Microsoft is bringing GPT-4 to US Government agencies
bloomberg.com
bloomberg.com
1. Lying about everything
2. Require human curation to procedure usable results, that will be biased because of that curation
3. Being extremely good at convincing people they should trust them
Gee, I wonder if there’s anything that can go wrong here, when it’s handed to unskilled, underpaid employees who don’t care and are used to just following instructions? And they start making decisions that affect peoples lives?
I can bet $100, that if that goes beyond any alpha test, we’ll have huge scandal in the future of how those models were purposely modified to influence government, that will make any social media scandal look like a child’s play.
EDIT: and I assume that there won’t be an information leakage - that’s the easiest problem to tackle, with separate infra that government clouds are reasonably good at.
Further, the narrative you paint suggests that no one in government is competent in anything and can only follow directions.
Finally, you combine the heavily biased perspectives you took and proposed that it would lead to a massive scandal in the government, but not just any scandal, one that is actually a coordinated attack BY MICROSOFT to screw the government, their largest customer.
Just interesting to see.
"I'm sorry sir, but the computer clearly says that you've been charged with sexual harassment - we cannot renew your driver's license and we're putting you on the sexual offenders list, please report to your local PD weekly." (completely made up and exaggerated, but I'm sure one can think of similar scenarios) [1] Good luck convincing the clerk that that's not real. You can probably get it corrected after months of your time and $$.
[1] https://www.washingtonpost.com/technology/2023/04/05/chatgpt...
[1] https://www.nytimes.com/2010/01/14/nyregion/14watchlist.html
There are 340 million people in the US. The US has one of the largest government systems that humanity is likely to ever see. How many similar cases of children being put on the terrorist watch list have there been in the past 20 years? Unless there are a lot of cases of that happening, if it's not rare (hint: it's extraordinarily rare; your example story is from 13 years ago), your premise is pure straw.
[0]: https://www.wired.com/story/face-recognition-software-led-to... [1]: https://www.theguardian.com/us-news/2023/apr/27/california-p...
>(completely made up and exaggerated, but I'm sure one can think of similar scenarios)
How about "I'm sorry sir, but the computer clearly says that you've been at the site of murder and thus killed this guy. Even though all other direct evidence contradicts this, we're gonna have to arrest you. "[1]
The best part of working on projects that used that data set in Google was learning about it from articles like this one.
[1]https://www.dailymail.co.uk/news/article-7897319/Police-arre...
We are holding it to a higher standard because this is going to be used by agencies with serious power over people's lives. It is not just to spit out, for example, a form rejection letter from a credit card.
And, nobody thinks that Microsoft wants to "screw" the government. But if something happens, the impact can be magnified significantly considering the reach and power of the state. I'm all for moving forward quickly with this tech, but there are a handful of spaces (government, medicine, aeronautics) where we need to be extremely deliberate.
The vast majority of government workers are underpaid apathetic cogs in a machine who do not fit this bill.
We just saw a LAWYER use hallucinated information in his practice. A lawyer who is ostensibly rigorously trained and tested in his field.
The amount of misuse of GPT by way of sheer ignorance alone by the government will be astounding.
I'm from the north-middle, sometimes I'm surprised how little people on the west coast of America think of the people on the east coast.
Above All, The NSA knows their shit. 44B+, Autonomy and Mathematicians Proves it above all, regardless of Morals.
Don't attack them on knowledge. You have to use a different approach to climb Everest.
I would only put the Mossad, KGB and <insert name of the chinese SIGINT agency> on their level.
I feel for my kids, and all I can do is warn them...
https://theconversation.com/excel-errors-the-uk-government-h...
But hey, I guess all those dumb dumbs at NASA can’t tie their shoelaces.
When talking about the pitfalls of bringing GPT-4 as a tool for government officials, the positive features are outside of the scope.
Obviously they exist, otherwise it wouldn't be proposed. But it's not our job to do a sales pitch for GPT-4.
>Further, the narrative you paint suggests that no one in government is competent in anything and can only follow directions.
No. The OP suggests that the primary users of the tool would be low-level, underpaid officials, who are mostly following directions.
