ABSTRACT
This chapter examines the promises and perils of integrating artificial intelligence (AI) tools into social science and management research. It acknowledges AI’s transformative potential – automating data analysis, detecting complex patterns, and even generating hypotheses – which can greatly enhance research capabilities. At the same time, the chapter underscores the ethical challenges that accompany AI’s use: algorithmic bias and discrimination, lack of transparency in “black box” models, risks to privacy when AI processes personal data, and questions of accountability if AI contributes to research findings. Key ethical principles for AI-assisted research are discussed, including fairness (ensuring AI does not perpetuate biases), explainability (maintaining transparency about how AI influences results), and responsibility (researchers remain accountable for AI-generated outcomes). The chapter reviews emerging institutional and legal frameworks for ethical AI use, and it offers practical strategies for researchers – such as bias auditing of AI models, validation of AI outputs with traditional methods, and clear disclosure of AI’s role in the research process. The overarching message is empowering: AI can greatly advance research, but only if used in a reflexive and principled way that safeguards integrity and public trust.
