Do AI Scientists Need a New Research Paper Format?

This May, 37 researchers from roughly two dozen top universities and tech companies published a paper on ArXiv, arguing that scientists should stop writing papers. Why? Because artificial intelligence needs a different format, and AI’s needs, they say, should be the priority.

“AI agents are becoming first-class participants in research workflows, not tools that assist humans but autonomous contributors that read, reproduce, and extend scientific work. That transition demands infrastructure built around agents from the start,” the authors write in the provocative article, titled “The Last Human-Written Paper.” The paper proposes a replacement, called an “Agent-Native Research Artifact” (ARA), that presents work in a format AI agents can use efficiently. (As an example, the paper itself is online in ARA form.)

Jiachen Liu cofounded the Agent Native Research Lab in May. Jiachen Liu

The growth of AI tools in the research process is not without its critics, and scientists’ opinions about that shift are split. Some evidence shows AI-enabled research could boost individuals’ careers in a discipline but generate fewer new ideas and topics. Still, some biologists have come to see promise in AI as a “co-scientist.”

Lead author Jiachen Liu conducted work on the ARA proposal while pursuing her Ph.D. in computer science from the University of Michigan, which she was awarded in 2025. This May, she became a cofounder of the Agent Native Research Lab, an AI-for-science startup in Palo Alto, Calif. She spoke with IEEE Spectrum about the paper and the future of AI in scientific research.

Building infrastructure for an AI collaborator

How did you come to believe AI has become a collaborator for scientists rather than a mere tool?

Jiachen Liu: At the end of 2024 when the [Cursor] coding agent came out, I realized it had a great potential to replace me as a researcher. Yet I still needed to do a lot of harness on top of the AI [creating the infrastructure that guides the model and connects it to the world]. It still needed a lot of manual work. I even wrote an article then to emphasize how the human was so important in the loop.

But AI has advanced since then. Already in 2026 there’s an almost complete undergrad level of knowledge inside the large language models. At some point soon, all the Ph.D.-level or professor-level knowledge will be inside those models. That’s the point where humans cannot provide more value. AIs will have to evolve further by themselves. So we’ll need an infrastructure that allows AI to safely and comfortably evolve. The ARA protocol is a first step to realize this.

What kind of response have you gotten to the paper?

Liu: I got diverse feedback, all of it positive. If they’re not positive, they probably don’t bother reaching out to you, right?

One type was from industry. They see this could make their research and knowledge systems more AI native. That could basically enable collaborations among the whole…