The AI Turn in Academic Research

Abstract

Critical AI Research redefines how scholars engage with artificial intelligence in academic work. Written by Mohamed Kharbach and Johanathan Woodworth, this book provides a critical yet pragmatic roadmap for researchers who want to use AI tools while maintaining intellectual autonomy and ethical integrity. Organized in seven parts, it examines every stage of the research process, including note-taking, literature reviews, data collection, analysis, writing, and ethical reflection. Readers learn to approach AI as a thinking partner rather than a content generator, cultivating transparency, methodological rigour, and epistemic awareness in their use of emerging technologies. Each chapter combines conceptual analysis with practical examples of AI platforms such as ChatGPT, Claude, Perplexity, and Elicit. The authors show how these tools can assist with literature synthesis, qualitative coding, and data visualization while emphasizing that AI supports but does not replace critical thought. The book concludes with a detailed discussion of AI ethics in research, focusing on authorship, bias, originality, and academic integrity. Instead of prescribing compliance, it encourages readers to adopt an ethically informed practice grounded in scholarly responsibility and reflective engagement. Critical AI Research is intended for graduate students, early-career researchers, and experienced academics who wish to engage critically and productively with AI in their scholarly work. It presents AI as a tool for deeper inquiry rather than a shortcut to automation.

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