Full Description
The field of social research is characterized by its broad scope and interdisciplinary nature, encompassing the examination of human behaviour, 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 programmes 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.
Contents
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