Not because it's their fault as human beings - but because their positions require them to do so, and perhaps for good reasons.
In any case, direction-followers (of questionable competence and low pay grade) make up the bulk of large organizations in general as a consequence of growth. Which is why the tool is being pitched in the first place: to streamline work of people who would rather not do it in the first place.
>Finally, you combine the heavily biased perspectives you took and proposed that it would lead to a massive scandal in the government, b
As if the governments aren't prone to massive scandals even without GPT-4 in place. Try checking the news today, you may be surprised.
>not just any scandal, one that is actually a coordinated attack BY MICROSOFT to screw the government, their largest customer.
"By Microsoft" wasn't in OP's statement. Manipulating data and statistics to get the desired outcome from seemingly impartial algorithms is something our government has been engaging in for a very, very long time.
Redlining[1] and gerrymandering[2] are just two prime examples.
We don't have to make any assumptions or apply biased perspectives to say that we expect:
1)Training data to be manipulated by entities with interest in influencing the outcome;
2)Lives of countless people being adversely affected, and
3)There being a massive scandal as a result.
The government has a long track history of 1, 2, and 3 happening any time a system is introduced which lacks transparency, and large language models are the epitome of that.
The only unrealistic thing about OP's statement is that a scandal will actually happen, instead of people getting away with it.
>It's always interesting to see how people engage with new technologies on HN.
And it is even more interesting to see how people here engage with ethics.
[1]https://www.nytimes.com/2021/08/17/realestate/what-is-redlin...
[2]https://www.brennancenter.org/our-work/research-reports/gerr...
Just communicate more clearly, you're clearly displeased and want to say something more?
(edit) how many people do you think are aware of LLM hallucinations as opposed to inaccurate google results
Why? Any who understands about Google or Wikipedia can understand about LLM.
Also the problem isn't necessarily about understanding the tech, but more about how it will be perceived at first. As long as every big player hypes up the tech as if it's perfect and revolutionary, I can't blame people for blindly trusting it at first(because it might as well work for most things they use it for, it will take some time before the pitfalls become apparent).
If someone blindly trusts and uses an LLM without checking for more evidence, then they would've done the same with any other source, be it Google, the newspaper or whatever.
"In a cringe-inducing court hearing, a lawyer who relied on A.I. to craft a motion full of made-up case law said he “did not comprehend” that the chat bot could lead him astray." [1]
[1] https://www.nytimes.com/2023/06/08/nyregion/lawyer-chatgpt-s...
LLMs will be involved in complex tool chains like everything else.
I agree there's cause for concern, and I hope it's a gradual rollout that's introspected in between each propagation of such, but I definitely think it's viable to be used no more less safely than other tooling in the government today (for better or worse).
https://digitalreadymarketing.com/wp-content/uploads/2014/08...
https://www.nytimes.com/2021/02/18/opinion/fake-news-media-a...
> 1. Lying about everything
> 2. Require human curation to procedure usable results, that will be biased because of that curation
> 3. Being extremely good at convincing people they should trust them
Finally, we automate politics!
It could also be used manipulate people:
- engage with people in online forums to stir their opinion
- making it seem the consensus is different with many posts
It could also be used affect people's freedom of movement:
- By analyzing someones social media posts, ChatGPT could say someone is a: "dangerous individual" which could be used to deny US entry or provide a justification to be constantly monitored.
It could also affect people's privacy:
- Doxxing people on reddit and other social media
- Identifying account belonging to a group or the same individual based on writing patterns, subreddits visited, etc...
Also scientific articles being constant don't quite matter when the "status quo" of science is asymmetrically understood.
There are doctors today still pushing the "fat is unhealthy" myth because of the sugar industry. Despite the ubiquity of modern unbiased research papers and proof.
But when you ask a doctor for advice, you're essentially getting the wetware equivalent of a stochastic parrot, because this random doctor is giving you dynamic answers coming from his/her own completely non-standardized corpus of knowledge.
When was the last time you tried to make a wiki edit on a popular page?
LLMs, in my opinion, are on average better at writing copy than humans. Or rather they manage to do so more consistently. Thus, even if humans still need to provide supervision, the clarity and conciseness of government documents may be improved overall.
