AI Tools in Academic Research
Critically evaluate AI research tools, develop a principled workflow for AI-assisted research, and understand the epistemological implications.
AI tools are changing how research is conducted, but they introduce new risks alongside new capabilities. A principled approach to AI-assisted research requires understanding both.
AI Research Tools: A Critical Evaluation
- Semantic Scholar: Strong for citation analysis and finding related work; does not hallucinate citations
- Elicit: Extracts specific claims from papers; useful for systematic review; verify all extractions
- Consensus: Synthesizes research findings; useful for overview; verify all claims
- Perplexity: Provides cited answers; citations are real but may be misrepresented
- ChatGPT/Claude: Useful for explanation and brainstorming; never use for citations or facts
Epistemological Implications
AI research tools raise important epistemological questions. When an AI synthesizes research findings, it makes choices about which studies to include, how to weight conflicting evidence, and how to characterize findings. These choices are not neutral — they reflect the training data and design choices of the system.
AI summaries of research papers are useful starting points but cannot replace reading the original. Methodology, limitations, and nuance are often lost in AI summaries. For important claims, always read the primary source.
1. Use AI to map the research landscape and identify key papers. 2. Use library databases to find and access actual papers. 3. Read primary sources critically. 4. Use AI to help understand methodology or terminology. 5. Write your own analysis. 6. Verify all facts and citations independently.
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3 questions · Grade 9 level