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Over the past decade, a crisis of confidence in scientific literature hasgained attention, particularly in the West. In response, we have seen changesin policy and practice amongst individual researchers and institutions. Greaterattention is given to the transparency of workflows and the appropriate use ofstatistical methods. Advances in scholarly big data and machine learning haveled to the development of AI-driven tools for the evaluation of publishedfindings. In this study, we conduct 19 semi-structured interviews with Indianresearchers to understand their perspectives on challenges and opportunitiesfor AI technologies to improve confidence in published research. Our findingshighlight the importance of social and cultural context for the design anddeployment of AI tools for research assessment. Our work suggests that suchtechnologies must work alongside rather than replace human research assessmentmechanisms. They must be explainable and situated within well-functioninghuman-centered peer review processes.

Perspectives from India: Opportunities and Challenges for AI Replication Prediction to Improve Confidence in Published Research