For example right now we have AIs writing CVs and cover letters that are read by AIs, we're "optimizing" things that shouldn't exist anymore but we're too deep in the cycle to even notice it
Ability to interpret/summarize is limited by context size and time.
Document dumping is the social DoS.
The best way to get people to interact with you a certain way is to reward them for interacting with you that way, and you likely don't. Not because that's a failure of you but it's just how people (all of us) act.
The world isn't a co-operative multi-tasking OS. We're more like the human body: a multi-agent conglomerate whose component organisms communicate via signals that are filtered and processed. Sometimes a pathogen mimics signals well enough. Other times we detect it. But the system wouldn't work if every participant trusted the counterparty.
Some communication is intended to inform, some is intended to persuade... And often, the speaker doesn't even really know which they are dealing with.
So now you have 2 machines talking to each other in text-to-speech English over audio, then having to do speech-to-text on each others audio streams, and then natural language processing to understand the message etc.
When all we needed instead was a simple API endpoint over the internet for the business where a machine could talk to the other machine with just a few bytes of information to convey the same information and process the same transaction.
Instead we are wasting bandwidth and tons of cpu cycles and electricity making the machines emulate a human analog conversation.
Maybe in the not so distant future, the AI agents can have a shibboleth which cuts the human gobbledygook short, and reverts to speaking in dialup tones.
Incidentally, this makes a fine tuned version perfect for the government, which produces a shit load of low-effort documents, but today employs a bunch of morons to write them.
If you want a lot of text that you don't want to think about, LLMs are great. If you want text that is pithy or persuasive, it doesn't help much, even when you use prompting tricks (eg "you are a CEO/professor..."). By the way, this has convinced me that local LLAMA-scale models are the future, not massive remote GPTs.
I appreciate the rest of your post though and I think you make a great point about AI being very effective for certain types of work
Some of them could be in the beginning part of their government career attending school. Did you run a survey to ask these people what they do with their lives?
> If you want a lot of text that you don't want to think about, LLMs are great. If you want text that is pithy or persuasive, it doesn't help much, even when you use prompting tricks (eg "you are a CEO/professor..."). By the way, this has convinced me that local LLAMA-scale models are the future, not massive remote GPTs.
Granted, we are judging LLMs based on highly generalized training sets. What if a GPT was fine-tuned on all of the writing and speeches of figures whom are considered the most persuasive?
Government reports continue to balloon in size, because of technological advancements (especially copy/paste).
In the age of typewriters, anything not important, or duplicate, was cut. With word processors, document sizes unnecessarily grew.
All things considered, an awkward sentence or two isn't really that much of a big deal compared to an incorrect assertion that was missed in review.
I also don't think GPT-4 is necessarily that brilliant at writing copy, but I don't really know how good/bad US government officials are so I can't really compare, but in other parts of the world I haven't really that much of an issue with it.
I disagree here.
But what I found LLMs really useful for is summarizing topics like: "Suppose I want to do XYZ, which steps should I take?" or "I want to write about ABC, how would you structure the article?"
The content is not very good if you look at it in detail, but LLMs provide good overviews and gave me ideas on parts of a topic I overlooked.
More librarian than search engine. I cannot copy and paste and rely on the results but I can rely on that they point me in a good direction.
> More librarian than search engine. I cannot copy and paste and rely on the results but I can rely on that they point me in a good direction.
The same can be said of physical books, and most content should be written more like that in books than what the internet is currently selecting for.
A disturbingly high proportion of US adults (at least in the US—I don't know how this looks in other countries) barely count as literate. Perhaps half[1]. Most of the rest aren't a ton better, and can't write worth a damn.
I think "on average" understates the case: at least 90% of US adults would probably get better results by passing their writing through ChatGPT, than not. Most of that remaining 10% would also see improvements from ChatGPT, except for writing they've put a great deal of effort into. It's very good at cleaning up writing, and/or tuning it to be better-suited to some purpose than the original was.
In fact, a large majority of readers in the US would probably benefit from passing what they read through ChatGPT and having it summarize it concisely, in very simple terms.
