How Organizations Use AI: Evidence from ChatGPT [pdf]
malshe · 114 points · 83 comments · hace 16 horas · Open original
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JCjcimshace 14 horas
I didn't scour the text but one thing I didn't see as an explanatory consideration in the paper is that the larger companies they talk about having larger adoption are also much more likely to have reasonably robust controls (and consequences) that prevent mixing personal/corporate use of AI tooling. That's my world.
On the other hand my girlfriend is a teacher and for the past year ChatGPT has allowed her to augment her lesson plans with slides/games/etc that have had a very positive effect on student engagement. She also uses it to help with analysis of testing data against her lesson plans and state standards to find places to shore things up as the year progresses. She runs the english language learning department in her school and also uses it to help ensure that there is representation in her materials for the huge mix of cultural backgrounds of her students.
It's truly helped her immensely and it's all been on her personal account. The district has no program or budget to guide or support teachers and admin on using these tools in education.
MJmjg2hace 15 horas
Would it kill these OpenAI guys to learn how to write a white paper? Google's DeepMind did better with their AGI to ASI, though I have qualms on their execution.
Whenever I see these Frontier Labs "publish a paper" on ArXiv.org the phrase Esse Quam Videri strides past my mind—is this genuine progress or merely a marketing metric for their stakeholders?
MAmarcus_holmeshace 15 horas
"badly". There, fixed it for you.
Seriously, the best blog post on this subject has to be Ludicity: https://ludic.mataroa.blog/blog/ai-mania-is-eviscerating-glo...
INinterludeadhace 11 minutos
Interesting data, but I think there's a pretty big trap in treating usage intensity as a proxy for economic impact. The finding that early-career workers send substantially more messages than senior people could mean they're getting huge productivity gains. It could also mean they're the ones doing the work that's easiest to delegate to ChatGPT…
DAdatadrivenangelhace 9 horas
They draw a random sample of matched adopters but use the full Compustat population of US companies as non-adopters and don't disclose the sampling rate, which is statistically risky.
Also doesn't account for pilots. If a Enterprise customer has 10 licenses for a pilot, they could be in there.
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5 preview comments · loading full threadLog in to h4cker, then connect Hacker News to publish comments.
I didn't scour the text but one thing I didn't see as an explanatory consideration in the paper is that the larger companies they talk about having larger adoption are also much more likely to have reasonably robust controls (and consequences) that prevent mixing personal/corporate use of AI tooling. That's my world. On the other hand my girlfriend is a teacher and for the past year ChatGPT has allowed her to augment her lesson plans with slides/games/etc that have had a very positive effect on student engagement. She also uses it to help with analysis of testing data against her lesson plans and state standards to find places to shore things up as the year progresses. She runs the english language learning department in her school and also uses it to help ensure that there is representation in her materials for the huge mix of cultural backgrounds of her students. It's truly helped her immensely and it's all been on her personal account. The district has no program or budget to guide or support teachers and admin on using these tools in education.
Would it kill these OpenAI guys to learn how to write a white paper? Google's DeepMind did better with their AGI to ASI, though I have qualms on their execution. Whenever I see these Frontier Labs "publish a paper" on ArXiv.org the phrase Esse Quam Videri strides past my mind—is this genuine progress or merely a marketing metric for their stakeholders?
"badly". There, fixed it for you. Seriously, the best blog post on this subject has to be Ludicity: https://ludic.mataroa.blog/blog/ai-mania-is-eviscerating-glo...
Interesting data, but I think there's a pretty big trap in treating usage intensity as a proxy for economic impact. The finding that early-career workers send substantially more messages than senior people could mean they're getting huge productivity gains. It could also mean they're the ones doing the work that's easiest to delegate to ChatGPT…
They draw a random sample of matched adopters but use the full Compustat population of US companies as non-adopters and don't disclose the sampling rate, which is statistically risky. Also doesn't account for pilots. If a Enterprise customer has 10 licenses for a pilot, they could be in there.