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http://dx.doi.org/10.9708/jksci.2022.27.04.009

A Conceptual Architecture for Ethic-Friendly AI  

Oktian, Yustus-Eko (Blockchain Platform Research Center, Pusan National University)
Brian, Stanley (Dept. of Computer Science of Graduate School, Dongseo University)
Lee, Sang-Gon (Dept. of Information Security, Dongseo University)
Publication Information
Journal of the Korea Society of Computer and Information / v.27, no.4, 2022 , pp. 9-17 More about this Journal
Abstract
The state-of-the-art AI systems pose many ethical issues ranging from massive data collection to bias in algorithms. In response, this paper proposes a more ethic-friendly AI architecture by combining Federated Learning(FL) and Blockchain. We discuss the importance of each issues and provide requirements for an ethical AI system to show how our solutions can achieve more ethical paradigms. By committing to our design, adopters can perform AI services more ethically.
Keywords
AI; AI Ethics; Architecture; Blockchain; Federated Learning;
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