I will write a quantitative economic geography paper over six days from Lantau Island in the South China Sea, without human collaborators, working entirely online.
The paper
Tentatively titled AI Exposure and Labour Market Dynamics in the United States, 2023–2025. It asks how the incidence of AI exposure is associated with basic labour market dynamics in the early AI period.
The recording
Every aspect of assembling the paper — data analysis through to composition — is recorded and broadcast. That archive becomes the material for a second paper, forthcoming with two co-authors at the University of Hong Kong.
Evenings
I will not discuss the paper itself with anyone. But each night I host a live conversation with colleagues and other researchers about AI-assisted research: how AI changes what authorship means, what the comparative advantage of a human researcher is in an AI-intensive world, how we should be training researchers now, and whatever else the guest wants to argue about. Come on stream →
The stakes
Livestream challenges are supposed to have stakes.
Can I write an academic paper that survives desk rejection at a Scopus-indexed journal?
If it works
The masalewali chaanp at New Punjab Club.
Lamb chops, marinated twice over 48 hours, in Central. Eaten alone, on camera, with no one to split the bill with.
If it doesn't
24 additional hours of service to the economic geography community.
Reviewing, letters, discussant duty — whatever is asked, until the hours are paid. Also livestreamed, in full.
B
What the project is about
The bigger things this project is about, besides the best lamb chops in Hong Kong.
01 · Tacit and explicit knowledge
How does AI change the relationship between tacit and explicit knowledge in academic research?
Economic geography has argued for fifty years that the knowledge that matters most cannot be written down. It travels badly, and you learn it by being in the room with people who already have it. Writing with a model looks like it should change that, because a prompt forces you to state what you want. My hypothesis is that it does not reduce how much tacit knowledge a researcher needs. It displaces that knowledge somewhere else, into knowing what to ask and into spotting when a fluent answer is wrong, and those skills may be harder to put into words than the ones they replace.
02 · Transparency in academic production
Is recording everything the last stable frontier of academic openness?
Coming on the heels of a replication crisis, AI has introduced an entirely new way for academic integrity — however defined — to be undermined. The movement toward open access and preregistration has productively made academic production more open. But once tools can stand in for so many parts of the work, full transparency may be the only stable frontier of openness left.
03 · Academic content creation
Will anyone actually watch scholarship happen?
The riskiest experiment here is the one about content. The creator economy has revealed pent-up demand for things once considered genuinely weird: people playing video games, people unboxing gadgets. Will academics and other weirdos turn out for live scholarship? This is one attempt at finding out.
C
About Lantau
Lantau is Hong Kong's largest island, and it holds one of the most connected places on earth: the international airport, the bridge to Macau and Zhuhai, the rail line into Kowloon.
It also holds Chi Ma Wan. The desk sits at 22°13′21″N, 113°59′03″E — a beach on the western shore of the peninsula, inside Lantau South Country Park , country park behind and open sea in front, on a shoreline that once stood in for somewhere else in a Jean-Claude Van Damme film.
Chi Ma Wan Peninsula, south Lantau · the shoreline, and the view from the balcony · illustrations
The independent variable
How remote, exactly?
From the desk
Straight line
Door to door
University of Hong Kong
17.1 km
TBC
Nearest research library
17.1 km
TBC
Nearest shop, Mui Wo
5.2 km
TBC
Ferries per day
—
6
Someone to ask
—
∞
D
Timeline
23 Aug
Arrival
I take the ferry out to Chi Ma Wan and start recording. From that point I have no contact with my co-authors, my colleagues or anyone else in the research community until the recording stops.
23 Aug · 21:00
Kickoff stream
I open the broadcast by explaining what the paper is supposed to be and what I think is most likely to go wrong. Then I put the first question to a model on camera.
I write during the day, from eight in the morning until six in the evening, Hong Kong time. The stream is unedited, so you will see the prompts I write, the answers I throw away, the dead ends I follow, and the long stretches where very little happens.
24 – 26 Aug 21:00 HKT
Nightly conversations
These are casual hangouts with colleagues and viewers about academic writing with AI, and anyone watching can ask a question while we are live. Nobody helps me with my own paper.
I leave with whatever I have managed to write. It might be a finished draft, it might be half of one, and it might be a cautionary tale. I will publish it either way.
Sep – Dec
Paper number 2: the meta paper
All three of us watch the footage on our own and then compare what we found. Two of my co-authors take no part in the writing week, so their reading acts as a check on my account of my own process.
2027
Publication?
Stay tuned to find out.
The evenings are open
Come on stream.
Each evening I open up the stream for conversation with other researchers about how they use AI tools in their work, and to pick their brain about what they think the future holds.
One rule: nothing substantive about my own paper. No feedback on the analysis, no suggestions about the data, no reading of drafts.
