Compound AI Systems: How Publisher AI Helps Researchers
Автор: NSF-Simons AI Institute for Cosmic Origins
Загружено: 2025-12-01
Просмотров: 8
Abstract
Scholarly communication still runs on workflows built for 1999. They’re costly, slow, and brittle.
I’ll share what we’ve learned building publisher specific AI systems: where generic chatbots fail in editorial contexts, and what purpose-built systems embedded in manuscript and peer-review workflows can do today. We’ll walk through AI triage that flags scope/rigor issues and journal fit in minutes; citation/figure checks that catch problems early; and reviewer discovery that explains “why this reviewer.”
I’ll discuss how these capabilities shorten time-to-first-decision, reduce manual error, and improve the experience of editors, reviewers, and authors.
Dustin Smith is Co-Founder & CEO of Hum, which builds AI systems used by leading publishers like Oxford University Press (MNRAS), Institute of Physics Publishing (ApJ), and IEEE (IEEE Access). His team ships taxonomy, engagement, and peer-review tooling that plugs into publishing platforms to improve efficiency, personalization, and discovery at scale.
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