Thank you for taking a look! Yeah there's definitely a few tells which are noticable if you look for it :)

Thank you for trying! I first built it as 'detect the human' response, but that was counter to the 'slop or not' framing. Yeah I'm also observing the same based on the first few hundred people's results. The harder models seem to write almost too well and that's generally not how humans write on the internet unless it is a blog post/essay. The easier models seem to be the ones that are tripping people the most.

Yeah the UX itself is clearly slop

thank you so much for taking a look :) Yeah you'd be surprised how difficult it can get to spot nuances sometimes. Sometimes, there isn't any nuance at all and the AI is just as good at writing about something pretending to know about the topic.

Also for example this one has a giveaway for the human case: "There are lots of great people here at /r/personalfinance" (actually, not sure if that is a giveaway, that was my guess, but depends on how the model was prompted, I guess). And human ones often seem to have two spaces sometimes instead of one, idk why. If you want to get a serious dataset, maybe you could use this one to find all the flaws and perfect it, and then try to get a real dataset from the next one? People will be more eager to help too if they've seen you designed it all very carefully. (Or you could filter the results from this one to make it a good dataset if you get lots of responses.)

Thanks for checking it out! The color signal is useful feedback. Let me think about it and rework!

Yeah there are some very obvious tells, but the models that are most capable are very good at writing like human.

Especially when the human responses for reddit or HN prompts were presumably made after reading the content of the article or the post; whilw the model is simply going off of the title.

The coloring is a fair point. I was some times confused if I got the right or the wrong one XD

Ha :) I'm not building models, nor am I affiliated with any big labs. The idea is to use this to educate people how to spot tells of AI writing. Although like any data that's made open this can be used to train future models as well I suppose.

Thanks for checking it out! The obvious ones are (hopefully) weaker models :) but yes my experience has been unless you're engaging with human written content consistently the line really blurs easily.