Record summary
A quick snapshot of what this page covers.
Risk profile
How this risk is described and categorized.
"These risks pertain to the misuse, misinterpretation, or leakage of data, which can lead to erroneous conclusions or the unintentional dissemination of sensitive information, such as private patient data or proprietary research. Recent research has demonstrated how LLMs can be exploited to generate malicious medical literature that poisons knowledge graphs, potentially manipulating downstream biomedical applications and compromising the integrity of medical knowledge discovery [28]. Such risks are pervasive across all scientific domains."
Suggested mitigations
Defenses that may help with related attacks.
Source
Research source for this risk, when available.
Included resource
Risks of AI Scientists: Prioritizing Safeguarding Over Autonomy
Original source
MIT AI Risk Repository
Open the public repository used for AI risk records and taxonomy fields.
