Innovation, Sustainability, Human-Machine Systems
Peer reviewed
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This Commentary responds to “Fighting Fire with Fire: Infusing AI into Peer Review to Sustain Quality Scholarship” and questions the premise that rising submission volume poses an existential threat.
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This Commentary responds to “Fighting Fire with Fire: Infusing AI into Peer Review to Sustain Quality Scholarship.” It shares the paper’s core position, that journals should govern artificial intelligence openly rather than leave it to the shadows, but it questions the premise that rising submission volume poses an existential threat. The safeguard is human judgment. Our shared fatigue with derivative, repetitive work is a sensor more discerning than any AI detector, because a model trained on what we have already rewarded cannot produce the novelty that our community prizes. The threat to a journal like Management Science is thus more contained than the original alarm implies, provided AI remains a non-final input and humans retain ownership of novelty and contribution. One test should govern any AI workflow: does it ask more of human judgment, or less? This paper was accepted by Christoph Loch, commentary.
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@article{Dai2026Sound,
title = {The Sound We Haven’t Heard Before: A Commentary on “Fighting Fire with Fire: Infusing AI into Peer Review to Sustain Quality Scholarship”},
author = {Tinglong Dai},
journal = {Management Science},
year = {2026},
doi = {10.1287/mnsc.2026.02441},
url = {https://doi.org/10.1287/mnsc.2026.02441}
}FAQ
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