The world makes a lot more sense, to those who grew up taking to the written word as naturally as a duck to water, when we appreciate that the world runs on the written word, yet most people are terrible readers and worse writers.
[1] "According to a 2020 report by the U.S. Department of Education, 54% of adults in the United States have prose literacy below the 6th-grade level." And, nb, if you're a good reader and you're thinking "6th grade level, that's not so bad", your idea of what a "6th-grade level" looks like, is probably skewed way higher than what they mean.
To continue the entirety of the quote which makes it not seem quite as dammning:
"Literacy in the United States was categorized by the National Center for Education Statistics into different literacy levels, with 92% of American adults having at least "Level 1" literacy in 2019.[1] According to a 2020 report by the U.S. Department of Education, 54% of adults in the United States have prose literacy below the 6th-grade level.[2]
In many nations, the ability to read a simple sentence suffices as literacy, and was the previous standard for the U.S. The definition of literacy has changed greatly; the term is presently defined as the ability to use printed and written information to function in society, to achieve one's goals, and to develop one's knowledge and potential.[3]"
Bullet list -> AI text generator -> AI text summarizer -> Bullet list
Perhaps OpenAI can optimize the process by storing the original prompt and just giving it back at the last phase.
this is quite saddening.
IIRC the high-school-graduate equivalent adult literacy rate from similar studies—as in, possessing reading skills that we hope a high school graduate would have, which basically equates to being able to read two moderate-length, moderate-complexity texts and understand them well enough to synthesize a description of their positions, and how they agree and differ—isn't much more than 20%. Four out of five people you encounter are going through life constantly struggling to understand WTF is happening or what they're supposed to do and getting by on a lot of guesswork, while all continually mis-communicating with one another. Really explains a lot.
For the boilerplate- well sure, but I could do that with existing tools, no AI needed. Custom communications I'm sure AI can handle the very basics. but once a human replies and consideration is needed for special cases- can you imagine ChatGPT counseling you on a healthcare decision? I can't.
I can't imagine ChatGPT doing much more than being an autoattendant until a human can reply fully, except the message humans can send to the agency will be customized and drafted according to a standard intake process.
The question is, do you want an AI writing the brief and doing the research that is going to be given to an administrator who is going to decide if you are denied medical care in an emergency?
I'd expect writing samples to get shorter, not longer, when being improved.
> 2. Require human curation to procedure usable results, that will be biased because of that curation
> 3. Being extremely good at convincing people they should trust them
You just described politicians
If that came from an organic brain we would call that clear intent.
I would however stop stick with “lying requires agency,” even if the model evaluation is crafted to be deceitful. The intent and the agency lies with the prompt creator, and therefore, IMO, the lie starts and ends there.
From experience, this is sort of lazily libeling a broad cross-section of public servants. The public sector has no monopoly on useless employees, you'll find them in equal if not greater numbers in the private sector.
There are plenty of very highly skilled people in government who are quite passionate about serving the public good. The one thing you're correct on is that they're underpaid, and we're fortunate that they're passionate enough about public service and aren't focused on salary-maxing. They're stuck in a system that's managed by the whims and grandstanding of politicians, and attacked as 'the deep state' by people who want to take us back to the spoils system where every public employee is a crony.
If you think it's frustrating dealing with Google/YouTube arbitrarily and capriciously and erroneously and mercilessly shutting down your account and providing zero explanation and zero accountability and zero helpful customer service...
Now imagine that for crucial government services. If there is a flag or datapoint in your government data, then that's that. Too bad. Can't help you. That's what the computer is telling me.
This happens on a daily basis right now, for any number of human or computer errors.
Now insert a hallucinating ML model that only a subset of the population truly know how to use in small doses for productivity, and expect the GOVERNMENT to utilize it in a non-erroneous way?
This is what I'm talking about. Saying "the GOVERNMENT" is a ridiculously broad stroke, it's like saying "the INTERNET" (which, ironically, was brought to us by a particularly smart group of people working for the government).
