Handbook on the Sociology of Artificial Intelligence - call for chapters

Proposed book editor: Tamanna M. Shah, Assistant Professor of Instruction, Ohio University 

Deadline: 10 October 2024

How to submit

Project outline

The Handbook on the Sociology of Artificial Intelligence offers an in-depth overview of the major trends in the field, addressing both the societal causes and effects of artificial intelligence. AI's pervasive influence necessitates a thorough sociological examination, from redefining labor markets and privacy norms to influencing political processes and altering social interactions. This handbook will systematically explore AI's sociological dimensions, to feature a theory-driven review of recent research, presenting approaches to investigating artificial intelligence as it transforms society, culture, and human relations. A recent Socius article highlighted a glaring need for a true “sociological analysis” of artificial intelligence. AI's societal impact spans multiple disciplines, yet much of the current research remains siloed within fields like computer science, ethics, and law. A sociological perspective can provide a holistic understanding of AI's influence on social structures, relationships, and behaviors. This publication aims to bridge these disciplinary divides, fostering interdisciplinary collaboration essential for addressing the complex societal challenges posed by AI. The handbook will serve as an intellectual space for scholars focusing on the sociological aspects of AI, promoting the development of new approaches, schools of thought, and innovative directions in scholarship.

Call for chapters

After an introductory chapter written by the editor, the Handbook will be structured under the following four sections (tentative) where each chapter should ideally provide an overview of the most important sociological concepts and research related to AI as well as provide some indication of a research agenda for the future.

Potential chapters might include but are not limited to:

Part I: Foundations of Artificial Intelligence and Society

• Evolution of AI, theoretical and philosophical foundations to practical applications

Part II: The Ontology and Epistemology of Human Data

• Datafication and the transformation of human experience
• The politics and ethics of data collection and representation
• Case studies in the utilisation of human data

Part III: Uncovering and Debunking AI Myths

• The construction, propagation, and impact of AI myths on policy and public perception
• Debunking AI myths, critical perspectives, and realities

Part IV: Imagining Equitable AI Futures

• Participatory design and inclusive development in AI
• Policy frameworks and governance for equitable AI, case Studies in AI for social justice

Part V: AI, Ethics, and Policy

Part VI: AI in Practice

• AI and the reproduction of social inequalities
• Structural discrimination in algorithmic design
• Intersections of race, gender, and class in AI systems
• Computational Sociology
• Empirical studies on inequality and discrimination in AI applications

Part VII: Teaching a Sociology of AI 

• Curriculum development for Sociology of AI courses
• Pedagogical approaches and best practices, incorporating interdisciplinary perspectives
• Case studies and practical exercises/assignments

Part VIII: Future Directions and Innovations

The book will be aimed at researchers, post-graduate students, and those outside academia in policy and practice. Therefore, chapters should be written in an accessible manner. Contributors can refer to their own research, but the focus should be on a broad overview of the field and a summary of the key research. Each chapter is expected to be around 8,000 words. There is also a possibility of some jointly authored chapters, perhaps combining an established scholar with an early-career researcher.