The field of social research is characterized by its broad scope and interdisciplinary nature, encompassing the examination of human behavior, societies, and various facets of social existence; however, it is influenced by numerous factors, including technological advancements. It is therefore no surprise that Artificial Intelligence (AI) has rapidly become a driving force, bringing about substantial transformations within the field.
The use of AI-assisted tools and programs for the collection, analysis, and interpretation of both quantitative and qualitative data is increasing at a remarkable pace. The implications of utilizing these applications are significant and noteworthy. While these technologies present numerous opportunities, it is important to acknowledge the accompanying dilemmas and risks associated with this form of technological advancement.
With a focus on AI's research implications, this book explores various considerations and examples across different disciplines of social research. It highlights the considerable promise AI holds for revolutionizing the discipline while also guiding readers in contemplating the potential drawbacks and various concerns. By doing so, researchers can optimize the capabilities of AI and promote its responsible, reliable, and beneficial application in enhancing and advancing social research.
Daugiau informacijos
Academics and researchers in the fields of sociology, psychology, anthropology, political science, economics, and other social sciences.
Chapter 1: Introducing "Artificial Intelligence (AI) in Social Research"
PART A: AI and Social Research Implications
Chapter 2: The Interconnection of
AI and Social Research
Chapter 3: Using Generative AI for Creativity and
Automating Time-consuming Tasks in Research
Chapter 4: Expanding the
Frontiers: Revolutionizing Quantitative Data Analysis in Social Sciences with
AI Expanding the Frontiers: Revolutionizing Quantitative Data Analysis in
Social Sciences with AI
Chapter 5: Using AI Agents in Quantitative Social
Research
Chapter 6: AI Augmented Qualitative Analysis: Is it the Right Choice
for your Study?
Chapter 7: Generative AI: A Catalyst for Paradigmatic Change
in Qualitative Data Analysis
Chapter 8: A Guide for Qualitative Researchers
Using Large Language Models with Representative Examples Using ChatGPT
Chapter 9: AI in Ethnography - Challenges and Collaborations
Chapter 10:
Exploring Research Design in the Context of Artificial Intelligence:
Evidence-based Recommendations for Social Research and Practice PART B: AI
and Social Research Rigor, Bias, and Ethical Considerations
Chapter 11:
Machine Learning Bias: Genealogy, Expression and Prevention
Chapter 12: Rigor
in Qualitative and Quantitative Studies that Make Use of AI Tools:
Reliability, Validity, Credibility, Transferability, Dependability, and
Confirmability Issues
Chapter 13: The Ethical Implications of Using AI in
Qualitative Research PART C: AI and Research Within Various Social Contexts,
and Case Studies
Chapter 14: Precision Nudging: The Future of Behaviour
Change
Chapter 15: Competence Frameworks for Exploring Generative AI in
Education
Chapter 16: Data Collection Methods in the Age of Artificial
Intelligence: Insights From a Survey-based Study on College Students
Perceptions and Use of AI
Chapter 17: Artificial Intelligence and
International Business
Chapter 18: AI Systems Employed in Archaeological
Research for Ancient Artefacts - A Dilemma
Chapter 19: Conclusion
Prokopis A. Christou is an Assistant Professor at the Cyprus University of Technology. He has published books and articles in various academic journals. His interest in AI stems from his observation that it is becoming increasingly useful in research, yet is associated with a number of risks. As such, he is investigating the implications, potentials, dynamics, limitations and perils of AI in research, society, and different social fields, such as education.
