Whenever one of these stories come up, there's always a lot of discussion about whether these suits are reasonable or fair or whether it's really legally the companies' fault and so on. If that's your inclination, I propose that you consider it from the other side: Big companies use every tool in their arsenal to get what they want, regardless of whether it's right or fair or good. If we want to take them on, we have to do the same. We call it a justice system, but in reality it's just a fight over who gets to wield the state's monopoly of violence to coerce other people into doing what they want, and any notions of justice or fairness are window dressing. That's how power actually works. It doesn't care about good faith vs bad faith arguments, and we can't limit ourselves to only using our institutions within their veneer of rule of law when taking on powerful, exclusively self-interested, and completely antisocial institutions with no such scruples.
Software has more than its fair share of acronyms, which we often choose to say phonetically, like SQL gets said "sequel." We also have the TTY, and you often have to detach things from it. Depending on the context, best to spell that one out, or just substitute "terminal," but I've definitely been in meetings where someone said something about a process that needs to be detached from the titty.
You can't use an LLM this way in the real world. It's not possible to make an LLM trade stocks by itself. Real human beings need to be involved. Stock brokers have to do mandatory regulatory trainings, and get licenses and fill out forms, and incorporate businesses, and get insurance, and do a bunch of human shit. There is no code you could write that would get ChatGPT liability insurance. All that is just the stock trading -- we haven't even discussed how an LLM would receive insider trading tips on its own. How would that even happen?
If you were to do this in the real world, you'd need a human being to set up a ton of stuff. That person is responsible for making sure it follows the rules, just like they are for any other computer system.
On top of that, you don't need to do this research to understand that you should not let LLMs make decisions like this. You wouldn't even let low-level employees make decisions like this! Like I said, we know how LLMs work, and that's enough. For example, you don't need to do an experiment to decide if flipping coins is a good way to determine whether or not you should give someone healthcare, because the coin-flipping mechanism is well understood, and the mechanism by which it works is not suitable to healthcare decisions. LLMs are more complicated than coin flips, but we still understand the underlying mechanism well enough to know that this isn't a proper use for it.
That is only true if you use capitalist metrics to measure poverty
(1) It is unlikely that 90% of the human population lived in extreme poverty prior to the 19th century. Historically, unskilled urban labourers in all regions tended to have wages high enough to support a family of four above the poverty line by working 250 days or 12 months a year, except during periods of severe social dislocation, such as famines, wars, and institutionalized dispossession – particularly under colonialism. (2) The rise of capitalism caused a dramatic deterioration of human welfare. In all regions studied here, incorporation into the capitalist world-system was associated with a decline in wages to below subsistence, a deterioration in human stature, and an upturn in premature mortality. In parts of South Asia, sub-Saharan Africa, and Latin America, key welfare metrics have still not recovered. (3) Where progress has occurred, significant improvements in human welfare began several centuries after the rise of capitalism.
One of the gas stations near me started putting ads on their pumps, so I started carrying around blank paper and painters' tape to make a little cover for it, that way you can flip it up to pay, and then flip it back down to fill in peace. This screen, though, is exclusively for ads, so, theoretically, one could just smash the screen, and it will only be improved. Theoretically, that is.
Meanwhile my 1951 tractor still runs strong. I'm a big right to repair guy (lord knows I've repaired that thing a million times) and I celebrate the victory, but these laws are a tiny step in our profit-driven, disposable world. Repairability and longevity need to be fundamental design considerations. We'll never get there with ticky tack regulations on a world where modern tractor manufacturers go out of their way to install computers on their tractor specifically so you can't repair it yourself.
No, I am saying it is overused, not oversimplified.
Oversimplification on its own is usually one of the weakest critiques of a model, because the point of any model is to simplify. For example, reducing the entirety of the sun and the Earth and everything in or on them as two point masses in an empty space is a ridiculous, almost offensive oversimplification, but it's really useful for understanding our orbit. It's an insufficient critique to say this model of our galaxy is oversimplified, because it obviously has utility. Often, the best theories or models are really simple. When we have really good, simple models, we often call them things like "elegant."
Mental health, as a model, is actually extremely complex. You can spend a lifetime getting advanced degrees in that field and you'd probably barely scratch its surface. I wouldn't dream of calling it an oversimplification. If anything, I'd say you're more likely to find a fruitful critique going in the other direction.
Ya that's a fundamental misunderstanding of percentages. For an analogous situation with which we're all more intuitively familiar, a self driving car that is 99.9% accurate in detecting obstacles crashes into one in one thousand people and/or things. That sucks.
Also, most importantly, LLMs are incapable of collaboration, something very important in any complex human endeavor but difficult to measures, and therefore undervalued by our inane, metrics-driven business culture. Chatgpt won't develop meaningful, mutually beneficial relationships with its colleagues, who can ask each other for their thoughts when they don't understand something. It'll just spout bullshit when it's wrong, not because it doesn't know, but because it has no concept of knowing at all.
I developed something like this, so maybe I can answer. It was a browser extension that let people bypass the old twitter login wall. It had many thousands of users until Twitter started walling themselves off this summer.
I was inspired to make it in the most American way possible -- someone I know was in a school that got locked down due to a shooter threat (ended up being a false alarm). The police and news agencies were live-tweeting the updates, and their partner didn't have a twitter and couldn't read them without making a fucking account that very moment, wondering if their partner was even alive. I directed them to nitter, but they're not very into tech, and replacing the URL was just intimidating for them at the moment.
I found the whole experience so grotesque that that very evening I made an extension that lets you press a button to dismiss the login modal and keep scrolling (just a few css changes, or about 30 lines of code).
My two cents: Though I don't personally use it, the fact is Twitter does have a lot of valuable stuff on it. Same goes for other large platforms -- google results are now worthless without adding "reddit" to the search, for example. These companies are bad, but there's so, so many things to care about, and people can't care about all of them. Tactically, that makes consumer-driven change very difficult.
I'm not sure what kind of organizing we need to start doing to take back the internet from these big platforms, but whatever it is, I think it has to reckon with our past mistake of giving a few companies ownership of most of the internet, which means it has to go beyond just stopping to use them. These few platforms have the last 10 years of the internet currently walled-off, and they plan on charging rent on that forever. That's shitty. We should try to stop them from doing that, if we can.
All these always do the same thing.
From the OP , buried deep in the methodology :
Yet here's their conclusion :
It's literally always the same. They reduce a task such that chatgpt can do it then report that it can do to in the headline, with the caveats buried way later in the text.