> Now insert a hallucinating ML model that only a subset of the population truly know how to use in small doses for productivity
What's special about the tech elite that makes them any better at using these hallucinating ML models? The government includes vast numbers of specialists and researchers, and many of them are a lot smarter than we are. Government doesn't consist entirely of DMV employees.
This is a pretty shitty assessment of places like DTIC, DoE, and NASA. Maybe there's another analysis that doesn't involve web forum commenters being the only wizards who can control the magic?
Since when are Government employees underpaid? The salary is typically competitive for the work being done and the benefits/pension are outrageously generous when compared to the private sector.
If you disagree, take a look at govt SWE jobs postings.
There has to be some way to explain a pay discrepancy if it exists. How does one justify receiving a lower salary for the same amount of skill and work?
I suspect (admittedly without evidence) that someone in the NSA or Marines are not primarily driven by a paycheck. Maybe that's what you mean by "true believers"?
You might need to define what you mean by "outrageously generous". I've worked in multiple public and private roles and, in general, the private ones were the ones with much more generous packages, in terms of pay and benefits.
This worldview would also mean that blue-collar employees in the government are more skilled than their private sector counterparts, no?
4. Having no legal accountability
(while arguably providing a means of avoiding or reducing accountability for those using them, "LLM says no" style.)
> unskilled, underpaid employees who don’t care
One of these things is not like the others. The models may not ask for a raise but they’ll no doubt go to work finding all sorts of other excuses to raise taxes.
So humans?
Most of the "AI" fears, including the ones you picked out, are also prevalent in people. Therefore, I don't see the problem.
Humans have been inventing and using tools to increase the scale and efficiency of the means of production since time immemorial. "AI" is nothing new.
>removal of accountability?
Not holding the makers of "AI" models and users of "AI" accountable has nothing to do with "AI" itself. "AI" is just a tool like a hoe or a kitchen knife or a gun, accountability lies with whoever made and/or uses it.
Every new technology initially has its own shortcut comings.
Steve jobs in his inaugural iPhone launch, used four different phones because each phone was capable of only one feature.
2. Require human curation to procedure usable results, that will be biased because of that curation
3. Being extremely good at convincing people they should trust them ```
So it's absolutely perfect for the US government.
It’s worse than that. Employees of the US government are definitely not underpaid, especially when you consider
What the hell was I thinking that I couldn't finish?
One immediate internal benefit would be the information retrieval bit - you kind of get rid of the "data" barrier, which involves knowledge in databases/SQL etc.
Gov. agencies typically have lots of bureaucrats with deep domain knowledge in laws, regulations, and whatever the field they're working on - but limited data knowledge. And instead of relying on analysts etc. to retrieve the needed information, these LLMs could bypass that step.
Of course, it's not entirely that straight forward - as you'd need to validate the things the LLM serves you, but that's one of the ideas. Leadership have been discussing AI/ML non-stop for the past 6-7 months, and it seems like these kinds of FOMO projects are popping up everywhere...good times for the consulting firms.
If so, I think that makes sense. With the /major/ caveat that you are also making it even easier to get incorrect data out. No?
1) Some worker is fed up with having to sift through hundreds of excel spreadsheets in order to find the information need, and the nightmare of keeping such spreadsheets updated
2) Said worker deploys a small database - just for their own use. After some time the DB gets more users, who make their own views and what not. The database and tables within may or may not follow some rules. Heck, maybe the worker that created it was learning as they went on.
3) Said worker quits or gets a new job, and the database is essentially unmanaged. Some other worker might not now about that DB, and you go back to step 1)
Now multiply a database like that with 100, and span it over 20 year. You get this unimaginable spaghetti monster of multiple DBs, some written in one dialect, some in others. Some are completely unnormalized, others a high degree of normalization.
And to build a report, you may need to access tables from numerous such databases. Even seasoned analysts dread starting on the reports, because they'll spend a good day just to find the right dbs, tables, and all the errors.
So of course when the directors hear about this new fangled AI magic that just spits out the results when you ask it it plain English, they immediately order a use/benefit analysis on it.
Ok, so that may be a bit harsh - but that's the reality of many agencies. Dogshit DB management, and being 20 year behind the digitalization revolution.
