Identity Theft in AI Conference Peer Review
By: Nihar B. Shah , Melisa Bok , Xukun Liu and more
Potential Business Impact:
Stops fake scientists from cheating research reviews.
We discuss newly uncovered cases of identity theft in the scientific peer-review process within artificial intelligence (AI) research, with broader implications for other academic procedures. We detail how dishonest researchers exploit the peer-review system by creating fraudulent reviewer profiles to manipulate paper evaluations, leveraging weaknesses in reviewer recruitment workflows and identity verification processes. The findings highlight the critical need for stronger safeguards against identity theft in peer review and academia at large, and to this end, we also propose mitigating strategies.
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