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Blockchain for explainable and trustworthy artificial intelligence

  • American University of Beirut
  • Khalifa University of Science and Technology

Research output: Contribution to journalArticlepeer-review

149 Citations (Scopus)

Abstract

The increasing computational power and proliferation of big data are now empowering Artificial Intelligence (AI) to achieve massive adoption and applicability in many fields. The lack of explanation when it comes to the decisions made by today's AI algorithms is a major drawback in critical decision-making systems. For example, deep learning does not offer control or reasoning over its internal processes or outputs. More importantly, current black-box AI implementations are subject to bias and adversarial attacks that may poison the learning or the inference processes. Explainable AI (XAI) is a new trend of AI algorithms that provide explanations of their AI decisions. In this paper, we propose a framework for achieving a more trustworthy and XAI by leveraging features of blockchain, smart contracts, trusted oracles, and decentralized storage. We specify a framework for complex AI systems in which the decision outcomes are reached based on decentralized consensuses of multiple AI and XAI predictors. The paper discusses how our proposed framework can be utilized in key application areas with practical use cases.

Original languageEnglish
Article numbere1340
JournalWIREs Data Mining and Knowledge Discovery
Volume10
Issue number1
DOIs
Publication statusPublished - 17 Oct 2019

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