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Generative AI in Research
Details
The growing popularity of Generative AI has stirred new debates about the future of knowledge production. With a prompt and a click, regular users can now generate contents on just about any topic of interest, drawing from hundreds of billions of parameters with which the latest versions of Gen AI models are trained. As Generative AI rapidly evolves with more advanced features and capabilities, stakeholders have expressed worries that AI models will displace humans as central agents in the research process. This book examines the case for and against applications of Gen AI in research, highlighting the prospects and pitfalls. Using exemplar prompts and custom GPTs created by the authors, it explores prospective use cases for automated data processing, complex modelling and simulations; applications in experimental designs; and review of draft manuscripts. The book also engages with key issues around algorithmic bias, inaccuracies, fake information, epistemic injustice, and the ethics of AI applications in research.
In some ways a companion piece to the authors' previous title, 'Generative AI in Higher Education: Innovation Strategies for Teaching and Learning', this book has a particularly practical appeal for researchers, as well as university officials and policymakers getting to grips with the explosion of AI-assisted research. It will also be of value to scholars of AI and innovation strategy in higher education.
Provides in depth exploration of AIs impact on research design, data analysis, and feedback Offers practical insights into how AI can enhance or undermine knowledge production in research Critically engages with the future of AI in research, posing questions about AIs evolving role in knowledge production
Autorentext
Oluwaseun Kolade is a Full Professor of Entrepreneurship and Digital Transformation at Sheffield Business School, Sheffield Hallam University, UK. He has authored more than 100 academic outputs spanning digital transformation, AI, circular economy and SMEs strategies.
Abiodun Egbetokun is Senior Lecturer in Business Management at De Montfort University, Leicester, UK, and a Senior Fellow of the Higher Education Academy (SFHEA). His current research examines the implications of LLMs in research, industry and higher education.
Adebowale Owoseni is a Senior Lecturer in Information Systems at De Montfort University, Leicester, UK, and a Senior Fellow of the Higher Education Academy (SFHEA). He transitioned to academia in 2019 after a 13-year career in fintech.
Inhalt
Chapter 1: Gen AI for Research revolution or risk.- Chapter 2: Generative AI Applications in Research Design.- Chapter 3: Gen AI enabled data generation and simulation in Social Sciences.- Chapter 4: Generative AI Use Cases for Data Processing and Analysis.- Chapter 5: Towards Methodological Innovation CoCreating Research Design with Generative AI.- Chapter 6: Reviewing manuscripts for originality significance and rigour.- Chapter 7: Gen AI for public engagement and knowledge exchange.- Chapter 8: The future of AI for knowledge production.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09783032024398
- Sprache Englisch
- Genre Economy
- Lesemotiv Verstehen
- Größe H16mm x B148mm x T210mm
- Jahr 2026
- EAN 9783032024398
- Format Fester Einband
- ISBN 978-3-032-02439-8
- Titel Generative AI in Research
- Autor Oluwaseun Kolade , Abiodun Egbetokun , Adebowale Owoseni
- Untertitel Applications in Research Design, Data Analysis and Feedback
- Gewicht 410g
- Herausgeber Springer-Verlag GmbH
- Anzahl Seiten 228