Education · Consumers · Emerging
Over-reliance on AI tools for academic paper review leading to a lack of genuine evaluation and potential degradation of academic standards
PhD students are using AI tools to generate and review papers, resulting in inflated acceptance rates and concerns about the integrity of academic evaluations.
Who experiences it: PhD students
Momentum
0%
Pain
75
Competition
0
Opportunity
49/100
Signals over time
3 observed signals across 1 sources, tracked for 0 days. Confidence: medium.
What people are saying Observed
“As a PhD student, I am seeing the same thing. I am currently generating about 10 papers per month for marginal increments/architectural additions that are autoreviewed in a loop by Claude + Codex until those tools don't spot any major issues and then sending them in to various conferences. Since more than half of the reviewers are just using these tools to review, it's really easy to get a good score. This year I got into ICLR, ICML, NeurIps, SIGGRAPH and ACL with 2-authors papers (me and my supervisor). Its fucked up, but I am getting a lot of praise from the department/supervisor, I got an very good internship lined up next summer, and I have plenty of time to study whatever I find meaningful because the slop generates itself. I think that this ship will sink if enough people do this, so I set up similar systems for some of my colleagues as well. The only way to break the system is to overload it until it doesn't work, so I can only hope for this.”
Hacker News · frustration
“As a PhD student, I am seeing the same thing. I am currently generating about 10 papers per month for marginal increments/architectural additions that are autoreviewed in a loop by Claude + Codex until those tools don't spot any major issues and then sending them in to various conferences. Since more than half of the reviewers are just using these tools to review, it's really easy to get a good score. This year I got into ICLR, ICML, NeurIps, SIGGRAPH and ACL with 2-authors papers (me and my supervisor). Its fucked up, but I am getting a lot of praise from the department/supervisor, I got an very good internship lined up next summer, and I have plenty of time to study whatever I find meaningful because the slop generates itself. I think that this ship will sink if enough people do this, so I set up similar systems for some of my colleagues as well. The only way to break the system is to overload it until it doesn't work, so I can only hope for this.”
Hacker News · frustration
“As a PhD student, I am seeing the same thing. I am currently generating about 10 papers per month for marginal increments/architectural additions that are autoreviewed in a loop by Claude + Codex until those tools don't spot any major issues and then sending them in to various conferences. Since more than half of the reviewers are just using these tools to review, it's really easy to get a good score. This year I got into ICLR, ICML, NeurIps, SIGGRAPH and ACL with 2-authors papers (me and my supervisor). Its fucked up, but I am getting a lot of praise from the department/supervisor, I got an very good internship lined up next summer, and I have plenty of time to study whatever I find meaningful because the slop generates itself. I think that this ship will sink if enough people do this, so I set up similar systems for some of my colleagues as well. The only way to break the system is to overload it until it doesn't work, so I can only hope for this.”
Hacker News · frustration
Why now? AI inference
Existing solutions Observed
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