Mike Thelwall – författare

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.

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.

This book is concerned with the application of research methods to address a series of important questions that currently motivate research in this area. By concentrating on individual social media 'objects', it highlights and encourages readers to explore a range of different objects to study, how to design research questions around these, consider ethics where relevant, alongside a range of quantitative and qualitative methods that could be considered.

This handbook presents the state of the art of quantitative methods and models to understand and assess the science and technology system. Focusing on various aspects of the development and application of indicators derived from data on scholarly publications, patents and electronic communications, the individual chapters, written by leading experts, discuss theoretical and methodological issues, illustrate applications, highlight their policy context and relevance, and point to future research directions.

A substantial portion of the book is dedicated to detailed descriptions and analyses of data sources, presenting both traditional and advanced approaches. It addresses the main bibliographic metrics and indexes, such as the journal impact factor and the h-index, as well as altmetric and webometric indicators and science mapping techniques on different levels of aggregation and in the context of their value for the assessment of research performance as well as their impact onresearch policy and society. It also presents and critically discusses various national research evaluation systems.

Complementing the sections reflecting on the science system, the technology section includes multiple chapters that explain different aspects of patent statistics, patent classification and database search methods to retrieve patent-related information. In addition, it examines the relevance of trademarks and standards as additional technological indicators.

The Springer Handbook of Science and Technology Indicators is an invaluable resource for practitioners, scientists and policy makers wanting a systematic and thorough analysis of the potential and limitations of the various approaches to assess research and research performance.