21–30 of 364 posts
Perhaps ML could be applied here to help filter out the barrage of AI snake oil. Funding, anyone?
“For predicting social outcomes, AI is not substantially better than manual scoring using just a few features”
Suggests that only a simple heuristic is needed: if the AI salesman claims their product predicts a social outcome, like a candidate’s job performance or a person’s future criminality, it is snake oil.
self-censored, fanboys don't buy it
Not to indulge the troll, but Arvind Narayanan is an (associate) professor of CS at Princeton and is one of the foremost researchers in the field on topics of ML/data privacy and ethics [0]. His papers/talks/tweets regularly attract attention on HN [1]. That you're judging the talk based on which conferences the author hasn't published in says more about your ignorance of the STS field than it does about the author's…
Earlier quoted context omitted.
Any type of heuristic search = AI. hand-made decision tree or lookup table = AI, Naive bayes = AI, KNN = AI. Uses numpy = AI. One employee in mobile app startup has graduate thesis in ML = AI startup. Approximate string matching in SQL query = AI. Not clear what the product is going to be = AI. "Information is not knowledge. Knowledge is not wisdom. Wisdom is not truth. Truth is not beauty. Beauty is not blockchain.…
In my space (cybersecurity) I’ve heard “more than 2 joins” (in an SQL context) is ML.
self-censored, fanboys don't buy it
Not to indulge the troll, but Arvind Narayanan is an (associate) professor of CS at Princeton and is one of the foremost researchers in the field on topics of ML/data privacy and ethics [0]. His papers/talks/tweets regularly attract attention on HN [1]. That you're judging the talk based on which conferences the author hasn't published in says more about your ignorance of the STS field than it does about the author's…
My company is sourcing AI from MTurk. It's actually cheaper than running fat GPU model training instances. The network learns fast and adapts well to changes in inputs. I envision the sticker "human inside" strapped on our algorithms.
You should emphasize that this is Organic AI. It's low carbon and overall greener.
These things better be smart, because they are not low-footprint.
The "tl;dr" is basically that more features is not necessarily a panacea and can actually cause more problems.
My company is sourcing AI from MTurk. It's actually cheaper than running fat GPU model training instances. The network learns fast and adapts well to changes in inputs. I envision the sticker "human inside" strapped on our algorithms.
Given the number of people Facebook employees to censor content and the mistakes they make I would label most of Facebooks AI claims as snake oil.
It seems like at least half the tech people I talk to work with AI now... no matter their field.