can be tackled by the blockchain for building a chain of trust and smart contracts for digitized contracts. A machine maintenance use case is used to discuss the readiness of smart contracts for the automation of workflows defined in contracts. Furthermore, it is shown that the number of failures is significantly improved by using these contracts and a blockchain.
Abstract Today we are witnesses an explosion of online business, developed on the internet â a special environment that requires own resources and tools and it is governed by specific rules. In this context, a new type of technology has been developed â the distributed ledger system, which allowed the creation of a new form of the agreement - the smart contracts. Smart contract is the next step forward in the process of digitalized contracts, after using the PDF documents with electronic signatures, and it favors the businesses to be carried out completely automatically, without the need for human intervention, and to gain greater efficiency and reduction in costs. This paper will try to provide the answers to several questions, such as: what is a smart contract?; how smart contract will be used?; how smart contract will be enforced?; etc. Moreover, it will be emphasized the advantages of smart contract and the new developments such as âRicardianâ contracts representing more efficient and transparent agreements that can be drafted and enforced on platform. Most important issue of this paper consists in analysis of legal framework of smart contracts using the basic principles of contract law combined with blockchain regulations, taking into account changing the paradigm from âcode is lawâ to âlaw is codeâ.
Abstract This chapter focuses on how machine learning (ML) and distributed ledger technologies (DLTs) change the environment of the law, the substance of legal goods, and on the extent to which these changes affect legal protection. ML applications, for example, can decide a person's credit worthiness or employability. Moreover, DLTs can, for instance, self-execute transactions and policies without and beyond the law. One of the main challenges here thus concerns the regulatory effects of these novel technologies and the potential incompatibility of legal protection with techno-regulation (defined as the regulatory effects of a technology, whether or not intended). This challenge will be discussed in terms of automated compliance (âlegal by designâ) and technological articulation of fundamental rights (âlegal protection by designâ).
The stages of digital technology readiness are viewed through the lens of three contemporary and widely discussed examples, namely distributed ledger technology, machine learning, and the internet of things. I use these examples to clarify when there is really just an old technology being re-branded, when there is something genuinely new and useful, and whether there may be over-claiming.
While the digital layer of social interaction continues to evolve, the recently proclaimed hopes in the development of digital identity could be both naĂŻf 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 citizenshipâs 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 âcloud communitiesâ with truly âself-sovereignâ 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 âbrave new worldâ. 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.