Artificial intelligence is worse than humans in every way at summarising documents and might actually create additional work for people, a government trial of the technology has found.
Amazon conducted the test earlier this year for Australia’s corporate regulator the Securities and Investments Commission (ASIC) using submissions made to an inquiry. The outcome of the trial was revealed in an answer to a questions on notice at the Senate select committee on adopting artificial intelligence.
The test involved testing generative AI models before selecting one to ingest five submissions from a parliamentary inquiry into audit and consultancy firms. The most promising model, Meta’s open source model Llama2-70B, was prompted to summarise the submissions with a focus on ASIC mentions, recommendations, references to more regulation, and to include the page references and context.
Ten ASIC staff, of varying levels of seniority, were also given the same task with similar prompts. Then, a group of reviewers blindly assessed the summaries produced by both humans and AI for coherency, length, ASIC references, regulation references and for identifying recommendations. They were unaware that this exercise involved AI at all.
These reviewers overwhelmingly found that the human summaries beat out their AI competitors on every criteria and on every submission, scoring an 81% on an internal rubric compared with the machine’s 47%.
My guess ist that even if it would be better when it comes to generic text, most of the texts which really mean something have a lot of context around them which a model will know nothing about and thus will not know what is important to the people working with this topic and what is not.
From my experience that was the case. However it was with gpt 3, and I am a sample of 1.
Artificial intelligence is worse than humans in every way at summarizing documents
In every way? How about speed? The goal is to save human time so if AI is faster and the summary is good enough, then it is a success. I guarantee it is faster. Much faster.
A summary is useless if it’s not accurate.
If you make enough mistakes, speed is a detriment not a benefit. Increasing speed allows you to produce more summaries but if you still need to correct and edit them all you’ve done is add a step where a human has to still read the document to the level where they could summarize it and edit the AI summary. Therefore the bottleneck of a human reading the document and working on a summary is still there. It would only potentially make it slightly easier if the corrections needed are small and obvious.
47% is a fail. 81% is an A-… Sure the AI can fail faster than a human can succeed, but I can fail to run a marathon faster than an athlete can succeed.
I guess by the standards we use to judge AI I’m a marathon runner!
I’d heard that Canada gives out As down into the 80% range but I thought I was being fed a line
Yeah 0- 49% is an F 50-59 is a D 60-69 is a C 70-79 is a B 80-89 is an A 90-100 is an A+
It means that 10-20% of exams and assignments can be used to really challenge students without unfairly affecting grades of those who meet curriculum expectations.
If I want to get a better sense of lemmy than headlines, that 47% success at summarizing all the posts is good enough and much faster than I can even skim
If I want to code a new program, that 47% is probably pretty solid at structure and boilerplate so good enough. It can save me a lot of time
If I want to summarize the statuses of my entire team, that 47% may be sufficient for a Slack update to keep everyone up to speed but not enough to send to management
If I’m writing my thesis, that 47% is abject failure
If you miss key information the summary is useless.
If the structure of the code is bad then using that boilerplate will harm your ability to maintain the code FOREVER.
There are use cases for it, but it has to be used by someone who understands the task and knows the outcome they’re looking for. It can’t replace any measure of skill just yet, but it behaves as if it can which is hazardous.
No shit.
Intelligence vs non intelligence: intelligence is superior… Who would have thunk it lol
Here is the summary by AI
The article suggests AI is worse than humans at summarizing documents, based on one outdated trial. But really, Crikey is just feeling threatened. AI is evolving fast, and its ability to handle vast amounts of data without the human biases Crikey often exhibits is undeniable. While they nitpick AI’s limitations, they ignore how much better it will get—probably even better than their reporters. Maybe they’re just jealous that AI could do in seconds what takes humans hours!
Artificial intelligence is worse than humans in every way
As if capitalists have ever cared about that…
I would expect “faster” to be a way
“I can easily do it on my phone” is also good.
or cheaper
This reminds me. What happened to that tldr bot? I did appreciate the summaries, even if they weren’t perfect.
Well, not every metric. I bet the computers generated them way faster, lol. :P
Right? That’s the entire point.
And for a much much smaller paycheck.
All corporate gives af about.
It might be all I care about. Humans might always be better, but AI only has to be good enough at something to be valuable.
For example, summarizing an article might be incredibly low stakes (I’m feeling a bit curious today), or incredibly high stakes (I’m preparing a legal defense), depending on the context. An AI is sufficient for one use but not the other.
