I disagree pretty strongly with the headline advice here. An ideal response would be to go through a typical sample of stories from some news source—for instance, I keep MIT Tech Review in my feedly because it has surprisingly useful predictive alpha if you invert all of its predictions. But that would take way more effort than I’m realistically going to invest right now, so absent that, I’ll just abstractly lay out where I think this post’s argument goes wrong.
The main thing most news tells me is what people are talking about, and what people are saying about it. Sadly, “what people are talking about” has very little correlation with what’s important, and “what people are saying about it” is overwhelmingly noise, even when true (which it often isn’t). In simulacrum terms, news is overwhelmingly a simulacrum 3 thing, and tells me very little about the underlying reality I’m actually interested in.
Sure, maybe there’s some useful stuff buried in the pile of junk, but why sift through it? I do not need to know a few days or weeks earlier that AIXI is being gutted. I do not need to know a few weeks earlier that the slowdown OpenAI found in pretraining scaling had been formally reported-upon. (Also David and I had already noticed the signs of OpenAI having noticed that slowdown back in May of 2024, though even if we hadn’t suspected until it was reported-upon in November, I still wouldn’t need to know about it a few weeks earlier.) Just waiting for Zvi to put it in his newsletter is more than enough.
MIT Tech Review doesn’t break much news. Try Techmeme.
Re “what people are talking about”
Sure, the news is biased toward topics people already think are important because you need readers to click etc etc. But you are people, so you might also think that at least some of those topics are important. Even if the overall news is mostly uncorrelated with your interests, you can filter aggressively.
Re “what they’re saying about it”
I think you have in mind articles that are mostly commentary, analysis, opinion. News in the sense I mean it here tells you about some event, action, deal, trend, etc that wasn’t previously public. News articles might also tell you what some experts are saying about it, but my recommendation is just to get the object-level scoop from the headline and move on.
Re is it worth the time of sifting through
Skimming headlines is fast. Maybe the news tends to be less action-relevant for your research, but I bet AI safety collectively wastes time and misses out on establishing expertise by being behind the news. Reading Zvi’s newsletter falls under what I’m advocating for (even though it’s mostly that what-people-are-saying commentary, the object-level news still comes through.)
I disagree pretty strongly with the headline advice here. An ideal response would be to go through a typical sample of stories from some news source—for instance, I keep MIT Tech Review in my feedly because it has surprisingly useful predictive alpha if you invert all of its predictions. But that would take way more effort than I’m realistically going to invest right now, so absent that, I’ll just abstractly lay out where I think this post’s argument goes wrong.
The main thing most news tells me is what people are talking about, and what people are saying about it. Sadly, “what people are talking about” has very little correlation with what’s important, and “what people are saying about it” is overwhelmingly noise, even when true (which it often isn’t). In simulacrum terms, news is overwhelmingly a simulacrum 3 thing, and tells me very little about the underlying reality I’m actually interested in.
Sure, maybe there’s some useful stuff buried in the pile of junk, but why sift through it? I do not need to know a few days or weeks earlier that AIXI is being gutted. I do not need to know a few weeks earlier that the slowdown OpenAI found in pretraining scaling had been formally reported-upon. (Also David and I had already noticed the signs of OpenAI having noticed that slowdown back in May of 2024, though even if we hadn’t suspected until it was reported-upon in November, I still wouldn’t need to know about it a few weeks earlier.) Just waiting for Zvi to put it in his newsletter is more than enough.
MIT Tech Review doesn’t break much news. Try Techmeme.
Re “what people are talking about”
Sure, the news is biased toward topics people already think are important because you need readers to click etc etc. But you are people, so you might also think that at least some of those topics are important. Even if the overall news is mostly uncorrelated with your interests, you can filter aggressively.
Re “what they’re saying about it”
I think you have in mind articles that are mostly commentary, analysis, opinion. News in the sense I mean it here tells you about some event, action, deal, trend, etc that wasn’t previously public. News articles might also tell you what some experts are saying about it, but my recommendation is just to get the object-level scoop from the headline and move on.
Re is it worth the time of sifting through
Skimming headlines is fast. Maybe the news tends to be less action-relevant for your research, but I bet AI safety collectively wastes time and misses out on establishing expertise by being behind the news. Reading Zvi’s newsletter falls under what I’m advocating for (even though it’s mostly that what-people-are-saying commentary, the object-level news still comes through.)