Turns out being a domain expert (here, a practing professional artist) does indeed help - the latter produced more faithful copies and more creative divergent pieces. But AI (GPT-4o which was sota back then) blows laymen out of the water and challenges artists.
Amazing scene at a socsci internet research seminar.
At the end a comp sci guy asks if there's maybe practical takeaways, action points we could summarize.
First gets accused of "sounding like chatgpt", then a socsci lady pulls out a pack and goes well no but can I interest you in these tarot cards?
In light of recent AI writing debates, NeurIPS rejecting papers based on AI-detector results (lol), and certain academics piling AI user colleagues on the other app...
What is actually more important in an academic paper:
- the prose, narrative, writing, or
- the question, method, result, insight?
2/ ...will turn down this amazing revenue increase opportunity: more people want/need to publish more, and the want to publish open access ($$!) so other people's agents can cite them more.
This won't change (and will get worse) as long as science is evaluated by N papers and N citations.
Not even out of context. Quite literally, we don't do action points or policy recommendations, but have you seen our special tarot cards.
I'm grateful to be invited to these more qualitative research and soc sci spaces sometimes, but sometimes it can be...interesting. Very nice seminar though.
Prediction:
- most major publishers will AI-automate desk decisions and/or review in next few years. A similar pipeline in reverse will be sufficient for their (already low) level of review quality.
- open access will increase (to get cited by agents)
NO WAY a capitalist enterprise will... 1/
3/ The career hallmark of "has published over 100 papers" may become the average phd or postdoc output expectation.
It's gonna get worse before it gets better, i.e. before we arrive at a more sustainable model of science eval, phd awarding criteria, and dissemination model. Which may take a while.