Human-AI Collaboration in Research | Practical Applications, Ethical Frameworks, and Future Directions
Idioma: inglés
Editorial: Taylor & Francis Ltd, 2026
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Human-AI Collaboration in Research | Practical Applications, Ethical Frameworks, and Future Directions | Daniel Xerri (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2026 | Taylor & Francis Ltd | EAN 9781041331636 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
N° de ref. del artículo 135203889
- Título
- Human-AI Collaboration in Research | Practical Applications, Ethical Frameworks, and Future Directions
- Autor
- Daniel Xerri (u. a.)
- Editorial
- Taylor & Francis Ltd
- Año de publicación
- 2026
- Estado
- Neu
- Encuadernación
- Buch
- Idioma
- inglés
- ISBN 10
- 1041331630
- ISBN 13
- 9781041331636
- Peso del artículo
- 224 gramos
- Dimensiones
- 223 x 146 x 11 mm
- Catálogos de vendedores
- Bücher
Human–AI Collaboration in Research: Practical Applications, Ethical Frameworks, and Future Directions positions human–AI collaboration (HAIC) as a defining feature of contemporary research ecosystems. The book examines the incorporation of AI across the research lifecycle, including research design, literature work, data collection and processing, analysis, interpretation, academic writing, and dissemination. It highlights the opportunities created by automation and generative systems, alongside the challenges raised for research integrity, accountability, transparency, privacy, and epistemic authority. Ethical and regulatory foundations are addressed through established frameworks such as the Belmont Report and the Declaration of Helsinki, as well as European governance instruments including the Ethics Guidelines for Trustworthy AI, the General Data Protection Regulation, and the EU Artificial Intelligence Act. By combining interdisciplinary perspectives from robotics, management research, and education, the volume translates abstract ethical principles into concrete research-relevant practices, offering a coherent and human-centred approach to trustworthy AI-supported inquiry.
The book offers original, research-ready frameworks and applied guidance for responsible HAIC, combining real-world case studies with practical strategies for trustworthy AI use. It equips researchers, educators, and management scholars with tools for human oversight, transparency, bias mitigation, and accountable AI-supported workflows, ensuring scientific rigour alongside innovation.
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Acerca del autor
Ida Skubis is an Assistant Professor at the Silesian University of Technology in Poland. She holds a PhD in Linguistics and possesses Master’s degrees in four languages. She has extensive professional experience in both academia and business, having held managerial positions in international companies. She currently serves as the CEO of the Housing Community. She is actively involved in interdisciplinary AI projects and frequently participates in international conferences. Additionally, she serves as a reviewer for international journals on AI-related topics. She has received numerous scholarships and awards for her scientific research, including a prestigious scholarship in France under the Marie Skłodowska-Curie Actions (Horizon Europe) for her research on the Ethics of AI. https://idaskubis.net/
Daniel Xerri is an Associate Professor in Applied Linguistics and TESOL at the University of Malta and the Chairperson of the ELT Council. He has published widely on different areas of English language education. He has co-edited more than ten books and authored over 250 publications. He has also delivered plenary talks and keynotes in 20 countries, and his research has been awarded international prizes. His main research interests are teacher research, educational technology, and professional learning. His most recent book is The Rise of English as a Glocal Language: Reimagining its Role in an Era of Deglobalisation (Springer, 2026). www.danielxerri.com
Mladen Adamovic is a Reader in Global Management at King’s College London. His recent research on AI in management focuses on algorithmic bias, ethnic discrimination in recruitment, and the implications of AI for equality, decision making, and leadership. He is an expert in business research methods and uses surveys, field experiments, and advanced quantitative analyses. His work has been published in more than 50 peer-reviewed journal articles, including The Leadership Quarterly and Human Resource Management Journal, and has also appeared in Harvard Business Review. As an award-winning scholar and highly regarded educator, he regularly delivers executive education.
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