In the current era, people and society have grown increasingly reliant on artificial intelligence (AI) technologies. AI has the potential to drive us towards a future in which all of humanity flourishes. It also comes with substantial risks for oppression and calamity. In response, researchers and organizations have been working to publish principles and develop AI regulations for the responsible use of AI in consequential application domains. However, these theoretically formulated principles and regulations also need to be turned into actionable algorithms to materialize AI for good. This book introduces a unified perspective of Socially Responsible AI to help bridge conceptual AI principles to responsible AI practice. It begins with an interdisciplinary definition of socially responsible AI and the AI responsibility pyramid. Existing efforts seeking to materialize the mainstream responsible AI principles are then presented. The book also discusses how to leverage advanced AI techniques to address the challenging societal issues through Protecting, Informing, and Preventing, and concludes with open problems and challenges. This book serves as a convenient entry point for researchers, practitioners, and students to understand the problems and challenges of socially responsible AI, and to identify how their areas of expertise can contribute to making AI socially responsible.
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Lu Cheng is a tenure-track assistant professor in Computer Science at University of Illinois at Chicago (UIC), USA. Lu's research focuses on bridging conceptual AI principles to responsible AI practice using both statistical and causality-aware methods. Lu has published in SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), ACM International Conference on Web Search and Data Mining (WSDM), Association for the Advancement of Artificial Intelligence (AAAI), International Joint Conference on Artificial Intelligence (IJCAI), and Annual Meeting of the Association for Computational Linguistics (ACL), among others. She is the web chair of WSDM'22 and senior program committee member of AAAI'22–23. Lu was the recipient of the 2022 Computer Science PhD Outstanding Student Award in the School of Computing and Augmented Intelligence, 2021 Arizona State University Engineering Dean's Dissertation Award, 2020 Arizona State University Graduate Outstanding Research Award, and IBM PhD Social Good Fellowship.
Huan Liu is a professor of Computer Science and Engineering at Arizona State University (ASU), USA. His research interests are in data mining, machine learning, social computing, and artificial intelligence. He is a co-author of a textbook, Social Media Mining: An Introduction, Cambridge University Press; Field Chief Editor of Frontiers in Big Data and its Specialty Chief Editor of Data Mining and Management. He is a Fellow of Association for Computing Machinery (ACM), Association for the Advancement of Artificial Intelligence (AAAI), American Association for the Advancement of Science (AAAS), and Institute of Electrical and Electronics Engineers (IEEE).
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