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AI for Knowledge explores the question of whether artificial intelligence (AI) is transforming knowledge access and creation for the good. AI is accelerating our access to knowledge through search, recommendation, summarisation, translation and a proliferating range of tools with AI built in. Generative AI is further changing how we use and create information at home and in the workplace. Yet AI also has a dark side with hallucination, bias and lack of explainability, as well as potential for harmful impacts on social equity and the environment.
The book investigates how AI will impact everyday knowledge discovery, understanding and creation. It considers both the positive benefits and the many informational and ethical challenges, including the impact on our wider information culture. It then weighs up the impact on scholarship, in science, social science and the humanities and including the processes of scholarly communication. It explains the role of libraries and archives and how they could be enhanced using AI. It concludes by showing how governments can regulate AI to ensure social benefit and outlines what we as individuals need to know about AI.
The book helps the reader see through some of the AI hype to understand much more clearly what are the issues around the impact of AI on knowledge access and creation, including the implications for environmental sustainability and the power of Big Tech. What emerges is a nuanced picture of potential benefit and risk, especially when we consider the experiences of those with less privileged access to the digital, particularly those outside the Global North.
List of contents
1 Introduction
2 AI and everyday knowledge
3 AI and research
4 Generative AI and research practice
5 AI and scholarly communication: Peer review
6 Libraries and archives
7 Ensuring the benefits of AI are shared fairly
8 Conclusion
About the author
Andrew Cox, PhD, is Senior Lecturer at the Information School, University of Sheffield, United Kingdom. His interests include the impact of datafication and AI on knowledge creation and use.
Mike Thelwall is Professor of Data Science at the Information School, University of Sheffield, United Kingdom. His interests include applications of artificial intelligence for research evaluation.
