Thanks @willknight for the excellent overview and analysis of @sarahbmyers, @davidthewid and my new paper on the confusing (and intentionally confused) landscape of ‘open’ AI 🙏👇
https://t.co/cakyGNUC0u
Literally the only thing I can think about when I read this is the eye-watering environmental impacts of manufacturing tens of thousands of GPUs (and replacing them every couple of years to get the latest generations) just to make AI go brrrr 🤦♀️
https://t.co/xMTCbJKHrX
There are some stories that you know will stay with you for a very long time, and this is one of them. Had the honor of profiling these five women who have been warning about AI risks before you'd ever heard of ChatGPT. My latest for @RollingStone https://t.co/nt6kHaWoDD
Few things fill me with dread like the current organized censorship of literature, history, access to knowledge
Then I learn they’re consulting ChatGPT like some computational divining rod because no one can be bothered to read books before banning them.
I’m impossibly tired!
1) Don't ban books
2) Don't waste educators' time with book bans
3) Don't make decisions about books without reading them
4) Don't fall for OpenAI's interface: ChatGPT is not the kind of thing you can sensibly ask for information
https://t.co/GZIA8pNg8X
"We urge policymakers to instead draw on solid scholarship that investigates the harms and risks of AI—and the harms caused by delegating authority to automated systems" w/@alexhanna in @scientificamer
https://t.co/yhtrh8r7oG
Soo, ChatGPT, which is definitely not three stochastic parrots in a trench coat, is not only bad at coding but also really good at making people think that it's good at it.
https://t.co/uSjpha7Etz
We hope our work encourages skepticism for GPT as eval ground truth, and encourages folk to look a little deeper into preprint papers before sharing.
Much thanks to @NeilDeshmukh and @David_Koplow for working w/ me on this and @willwjack for the review.
https://t.co/mpDqlenk04
Pro tip: if a machine learned model scores 100% on something, the metric is wrong, or the evaluation dataset is not robust, or the evaluation dataset is in the training data, or a combination of all of the above. At least in this point in time.
Screen sharing with a student today:
S: "I don't understand this function.."
Me: "<Explains>...change line 11"
S: "<Starts typing...>
Copilot: "<Offers suggestion, no explanation>"
S: "<Immediately accepts suggestion without reading, still doesn't understand, code is wrong>"