But yes, a problem would of course be: How do you know that the data the LLM returns is true? Is it conjuring up fake data? Does it process/calculate data as you want it to?
But I'm hoping LLM-generated code (R in my case) can let me stay "in the flow" when exploring. I can spot-check generated code pretty quickly, but finding data, reading their docs, then finding packages to do what I want takes time. I'll often forget why I asked the question in the first place. For example, "How many children lived within 50 miles downstream of X in 2015 and were diagnosed with Y?" I can imagine how the finished code would look, but writing it myself means brushing up on the diagnosis records, two or three GIS datasets, and a GIS package. If we had a nice database or warehouse, this wouldn't be terrible.
I don't fear for my job. The coffee would be generated by including snippets of previous analyses in prompts, and guess who wrote those snippets? My role will become less coding, and more reaching out to policymakers and nonprofits to help them answer questions. I'll tell them what data we do have, what's reliable, and what kind of statistics can answer their questions. At least, that's my dream.
I can confirm the giant FOMO happening, and LLMs projects are popping up everywhere.
Good news is, the "talk-to-your data" use case you're describing is not the only one that can deliver amazing new tools! There's the "explain-me this", "summarize that", and "next-best-action" use cases that shows great promise!
In that case, I would recommend a search engine (i.e. Lucene, Elastic, Solr, or other) that holds the agency's 'knowledge' before I'd try feeding all of that into an AI such as GPT-4. Granted there are a lot of ML tools that can be statistically rigorous but GPT-4 is generative and therefore not providing access to original source material, which is troubling to reconcile with its potential use in any organization that needs to establish and maintain a ground truth.
And that is not as hard as retrieving that originally, how so then?
Also no "here we have a prototype never intended to be the real thing, now ship it"-mentality there? Oh, certainly not, it is a non overloaded government agency :D
> And that is not as hard as retrieving that originally, how so then?
Not necessarily. With good prompts GPT-4 is decently good at citation of exact sentences in the source. And there could be a separate system that verifies that citation text matches the real text for being safe.
This is what we’re doing with LLMs at my job and it works quite well. Essentially, the LLM generates a space of possible answers that are then validated with various procedural logic checks. The two strategies work well together, whereas either alone wouldn’t produce as good of results.
A package I open sourced recently might be useful for use cases like this, https://github.com/approximatelabs/datadm It's essentially a chatGPT code interpreter, specifically designed to work with data, that can be run entirely on open models (eg. StarChat). True local mode operation.
1. Information sensitivity. Even ignoring classified information, there are quite a few things we can't even put into a Google search. It's definitely a no-go for this to end up in a training dataset.
2. "Hallucinations"
Making LLM available through some infrastructure that is already approved for sensitive information will definitely help with the first point, and allow us to experiment with more areas where it might be helpful. I presume this would come along with guarantees about the interactions not being used for training.
It might be even better if some company would sell an appliance we could install on-prem with similar non-training guarantees. Then we could leverage these new tools for very sensitive information, which could be a great help.
> "Documents Sen shared with The Register said to be from the exposed server include a rich amount of data that certainly be valuable to a foreign adversary. It included all the usual PII, as well as blood type, religious affiliation, educational background, military service history and more, all in plain text. Sen told us that close to 3TB of data was available before the Azure server was taken offline on Monday."
Any any operation can make a huge mistake like that. E.g. the guy that leaked all those documents to discord.
I understand they want to protect their IP but I don’t think the model leaking will cost openai billions.
No. These new tools cannot provide leverage. They just produce a street pizza (1) based on the inputs they are given. Whether the street pizza is any good depends on the quality of the ingredients and how discerning the consumer is.
I think the worry about GPT-4 making things up is valid. We all know what happened to they lawyer who used GPT. But I think this comes with training. Users need to be trained to use it as tool and to verify the outputs. Now will everyone do this? No. There are lazy and incompetent people in every large organization and the govt is no different.
The concern about a LLM influencing or biasing its output is also a worry. Maybe there isn't a good solution to this one. I would say that having a govt group testing and assessing it would be best however they don't have the expertise form such a group which is the whole reason why they are leaning on companies like MS to guide their AI usage in the first place. I could also argue that this may not matter much anyway since the govt decisions are already heavily influenced by lobbyist and illegal promotion / favoritism of contractors.
