Data-Driven Learning for Data Rights, Data Pricing, and Privacy Computing

In recent years, data has become one of the most important resources in the digital economy. Unlike traditional resources, the digital nature of data makes it difficult to value and contract. Therefore, establishing an efficient and standard data-transaction market system would be beneficial for low...

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Bibliographic Details
Published in:	Engineering (Beijing, China) Vol. 25; no. 6; pp. 66 - 76
Main Authors:	Xu, Jimin, Hong, Nuanxin, Xu, Zhening, Zhao, Zhou, Wu, Chao, Kuang, Kun, Wang, Jiaping, Zhu, Mingjie, Zhou, Jingren, Ren, Kui, Yang, Xiaohu, Lu, Cewu, Pei, Jian, Shum, Harry
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01-06-2023 College of Computer Science and Technology,Zhejiang University,Hangzhou 310027,China%International Digital Economy Academy,Shenzhen 518045,China%Craiditx,Shanghai 200050,China%Antgroup,Hangzhou 310023,China%Department of Computer Science and Engineering,Shanghai Jiao Tong University,Shanghai 200240,China%School of Computing Science,Simon Fraser University,Burnaby,BC V5A 1S6,Canada Elsevier
Subjects:	Artificial intelligence Data pricing Data rights Data science Privacy computing Data science Data rights Data pricing Privacy computing Artificial intelligence
Online Access:	Get full text
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Summary:	In recent years, data has become one of the most important resources in the digital economy. Unlike traditional resources, the digital nature of data makes it difficult to value and contract. Therefore, establishing an efficient and standard data-transaction market system would be beneficial for lowering cost and improving productivity among the parties in this industry. Although numerous studies have been dedicated to the issue of complying with data regulations and other data-transaction issues such as privacy and pricing, little work has been done to provide a comprehensive review of these studies in the fields of machine learning and data science. To provide a complete and up-to-date understanding of this topic, this review covers the three key issues of data transaction: data rights, data pricing, and privacy computing. By connecting these topics, this paper provides a big picture of a data ecosystem in which data is generated by data subjects such as individuals, research agencies, and governments, while data processors acquire data for innovational or operational purposes, and benefits are allocated according to the data’s respective ownership via an appropriate price. With the long-term goal of making artificial intelligence (AI) beneficial to human society, AI algorithms will then be assessed by data protection regulations (i.e., privacy protection regulations) to help build trustworthy AI systems for daily life.
ISSN:	2095-8099
DOI:	10.1016/j.eng.2022.12.008