alt Hacker NewsThe kids who used AI and studied for a similar amount of time as the non-AI high performers apparently had similar (slightly higher) performance. The kids who used AI and did poorly used the AI to do the homework for them (this is what the article says).
I believe AI is basically an amplifier of bad and good. I’m cynical about the world and assume it will be used more for bad than good, but I don’t doubt some of the best people in every field will be using AI to amplify their work in good ways.
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The scary thing is that 81% of AI users in this study were determined to be "outsourcing" their homework to the LLMs - and the rate increases the more exposure they had to LLMs.
The "slightly higher" performance is based on statistically insignificant samples (between 4 and 20 students, depending on the context, out of the total population of 26,000): https://bsky.app/profile/benjaminjriley.bsky.social/post/3mt...
This is kind of damning, isn't it? "Similar or slightly higher" for spending the _same time_ means it's not, in fact, helping. At the same time as being extremely damaging to a significant number of students who, of course, use the AI to cheat. Because everything about it makes cheating easy.
> I believe AI is basically an amplifier of bad and good.
Same can be said of technology in general tbh.
You aren’t being cynical, you’re arguing with disingenuous entities with money on the line. We already know it’s used primarily for the negative case. Everyone who ever intended High School or College knows this.
It's a familiar story. If you copy/paste Wikipedia and turn it in, you learn nothing. If you skim Wikipedia, hit up the references, the consult other sources, then synthesize your own thought, you probably get farther faster than you would without it.
We could probably cook up thousands of examples of the same problem (YouTube DIY tutorials, GPS navigation, etc.)
The dangerous thing about amplifying is that bad people are often more willing to amplify their activities, because they don't care about the negative effects. We are seeing this now as AI companies (and large companies of all kinds) rush to secure whatever advantages they can, regardless of the negative externalities. Meanwhile people who actually care about doing the right thing get trampled.
We need to shift the incentives by adding ruinous penalties for things that are currently quite commonplace if they are done by large players. Some dude training his own AI on his own computer can scrape and train. The fine for OpenAI or Meta using a single copyrighted book without permission should be in the tens or hundreds of millions.
What we're seeing currently in our society is a "loophole inversion" where the rules have an effect mainly via their loopholes. The most profitable activity is to find loopholes and exploit them as frenetically as possible to gain as much advantage as you can before the loophole is closed, or get people hooked on the loophole so it's retroactively legalized. Entities that are big enough to do this are big enough because they have lots of money behind them. Entities doing the same kinds of things without lots of money are not really doing much harm. So the best approach is to adopt a "sliding scale" in which even tiny violations by wealthy actors result in penalties enormously greater than fairly large violations by small players.
This is my thoughts as well! It makes smarter people smarter and dumb people dumber!
It's not so clear that AI is an amplifier.. The paper has some fascinating analysis on this topic:
"At the other end of the distribution, AI students who spend more than 65 minutes on their homework receive homework and exam scores similar to those of non-AI students, suggesting that these students do not use generative AI for homework assignments. However, this group consists entirely of students who adopted generative AI no more than Öve months. Six months after adoption, no AI student spends more than 65 minutes completing their homework (see Figure A5). This is consistent with the gradual process of learning how to use AI tools. It also suggests that AI crowds out the highest level of e§ort."
"Interestingly, in the range of 50-65 minutes, the median and the interquartile range of exam scores of AI and non-AI students are similar. This implies that, in the range where AI students and non-AI students have overlapping homework times, students who spend the same amount of time completing homework on average receive similar exam scores."
"This pattern shows that students who spend the same amount of time on homework learn similarly, with or without generative AI. In other words, generative AI reduces time spent learning for the majority of AI students but not learning efficiency for those who spend the same time studying as the non-AI students."