Exploiting Blockchain to Make AI Trustworthy: A Software Development Lifecycle View

Author:

Zhang Peiyun1,Ding Song2ORCID,Zhao Qinglin3ORCID

Affiliation:

1. The Engineering Research Center of Digital Forensics of Ministry of Education, and the School of Computer Science, Nanjing University of Information Science & Technology, Nanjing 210044, China

2. The School of Software, Nanjing University of Information Science & Technology, Nanjing 210044, China

3. The School of Computer Science and Engineering, Macau University of Science and Technology, Avenida Wei Long, Taipa, Macau 999078, China

Abstract

Artificial intelligence (AI) is a very powerful technology and can be a potential disrupter and essential enabler. As AI expands into almost every aspect of our lives, people raise serious concerns about AI misbehaving and misuse. To address this concern, international organizations have put forward ethics guidelines for constructing trustworthy AI (TAI), including privacy, transparency, fairness, robustness, accountability, etc. However, because of the black-box characteristics and complex models of AI systems, it is challenging to translate these guiding principles and aspirations into AI systems. Blockchain, an important decentralized technology, can provide the capabilities of transparency, traceability, immutability, and secure sharing and hence can be used to make AI trustworthy. In this paper, we survey studies on blockchain-based TAI (BTAI) from a software development lifecycle view. We classify the lifecycle of BTAI into four stages: Planning, data collection, model development, and system deployment/use. Particularly, we investigate and summarize the trustworthy issues that blockchain can achieve in the latter three stages, including 1) data transparency, privacy, and accountability; 2) model transparency, privacy, robustness, and fairness; and 3) robustness, privacy, transparency, and fairness of system deployment/use. Finally, we present essential open research issues and future work on developing BTAI systems.

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science,Theoretical Computer Science

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