survey

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

Authors:

Qinglin ZhaoAuthors Info & Claims

ACM Computing Surveys, Volume 56, Issue 7

Article No.: 163, Pages 1 - 31

https://doi.org/10.1145/3614424

Published: 09 April 2024 Publication History

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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Cited By

He SChen JZhang PFu Z(2024)Multi-source Trust Model Based on Blockchain and IoT Edge Task Collaboration2024 IEEE 49th Conference on Local Computer Networks (LCN)10.1109/LCN60385.2024.10639735(1-7)Online publication date: 8-Oct-2024
https://doi.org/10.1109/LCN60385.2024.10639735
Li XLi R(2024)A Trustworthiness Evaluation Mechanism Based on Principles–Assumptions ModelIEEE Internet of Things Journal10.1109/JIOT.2024.335770511:10(17510-17524)Online publication date: 15-May-2024
https://doi.org/10.1109/JIOT.2024.3357705
Begum SAhmed MBarua SKabir MMasud A(2024)Research Issues and Challenges in the Computational Development of Trustworthy AI2024 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)10.1109/IICAIET62352.2024.10730209(300-305)Online publication date: 26-Aug-2024
https://doi.org/10.1109/IICAIET62352.2024.10730209
Show More Cited By

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

cover image ACM Computing Surveys

ACM Computing Surveys Volume 56, Issue 7

July 2024

1006 pages

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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New York, NY, United States

Publication History

Published: 09 April 2024

Online AM: 09 August 2023

Accepted: 03 August 2023

Revised: 10 May 2023

Received: 15 September 2022

Published in CSUR Volume 56, Issue 7

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Cited By

He SChen JZhang PFu Z(2024)Multi-source Trust Model Based on Blockchain and IoT Edge Task Collaboration2024 IEEE 49th Conference on Local Computer Networks (LCN)10.1109/LCN60385.2024.10639735(1-7)Online publication date: 8-Oct-2024
https://doi.org/10.1109/LCN60385.2024.10639735
Li XLi R(2024)A Trustworthiness Evaluation Mechanism Based on Principles–Assumptions ModelIEEE Internet of Things Journal10.1109/JIOT.2024.335770511:10(17510-17524)Online publication date: 15-May-2024
https://doi.org/10.1109/JIOT.2024.3357705
Begum SAhmed MBarua SKabir MMasud A(2024)Research Issues and Challenges in the Computational Development of Trustworthy AI2024 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)10.1109/IICAIET62352.2024.10730209(300-305)Online publication date: 26-Aug-2024
https://doi.org/10.1109/IICAIET62352.2024.10730209
Preethi DSharma RShrivastava V(2024)A Novel Intelligent Network Forensics Enabled By AI/ML Algorithms and Time Series Analysis in Edge computing2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)10.1109/ICOCWC60930.2024.10470588(1-7)Online publication date: 29-Jan-2024
https://doi.org/10.1109/ICOCWC60930.2024.10470588
Deng QFan ZLi ZPan XKang QZhou M(2024)Solving the Food-Energy-Water Nexus Problem via Intelligent Optimization Algorithms2024 IEEE 20th International Conference on Automation Science and Engineering (CASE)10.1109/CASE59546.2024.10711356(3187-3192)Online publication date: 28-Aug-2024
https://doi.org/10.1109/CASE59546.2024.10711356
Swain PMahajan KRawat RK BPatjoshi PBalaraman N(2023)Block Chain for Cloud Security: Enhancing Trust and Data Integrity in AI-Based Systems2023 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES)10.1109/ICSES60034.2023.10465288(1-6)Online publication date: 14-Dec-2023
https://doi.org/10.1109/ICSES60034.2023.10465288

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