survey

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

Authors:
Peiyun Zhang

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

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

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

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

0009-0009-9016-0895
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,
Qinglin Zhao

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

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

0000-0003-4873-5631
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Authors Info & Claims

ACM Computing Surveys Volume 56 Issue 7Article No.: 163pp 1–31https://doi.org/10.1145/3614424

Published:09 April 2024Publication History

ACM Computing Surveys

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, and so on. 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.

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Index Terms

Exploiting Blockchain to Make AI Trustworthy: A Software Development Lifecycle View
1. Computing methodologies
  1. Artificial intelligence
    1. Distributed artificial intelligence
      1. Cooperation and coordination

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Published in
ACM Computing Surveys Volume 56, Issue 7
July 2024
1006 pages
ISSN:0360-0300
EISSN:1557-7341
DOI:10.1145/3613612
Editors:
David Atienza
Swiss Federal Institute of Technology Lausanne (EPFL), Switzerland
,
Michela Milano
University of Bologna, Italy
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].
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Publication History
- Published: 9 April 2024
- Online AM: 9 August 2023
- Accepted: 3 August 2023
- Revised: 10 May 2023
- Received: 15 September 2022
Published in csur Volume 56, Issue 7

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

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Trustworthy Software Development

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

ACM Computing Surveys

Abstract

REFERENCES

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Recommendations

Trustworthy Software Development

Modern software cybernetics

AI and Blockchain-based source code vulnerability detection and prevention system for multiparty software development

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