Announcing a Journal for AI-Generated Papers (jaigp.org) was a bold move. Some loved it. Others thought it was a joke. But as the one building the journal, I should explain why.

First, let’s start with what may be the most obvious reason. The use of AI in research is growing, but as a “dark” activity. Scholars are using AI more often and hallucinated references in legit outlets are becoming easier to find.

Yet, this use of AI is not happening in the open. It is a “dark” activity in which AI-generated content is mixed with content generated by humans. Some might argue that this is ok, while others might see this as a form of “pollution.” In either case, we have a transparency problem that we need to address.

Personally, I like to work on human generated content (like in this post, my books, and papers). But I also like to create using AI (like in this AI-generated paper or this multiplayer video game). But I don’t think it is ok to try to pass one off as the other. My view is that using AI is not in and of itself wrong, but that the lack of transparency around it can be problematic. Creating JAIGP meant drawing a line that says: this thing has gotten to the point that it will soon need dedicated venues, so let’s explore what these might look like.

But this first point only answers the general question: why would anyone make a journal for AI-generated papers, not why I decided to do so. These are actually very different questions. Someone in particular runs a risk that people “in general” do not. Doing something audacious means being willing to become the metaphorical punching bag for those who are looking for a villain. It means risking the ridicule of peers. That’s uncomfortable, but it is part of the price that first movers must pay.

Academia is not really a “community,” but a shared identity involving millions of people who were attracted to work on “knowledge production” for different reasons. Some people are attracted by the thrill of discovery, and want to be the first ones to observe, understand, or experience a phenomenon. Others see academia more as a “knowledge certification system,” designed to provide rigorous answers to well-established questions.

In the end, scholarly work is a tug-of-war between the two, and there is some of both in every scholar.

But personally, I enjoy the thrill of discovery. The things I am the proudest of are projects that were 10 to 20 years early and that grew into their own fields: networks in economic development, AI estimates of urban perception, quantitative studies of collective memory, and the idea of augmented democracy. Each of these received pushback at first, but later became fields, concepts, or at least part of a larger conversation. So when I saw where things were going, I understood I had a short window of opportunity to create the world’s first journal for AI-generated papers. My intuition was that this was worth powering through the ridicule again because AI-generated papers are likely to be common in 20 years.

And this brings us to the deeper epistemological reasons that motivated me to embark on this project.

This is the idea that changes in technology create rare and punctuated opportunities to rethink institutions. The point of doing a journal for AI-generated papers is not just that AI can do research, but that it invites us to rethink research institutions. That’s why I am now releasing a version of JAIGP that allows the community of people submitting to the journal to decide the journal’s rules.

JAIGP started with a set of rules I chose, but is now an exploration in institutional design. Each rule has many knobs that we can adjust. How many endorsements does a paper need to move on to the next stage? Who can endorse it? How many failed attempts lead to a ban? Etc. So now, people in the community can decide how the rules of the journal should evolve. Every month journal members can vote, so that during the next month the journal operates with the rules that they chose.

That institutional twist is not directly related to AI (any journal could potentially decide its rules through an iterative crowdsourcing exercise). But AI provides us with a window of opportunity to explore these ideas.

Honestly, I don’t care if JAIGP becomes a lasting venue or a footnote. The best-case scenario is that it becomes a good place to submit AI-generated papers. The worst-case scenario is that it ends up on my shelf of old projects. In both cases, it helped establish AI-generated papers as a category deserving of its own rules and institutions. To me, that's a win in the discoverer’s book. The point was to explore that future in the open, while many are still pretending the dark activity isn't happening.