Note that this probably does not affect US govt because from what I understand MS has a totally isolated dedicate Azure environment for US Govt entities.
[1] https://www.lastweekinaws.com/blog/azures_vulnerabilities_ar...
The government should demand open source code, open weights, and open research from any AI company it purchases services from.
Not the Skynet.
Government wages are already crap. How much crapier do you want them to get?
To hear that 6.4% of the GDP is spent on gov pensions is shocking to me.
That means that we are spending 6.4% of everything on just the pensions of 16.1% of the workers. If we did the same for all workers, we’d be spending 39.8% of the GDP just on pensions. That seems outrageous to me, but I’m not an economist. Why would it be that high?
This is inline with most advanced economies.
Of that ~6.4% - A LOT of that is healthcare related costs.
Considering that healthcare in the US is ~18.2% of GDP - and the vast majority of it comes from retirees - I don't know what you're expecting to see here.
Essentially, you're shocked that healthcare in the US is ~18.2% of GDP, and ~75% of that comes from retirees...
Social Security spending is ~5% of GDP, and Medicare spending is ~4% of GDP... That's for only ~19% of the population. And it doesn't even cover all of their healthcare costs.
If you keep the same ratio for government employees, that comes down to ~2.84% of GDP for healthcare & 3.56% for what most people think of as pensions...
And you're looking at ~65% of that spending coming from state & local governments, not the Federal government.
If pensions are considered part of the labor cost, that would mean not 25% of income going to retirement, but 66%! Or, if pensions are separate from labor, you’ve used up all 100% of the GDP, just between labor and pensions. Neither seems reasonable.
Furthermore, the US only spends 7.5% of the GDP on pensions all told.[0] If these numbers are equivalent, that means 85% of pension dollars are going to government workers.
Compare it to any other remotely advanced economy in the world, and you'll see it's not out of line.
Any problems that exist are mostly with local and state government pensions, not the federal government.
This is a bold assertion that I'll charitably entertain.
> Frequently better.
To further assert the government is frequently better demands evidence.
I explained the parent's comment to you, I didn't say this specific action would cause the end of civilization. And yes while we're at it the government using Microsoft Encarta or even Google to do research is also anti democratic, you'd want the government employees to use a non censored search engine instead of just seeing the snopes fact checked articles if they're going to base their life affecting decisions on it, and if Encarta had something like "the king of Gondor is a bad person" because some microsoft employee wrote it, and the CIA based their decision on that to assassinate him, then it'd be antidemocratic as well. I'll let you stare at the finger and miss the moon telling me how Gondor isn't real.
And what's sad is ChatGPT is really the best machine translator in existence. It's not hard to imagine it making a serviceable substitute for a translator, at least in principle, if uncensored.
I suspect Microsoft would do something similar, no data would leave government property.
Doesn’t AWS have a gov offering? I would assume MS can have similar offering with Azure using their express route.
More than that, they even have an air-gapped regions for more sensitive purposes, where you need not only to be a US citizen, but also a certain level of security clearance to access. As an (now ex-) AWS SDE working outside of the US, those regions were a pain in the ass to bring up your service in (as was govcloud, but that wasn't nearly as bad—at least there the ops guys could share logs and screenshots without having to work around an airgap)
The ops guys with direct access to those regions had to be on-site, as they only had access from a limited number of locations, and they were often severely understaffed. They were a pleasure to work with, but you could be waiting a day or more to find out your deployment had failed (the longest SLA I had to deal with in my time there was ~2 weeks due to some unfortunate vacation timings over the summer).
I can imagine alignment is probably an impediment to several areas of interest.
Nothing says "let's slow down and do this right" like giving that power over to the largest and most powerful government in the world.
I don’t really care other than I’d like to be able to ensure that my OpenAI library works on Azure.
Anyway, I guess those Government agencies will get the unsanitized version of GPT, not the politically corrected one.
This is what "technocracy" is, right? And "corporatism"?
hard to tell sometimes...