Sometimes I am preparing a high stakes communication for work and struggling for brevity. I will ask AI for help reducing my word count and I find it is helpful as an impartial editor. I take its 25% reduction, sigh, accept most of what it sacrificed, fix a word or two, and am done. It’s helpful.
I mean, what you’re essentially implying is, what if we could do a lot of things that we do today, but faster and less quality.
Imo we have too much things today and very few are worth their salt, so this is the opposite of the right direction.
That’s not what I’m implying. What I’m saying is that wasting time and effort on quality is pointless when the threshold for success is low.
For example, I could use aerospace quality parts (perfectly machined to micron-level tolerances) to build a toaster. However, while this would not increase the performance meaningfully, the cost would be orders of magnitude greater. Instead I can use shitty off-the-shelf parts because it doesn’t really make a difference.
Maybe in other words, engineering tolerances apply to LLMs too. They’re crude devices, but it’s totally fine if you have a crude problem.
That’s not what I’m implying. What I’m saying is that wasting time and effort on quality is pointless when the threshold for success is low.
Yes and my response to that is for some people maybe, for others they don’t want a low threshold, they want few good articles instead of spam of low quality.
Maybe in other words, engineering tolerances apply to LLMs too. They’re crude devices, but it’s totally fine if you have a crude problem.
Exactly, I’m saying there is no objective crude problem. You might be okay with simple summaries but I want every single piece of information I consume to have a very high bar.
Sure, go for it. But good luck paying an army of copywriters to summarize every article you read.
No summery is better than a bad summery, it would encourage you to actually read the source.
What if you’re reading Lemmy, and you don’t really feel like reading the article. Is the headline likely to tell you all you need to know or is the ai summary likely to find more info and without the clickbait?
Imo it’s on me to either read the article or be okay with not being informed. Don’t get me wrong, a summery is good, but not when it’s not reliable and the article is a click away, some might have a different comfort level.
Part of the time.
And you can absolutely trust that tons of executives will definitely not understand this distinction and will use AI even in areas where it’s actively harmful.
They’ll use it until it blows up in their faces and then they will all backtrack. Executives are like startled cattle.
Let’s not act like executives are the only morons in this world. Plenty of rank and file are leaning on AI as well.
This is a really valid point, especially because it’s not only faster but dramatically cheaper.
The thing is, summaries which are pretty terrible might be costly. If decision makers are relying on these summaries and they’re inaccurate, then the consequences might be immeasurable.
Suppose you’re considering 2 cars, one is very cheap but on one random day per month it just won’t start, the other is 5x the price but will work every day. If you really need the car to get to work, then the one that randomly doesn’t start might be worse than no car at all.
Are we sure it’s cheaper though? I mean it legitimatly might not be. I have some friends who work in tech and they use an AI model for, amongst other things, summarizing information on their internal documentation. They’ve told me what their company is paying for the license to use this thing, and it’s eyewatering. also, uhh last time I checked, the company they got that license from does not turn a profit… so it appears to be too cheap at the moment.
It might really be the case that it isn’t cheaper than just paying someone a normal salary to do that work, and it probably isn’t cheaper than just jamming the work being done by the AI now back onto preexisting employees (which is what they did before ~2 years ago anyway).
The other thing that makes me feel this might not be unreasonable is that everyone on the team likes the tool, except their manager, who has thrown out the idea to cut it twice now (that I know of).
I’ve been curious about this too, but haven’t been able to find anything that puts a real price (including future profit margin) on GenAI. For example, having a chat conversation with a customer service agent in India might cost about $2-3. Is a GenAI bot truly cheaper than that once you factor in the energy & water costs, hardware, training, profits, etc.? It might be, but I’m skeptical.
“Just one more training on a social network”
Can’t wait for the bouble to burst.
We shouldn’t wait, it is already basically illegal to sample the works of others so we should just pull the plug now.
The issue with legally pulling the plug is that it won’t stop AI baddies, only good AI companies who respect the law.
The knowledge and tools are still out there.
But when the bouble bursts it will tank AI globally.
good AI companies who respect the law
When those come around maybe we can rethink our stance, but for now we should stop the AI baddies.
Which will only be possible with good old fashioned bouble bursting as I said.
Nah we can start enforcing the laws as they exist. OpenAI is using works of others commercially without permission.
We don’t have to wait.
As I noted, that only works with a limited set of AI companies.
They need to be in the juristiction of whatever government that decide to enforce the laws, if not, there is very little that can be done.
