
AAAI 2027 has flagged collusion in reviewer assignments.
Most submissions come from one country, raising collusion risks.
The conference's acknowledgement is a positive step.
What happened
AAAI 2027 organizers recently emailed reviewers about collusion in the review process, specifically in the 2-cycles category, where authors review each other's papers.
Why it matters
Most submissions come from a single country, increasing the chance that the assignment algorithm naturally creates such 2-cycles, and most colluding authors could be from that country. The conference acknowledging this issue is seen as positive, as such collusion has been suspected for years.
What to watch
It remains unclear if AAAI will release submission statistics as they did last time. The post also notes that some top-conference papers (NeurIPS, ICLR, AAAI, ICML) lack public code on GitHub, hinting at broader integrity concerns.
Ask the AI about this article →
The AAAI 2027 organizers' email about collusion in the review process marks a rare public acknowledgment of a problem that many in the research community have long suspected. The focus on 2-cycles—where authors review each other's papers—highights a specific vulnerability in peer review, especially when a large share of submissions originate from a single country. The original poster declines to name that country, fearing accusations of racism, but the implication is that the algorithm's natural tendency to create such cycles among co-nationals could be exploited. This acknowledgment could lead to changes in how assignments are made or how submissions are monitored. The comment about top-conference papers lacking public code on GitHub is a separate but related concern about research integrity, suggesting that the issue extends beyond collusion to reproducibility. Whether AAAI will release submission statistics, as it did previously, remains an open question that could provide more transparency.
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