Generative AI in the Social Sciences and Humanities

Navigating Challenges and Opportunities in Research and Education
1. Auflage 2026
ISBN: 978-1-041-14370-3
Verlag: Taylor & Francis Ltd

Buch, Englisch, 272 Seiten, Format (B × H): 156 mm x 234 mm

Generative AI is transforming how we learn, teach, and conduct research, reshaping the foundations of the social sciences and humanities. Generative AI in the Social Sciences and Humanities examines this profound shift, offering an accessible and authoritative guide for scholars, educators, and professionals navigating the opportunities and risks of AI in academic life.

Bringing together an international team of contributors from Poland, Italy, the UK, Ukraine, and Finland, this volume provides an interdisciplinary exploration of how generative AI is reshaping research practices, educational environments, and scholarly culture within SSH. The book covers a broad thematic landscape: from the evolution and taxonomy of AI, to its uses in disinformation studies, academic integrity, and specialized professional training. It includes empirical insights from focus groups and classroom research, detailed analyses of LLM-driven risks such as hallucinations, bias, and erosion of critical thinking, as well as practical applications like AI-enhanced tutoring and dataset governance. Combining theoretical perspectives with real-world examples, the monograph illuminates how AI tools are deployed, perceived, and negotiated in universities, research institutions, and digital public spheres.

The book is unique for its SSH-focused perspective, empirical depth, and strong ethical framing. It provides concrete guidelines and best practices for the responsible use of AI, enabling researchers, educators, and students to balance innovation with integrity. By bringing technical and humanistic perspectives into dialogue, the volume offers a vital roadmap for navigating AI’s rapidly evolving place in academic life.

· First major volume fully dedicated to AI in the social sciences and humanities, not STEM.

· Based on original empirical research (focus groups, classroom studies, interviews).

· Offers practical guidelines for researchers, educators, and decision-makers.

Zielgruppe

Academic, Postgraduate, and Undergraduate Advanced

Autoren/Hrsg.

Olszowski, Rafal

Gomulka, Jakub

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
• Sozialwissenschaften Pädagogik Lehrerausbildung, Unterricht & Didaktik E-Learning, Bildungstechnologie
• Sozialwissenschaften Soziologie | Soziale Arbeit Spezielle Soziologie Wissenssoziologie, Wissenschaftssoziologie, Techniksoziologie
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein Soziale und ethische Aspekte der EDV
• Sozialwissenschaften Medien- und Kommunikationswissenschaften Kommunikationswissenschaften
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken

Inhaltsverzeichnis

Introduction, Chapter 1: The Evolution of AI: Bridging Technology and the Humanities, Chapter 2: AI Myths and Realities: Separating Fact from Fiction, Chapter 3: Opportunities and Threats of AI in the Social Sciences and Humanities: Insights from a Focus Group Interview, Chapter 4: Misinformation, Disinformation, and Critical Thinking in Academic Contexts: The Impact of AI, Chapter 5: The Phenomenon of AI Hallucinations and Their Influence on Society and Academic Communication in SSH, Chapter 6: Teaching Applications of AI in Social Sciences and Humanities: An Overview, Chapter 7: Research Applications of AI in the Social Sciences and Humanities: An Overview, Chapter 8: AI in Specialised Education and Professional Training, Chapter 9: Understanding University Students' Perspectives on Generative AI, Chapter 10: AI as a Tool for Developing Critical Thinking Among Students, Chapter 11: AI Ethics in the Social Sciences and Humanities, Chapter 12: AI-Generated Images: Use Cases, Benefits, and Risks for Social Sciences and Humanities, Chapter 13: LLMs in SSH-researchers' Practices: A Case Study of Wittgenstein-related Customised GPTs, Chapter 14: Large Language Models: Mathesis Universalis Without Method, Chapter 15: Psychological Foundations of Technological Harmony

Über Autor(innen)

Rafal Olszowski is a social scientist specializing in research on e-participation, the public sphere, political communication on social media, argument mining, AI ethics, e-government, and the history of political doctrines. He is affiliated with AGH University of Kraków. He is the author of two monographs: Permanence and Change in the Political Thought of Edmund Burke (2021) and Collective Intelligence in Open Policymaking (2024). In addition to his academic work, he is an experienced business consultant in new technologies, a designer of educational board games, and a manager of innovation-driven learning projects. Beyond his professional activities, he is actively involved in the non-governmental sector through the Aurea Libertas Institute Foundation.

Jakub Gomulka is a philosopher and computer scientist whose work centres on Ludwig Wittgenstein, Stanislaw Lem, knowledge graph technology, and the applications of generative AI within the humanities. He is affiliated with the Faculty of Humanities at the AGH University of Kraków. He is the author of two monographs on Wittgenstein’s philosophy and currently serves as the lead researcher in the development of the ongoing Lem Knowledge Graph project. In addition, he contributes to the Wittgenstein Ontology project conducted by the Wittgenstein Archives at the University of Bergen.