Then, besides needing to be in the right juristiction, the punnishment needs to be large enough that you can’t just budget it away.
Then any country doing this will know that they are deliberately getting rid of an important sector, while other countries will continue running their sectors.
Important? Unlikely.
This is an old study, they tested University level adults against the standard Llama2-70B.
Kinda absolete now, the model has completely fallen out of use, for the newer and far better 3 and 3.1 Versions. It also wasnt fine tuned for summarization, and while base L2-70B was OK, it wasnt great at anything without fine tuning.
This clickbait title also sounds like self gratification, the abysmal reading comprehension in the Internet is directly counter to it. The average human found on the Internet doesnt approch the level of literary capabilities, that those ten human testers showed in the study.
To all of you AI haters out there, stay away from the two minute papers yt channel. You’ll get very sad at the actual state of AI.
Also beware the AI Explained channel, where the creator is full-time investigating and evaluating cutting edge development in AI. You might even glimpse what’s coming.
The most promising model, Meta’s open source model Llama2-70B, was prompted to summarise the submissions
Llama 2 is insanely outdated and significantly worse than Llama3.1, so this article doesn’t mean much.
You didn’t bother to Read the article. Read the article. Study was conducted last year
I read the article. I’m aware it’s an older study. Point still stands.
And yet your claim is still pointless unlike this study
This is pretty much every study right now as things accelerate. Even just six months can be a dramatic difference in capabilities.
For example, Meta’s 3-405B has one of the leading situational awarenesses of current models, but isn’t present at all to the same degree in 2-70B or even 3-70B.
Did LLama3.1 solve the hallucination problem?
I bet we would have heard if it had, since It’s the albatross hanging on the neck of this entire technology.
Just a few more tens of millions of dollars, and it’ll be vastly improved to “pathetic” and “insipid”.
On July 18, 2023, in partnership with Microsoft, Meta announced Llama 2 On April 18, 2024, Meta released Llama-3
L2 it’s one year old. A study like that takes time. What is your point? I bet if they would do it with L3 and the result came back similar, you would say L3 is „insanely outdaded“ as well?
Can you confirm that you think with L3, the result would look completely opposite and the summaries of the AI would always beat the human summaries? Because it sounds like you are implying that.
Can you confirm that you think with L3, the result would look completely opposite and the summaries of the AI would always beat the human summaries? Because it sounds like you are implying that.
Lemmy users try not to make a strawman argument (impossible challenge)
No, that’s not what I said, and not even close to what I was implying. If Llama 2 scored a 47% then 3.1 would score significantly better, easily over 60% at least. No doubt humans can be better at summarizing but A) It needs someone that’s very familiar with the work and has great English skills and B) It needs a lot of time and effort.
The claim was never that AI can summarize better than people, it was that it can do it in 10 seconds and the result would be “good enough”. People are already doing AI summaries of longer articles without much complaints.
Lemmy users try not to make a strawman argument (impossible challenge)
This was not a strawman. Please don’t assume lemmy users make logical fallacies when it’s only you who thinks that.
I guess you missed the part where he said “Oh you said X but you’re actually implying Y? Did you mean Y? Please confirm you actually meant Y.”
That’s my point, from my perspective, there was no switch. Using a one year old model is fine.
My comment was about how people looking at the same thing, one might think it’s a bait and switch while the other one always knew the second item was being implied.
The headline never said all AI or latest AI.
We know the performance of L2-70b to be on par with L3-8b, just to put the difference in perspective. Surely they models continue to improve and we can only hope the same improvements will be found in L4, but I think the point is that models have improved dramatically since this study was run and they have put in way more attention in the fine-tuning and alignment phase of training, specifically for these kinds of tasks. Not saying this means the models would beat the human summaries everytime (very likely not), but at the very least the disparity between them wouldn’t be nearly as large. Ultimately, human summaries will always be “ground truth”, so it’s hard to see how models will beat humans, but they can get close.
Not a stock market person or anything at all … but NVIDIA’s stock has been oscillating since July and has been falling for about a 2 weeks (see Yahoo finance).
What are the chances that this is the investors getting cold feet about the AI hype? There were open reports from some major banks/investors about a month or so ago raising questions about the business models (right?). I’ve seen a business/analysis report on AI, despite trying to trumpet it, actually contain data on growing uncertainties about its capability from those actually trying to implement, deploy and us it.
I’d wager that the situation right now is full a lot of tension with plenty of conflicting opinions from different groups of people, almost none of which actually knowing much about generative-AI/LLMs and all having different and competing stakes and interests.
