2019
DOI: 10.1108/rmj-12-2018-0045
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“The margin between the edge of the world and infinite possibility”

Abstract: Purpose This paper aims to explore a paradoxical situation, asking whether it is possible to reconcile the immutable ledger known as blockchain with the requirements of the General Data Protection Regulations (GDPR), and more broadly privacy and data protection. Design/methodology/approach This paper combines doctrinal legal research examining the GDPR’s application and scope with case studies examining blockchain solutions from an archival theoretic perspective to answer several questions, including: What r… Show more

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Cited by 27 publications
(43 citation statements)
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“…A central facet of establishing AI accountability concerns our ability to independently audit AI (i.e., AI's auditability), especially in terms of data provenance (i.e., addressing the malicious training data tension) and the degree of uncertainty with which AI models make their predictions (i.e., addressing the model uncertainty tension). Owing to DLTs characteristics (e.g., decentralization, high tamper resistance), research has recently begun exploring the application of DLT for auditing purposes in organizational contexts (Hofman et al 2019), while first research results also indicate the feasibility of DLT for the auditing of AI (Dillenberger et al 2019). However, the development and deployment of AI are highly dynamic, with training data and algorithms (and thus model uncertainty) rapidly changing and constantly evolving.…”
Section: Dlt-based Transparency Accountability and Explainabilitymentioning
confidence: 99%
“…A central facet of establishing AI accountability concerns our ability to independently audit AI (i.e., AI's auditability), especially in terms of data provenance (i.e., addressing the malicious training data tension) and the degree of uncertainty with which AI models make their predictions (i.e., addressing the model uncertainty tension). Owing to DLTs characteristics (e.g., decentralization, high tamper resistance), research has recently begun exploring the application of DLT for auditing purposes in organizational contexts (Hofman et al 2019), while first research results also indicate the feasibility of DLT for the auditing of AI (Dillenberger et al 2019). However, the development and deployment of AI are highly dynamic, with training data and algorithms (and thus model uncertainty) rapidly changing and constantly evolving.…”
Section: Dlt-based Transparency Accountability and Explainabilitymentioning
confidence: 99%
“…Blockchain has a specific problem with identifying these roles since there is no centralized authority to control all the nodes [30], [31], [41]. Several approaches have been proposed in prior literature, such as defining the participating nodes as controllers [42], [43], data providers as controllers and miners as processors [44], actors who are able to execute a transaction and add a block as the controllers, joint controllers for federated blockchain [45], and developers as processors for smart contracts [46], [47], [48], [49].…”
Section: ) Responsibilities Of Controllers and Processors (Article 2mentioning
confidence: 99%
“…Information Governance Information Governance [48,45]  Discussed Roles and applicability of blockchain in Information Governance [48,45]…”
Section: Personal Data Management Inmentioning
confidence: 99%
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