Overcoming Fear: Social Scientists’ Perceptions of AI

Abstract

This case study centers around tensions between social science fields over integrating artificial intelligence into research and education. While technologies like natural language processing and machine learning provide faster analysis and new knowledge, the majority of social scientists are wary of their impact on interpretive rigour, ethical values, and disciplinarity. Controversy ensued at Ridgewood University when junior researchers proposed AI-enabled coding for streamlining qualitative data analysis. Senior academics, worried about losing human-based context, resisted the prospect, dreading algorithmic partiality and the loss of methodological integrity. Early-career academics countered that limiting AI to dissertations would stifle innovation at a disadvantage to them as professionals. A symposium at the university showed that AI can augment and not replace conventional methods with the aid of strong ethical frameworks and human guidance. The case refers to broader concerns: harmonizing innovation and prudence, reducing fears over automation, and ensuring that the adoption of AI advances and does not undermine the values of social inquiry. It calls on social scientists to meaningfully address new technologies and to collaborate in exploring standards allowing responsible, open, and context-sensitive use of AI in research.