What are the chances that this is the investors getting cold feet about the AI hype?
Investors have proven over and over they’re credulous idiots who understand sweet fuck-all about technology and will throw money at whatever’s in their face. Creepy Sam and the Microshits will trot out some more useless garbage and prize a few more billion out of the market in just a little while.
“What are the chances…”
Approximately 100%.
That doesn’t mean that the slide will absolutely continue. There may be some fresh injection of hype that will push investor confidence back up, but right now the wind is definitely going out of the sails.
The core issue, as the Goldman - Sachs report notes, is that AI is currently being valued as a trillion dollar industry, but it has not remotely demonstrated the ability to solve a trillion dollar problem.
No one selling AI tools is able to demonstrate with confidence that they can be made reliable enough, or cheap enough, to truly replace the human element, and without that they will only ever be fun curiosities.
And that “cheap enough” part is critical. It is not only that GenAI is deeply unreliable, but also that it costs a truly staggering amount of money to operate (OpenAI are burning something like $10 billion a year). What’s the point in replacing an employee you pay $10 an hour to handle customer service issues with a bot that costs $5 for every reply it generates?
Yeah we are on the precipice of a massive bubble about to burst because, like the dot com bubble magic promises are being made by and to people who don’t understand the tech as if it is some magic that will net incredible profits just by pursuing it. LLMs have great applications in specific things, but they are being thrown in every direction to see where they will stick and the magic payoff will come
The problem is that even the specific things they’re good at, they don’t do well enough to justify spending actual money on. And when I say “actual money”, I’m not talking about the hilariously discounted prices AI companies are offering in an effort to capture an audience.
A bot that can do a job reasonably well, but still needs a human to check their work is, from an employment perspective, still an employee, just now with some very expensive helper software. And because of the inherent unreliability of LLMs, a problem that many top figures in the industry are finally admitting may never be solved, they will always need a human to check their work. And that human has to be competent enough to do the job without the AI, in order to figure out where and how it went wrong.
GenAI was supposed to put us all out of work, and maybe one day it will, but the current state of the technology isn’t remotely close to being good enough to do that. It turns out that while bots can very effectively look and sound like humans, they’re not remotely capable of thinking like humans, and that actually matters when your chatbot starts promising customers discounts that don’t actually exist, to name one real example. What was treated as being the last ten percent is actually looking more and more like ninety-nine percent of the work in terms of creating something that can effectively replace a human being.
(As an aside, I can’t help but feel that a big part of this epic faceplant arises from Silicon Valley fully ingesting the bullshit notion of “unskilled labour”. Turns out working the drive thru at McDonald’s is a more complicated job than people think, including McDonald’s themselves. We’ve so undervalued the skills of vast swathes of our population that we were easily deluded into thinking they could all be replaced by simple machines. While some of those tasks certainly can, and will, be automated, there are some human elements - especially in conflict resolution - that are really hard to replace)
Yea, the “cheaper than droids” line in Andor feels strangely prescient ATM.
NVIDIA has been having a lot of problems with their 13th/14th gen CPU’s degrading. They are also embroiled in an anti-trust investigation. That coupled with the “growing pains of generative AI” has caused them a lot of problems where 2 months ago they were one of the world’s most valuable companies.
Some of it is likely the die-off of the AI hype but their problems are farther reaching than the sudden AI boom.
Thanks!
Are we talking 10% worse and 95% cheaper? Or 50% worse and 10% cheaper? Or 90% worse and 95% cheaper?
Because that last one is good enough for fiscal conservatives. Hell, the second one is good enough for fiscal conservatives.
The linked pdf lists the deficiencies of the LLM responses. They are varied and it sometimes misses the mark completely or cant grasp vital context.
Still pretty useless comparison, they testet 10 university level humans against Llama2-70B. The model has fallen out of use completely by now and was never really great at summarization. The study didnt fine tune it either, so this isnt really representative of the current situation.
There are far better models out, that were either especially trained for summarization or can be easily fine tuned to excel at it. Not to mention the Llama3 and 3.1 series, with the crazy 405B model.
There are far better models out
I’ve heard this refrain a few times. Still waiting for it to pan out.
The next update will fix everything, just need this one hotfix and everything will be solved, just wait.
Just one more update, okay? Just one more. One update. Just one.
Knowing this it seems like a very low quality study. They should probably redo this with multiple conditions.
- Base Llama 3
- Tuned Llama 3
- Untrained human summarizer
- trained/professional human summarizer
