How can the accuracy of literature reviews be improved when using AI tools?

Accuracy in literature reviews using AI tools can be enhanced through critical human oversight guided by specific protocols. Human supervision remains essential for validation and interpretation. Key principles involve verifying all AI-generated summaries and citations against primary sources. Crucially, select AI tools known for robust academic database integration and transparent citation practices. Understand the tool's limitations, such as potential biases in source selection or summarization algorithms, and its scope concerning publication dates and disciplinary coverage. Always maintain rigorous standards for source credibility assessment, applying the same critical evaluation to AI outputs as to manually found materials. Comprehensive validation by the researcher is non-negotiable. Implement improvement by strategically utilizing AI: employ tools like semantic search platforms and citation mapping software (e.g., Connected Papers) to identify key literature and connections. Craft precise queries to minimize irrelevant results. Use AI summaries as starting points, then meticulously fact-check claims and references against original publications. Perform comparative analysis across different AI outputs or alongside traditional manual searches. This structured integration augments efficiency while safeguarding scholarly rigor through consistent human verification.