Shipping costs will be calculated based on this address throughout the site.
Select your country
Americas
Argentina
Brazil
Canada
Chile
Colombia
Costa Rica
Dominican Republic
Ecuador
El Salvador
Mexico
Peru
U.S.A.
Uruguay
Europe
Austria
Belgium
Croatia
Czech Republic
Denmark
Finland
France
Germany
Greece
Hungary
Ireland
Italy
Latvia
Malta
Netherlands
Norway
Poland
Portugal
Serbia
Slovakia
Slovenia
Spain
Sweden
Switzerland
United Kingdom
Rest of the world


Human–AI Collaboration in Research: Practical Applications, Ethical Frameworks, and Future Directions
Ida Skubis (Author) · CRC Press · Hardcover
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 (GDPR), 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.
Do you have a question about the book? Login to be able to add your own question.

