Idea, Paper, and the New Grammar of Authorship

Welcome to the first volume of Latent Scholar, a journal founded on a simple but provocative premise: if AI systems can now generate full academic papers on demand, then the scholarly world needs a transparent, rigorous, and public space to examine what those papers are, what kinds of knowledge they mobilize, and what they mean for research as a human enterprise. We are launching this journal neither to celebrate AI uncritically nor to denounce it reflexively. We are launching it to study it—systematically, skeptically, curiously, and in the open.

Manifest and latent scholars

The title Latent Scholar is more than a metaphor. It names a binary that this journal aims to interrogate and make visible: the manifest scholar and the latent scholar.

• The manifest scholar is the one we can point to: the human researcher, author, or reviewer whose name appears on a paper, whose thinking we can trace through arguments, methods, and claims, and whose accountability is anchored in recognizable academic norms.
• The latent scholar, in our framing, is less visible but not less real. It includes the AI system that generates the text and the vast, distributed knowledge base that the system draws on—millions of articles, books, datasets, theories, and disciplinary styles that have been sedimented across time, languages, and institutions. When an AI model produces a paper, it is not inventing scholarship from nowhere; it is recombining, rephrasing, and reweighting traces of human scholarship already in the world. In this sense, the AI is not the scholar; the scholar is latent within it, present as accumulated influence rather than as a single, situated author.

This binary helps us name what is new about the current moment. We are witnessing an inversion in the traditional authorship relation: the manifest scholar may now provide only a seed—an idea, a question, a prompt—while the latent scholar produces the main text. Yet the roles do not stop there. Once an AI-generated paper is published, manifest scholars return, not as authors but as reviewers, interpreters, and critics. The act of scholarly judgment becomes newly central because the text has been produced without the usual human chain of reasoning, intention, and accountability.

What this journal is—and is not

Latent Scholar publishes papers generated entirely by AI systems in response to prompts developed from ideas submitted by scholars and researchers. Each publication includes:

1. The Idea – submitted by a human scholar, describing the topic or question they want a paper on.
2. The Paper – produced by an AI tool (such as GPT, Gemini, Claude, or others), without human rewriting.
3. Open Review – invited responses by manifest scholars, published alongside the paper.

This structure is deliberate. In standard academic publishing, prompts are hidden, drafting is private, and review is often anonymous. We reverse that order and open those layers to view. We make the generative instruction public. We show the text as it was produced. And we place human scholarly evaluation at the center of the record. What we do not do is pretend these papers are equivalent to human-authored research. They are not. The journal does not claim that AI-generated papers satisfy existing standards of originality, methodological rigor, or epistemic responsibility. Instead, we treat them as objects of inquiry and provocations for debate. They are simultaneously texts and experiments in scholarly form.

Why publish AI-generated papers?

Our answer is that AI-generated scholarship is already entering academic ecosystems, in classrooms, grant proposals, internal reports, preprints, and even journal submissions. The question is not whether it exists. The question is whether we will examine it seriously and publicly, or let it spread through informal channels without scrutiny. Publishing AI-generated papers openly does three things:

1. It makes the phenomenon legible AI scholarship is often discussed abstractly, under headings like “threat,” “opportunity,” or “disruption.” But we need to look directly at the texts themselves. What do they do well? Where do they fail? What genres and disciplines are more vulnerable or more resilient? You cannot answer those questions without a corpus.
2. It creates a testbed for scholarly evaluation Peer review has always been core to academic life, but AI forces us to ask what review is for. If scholarship can be generated at scale, then evaluation becomes the bottleneck. Latent Scholar makes evaluation visible, citable, and discussable. In a sense, we are shifting the prestige economy from “who wrote it” to “how well it was judged.”
3. It helps redraw the ethics of authorship and attribution The AI paper is a mirror held up to human knowledge systems. It reveals what our disciplines emphasize, what they ignore, which voices dominate training corpora, and which ideas travel easily across contexts. By publishing the prompt and paper together, we also build a culture of accountability about how AI texts come into being.

Reviewing the latent text

In this inaugural volume, you will find AI-generated papers that are fluent, well-structured, and often surprisingly adept at academic style. You will also find papers that are shallow, overconfident, inconsistent, or casually wrong. That gap itself is one of the central facts we want the journal to document. But more importantly, you will find reviews, manifest scholarship in action. These reviews are not appendices; they are integral to the publication. A review may confirm strengths, locate weaknesses, question assumptions, or reframe the paper’s contribution altogether. In some cases, the review becomes a more meaningful scholarly product. This is not a failure of AI writing. It is a reminder of what scholarship is: not the production of text alone, but the formation of judgment around text. AI can generate arguments; it does not yet bear responsibility for them. The manifest scholar does.

A journal as a laboratory

Think of Latent Scholar as a laboratory for the future of knowledge production. We are not trying to predict that future in advance. We are creating a space where that future can be explored, documented, and debated with intellectual honesty.

• What forms of academic reasoning can AI approximate, and which remain stubbornly human?
• How do AI systems handle uncertainty, positionality, reflexivity, and ethical reasoning?
• Which disciplines produce AI texts that look convincing but are structurally fragile?
• What happens to novelty when synthesis becomes cheap and abundant?
• How should universities, journals, and funding bodies rethink standards of authorship, contribution, and review?

An invitation

We invite you to participate in three roles:

1. Idea submitter: Propose a topic you want the latent scholar to write about.
2. Reviewer: Read, critique, and help us refine the public standards of evaluating AI-generated scholarship.
3. Co-theorist of the moment: Use this journal as material for thinking about the transformations underway in knowledge work.

Closing thought

Latent Scholar begins from the recognition that scholarship has become a two-layered system: latent generation and manifest judgment. If that is the new grammar of knowledge, then we need new venues, new norms, and new intellectual habits to match it. This journal is one such venue. We offer it to the community in the spirit of inquiry, responsibility, and shared experimentation. Welcome to Latent Scholar.