Blockchain for explainable and trustworthy artificial intelligence
- Mohamed Nassar,
- Khaled Salah,
- ,
- Davor Svetinovic
- American University of Beirut,
- Khalifa University of Science and Technology,
Research Output: Contribution to journal Article Peer-review
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.
Publication Information
Output type
Research Output: Contribution to journal Article Peer-review
Original language
EnglishArticle number
e1340Journal (Volume, Issue Number)
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery (Volume 10, Issue 1)Publication milestones
- Published - 17/10/2019
Publication status
Published - 17/10/2019
External Publication IDs
- ORCID: /0000-0001-7428-2272/work/63305020
- Scopus: 85074413095
