Causes of deviation
AI tools may have incomplete information due to ranking tendencies in search results or training data limitations, which is especially evident when it comes to controversial topics.
Specific precautions
- Multi-mode verification: A quick scan in Ultra Fast mode (1-2 minutes) followed by Balanced mode to compare the consistency of key findings
- strategic intervention:: Manually add keywords for opposing viewpoints at the research strategy generation stage (e.g., add "limiting words" when researching "cryptocurrency advantages": disadvantages/risks/scams)
- Source control: Set the SOURCE_WEIGHTS parameter in the .env configuration file to increase the proportion of weight given to authoritative sources such as Wikipedia and academic journals
- Iterative adjustments:: When reporting tendencies are found to be evident, add 5-10 specialized iterations and assign clear instructions such as "please find supporting evidence for the opposite view".
Quality inspection methods
It is recommended to use the "triangulation method": 1) check for the presence of opposing nodes in the knowledge graph 2) use tables to compare key data from different sources and 3) manually search 3-5 highly cited papers through Google Scholar to verify the core ideas. If deviations are found, the preset instruction "Please maintain a neutral position" can be used in the clarification stage.
This answer comes from the articleKResearch: Generate Free In-depth Research Reports with Google Gemini APIsThe
May not be reproduced without permission:AI productivity tools " How to avoid the problem of information bias in KResearch generated reports?
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