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AI worse than humans in every way at summarising information, government trial finds

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%.

kromem ,

Meanwhile, here’s an excerpt of a response from Claude Opus on me tasking it to evaluate intertextuality between the Gospel of Matthew and Thomas from the perspective of entropy reduction with redactional efforts due to human difficulty at randomness (this doesn’t exist in scholarship outside of a single Reddit comment I made years ago in /r/AcademicBiblical lacking specific details) on page 300 of a chat about completely different topics:

https://lemmy.world/pictrs/image/fcee2a67-c10d-4b37-9f3b-ea5018a06fdd.pnghttps://lemmy.world/pictrs/image/131edaa5-6a94-4f0b-8f7a-80d2c236a49a.pnghttps://lemmy.world/pictrs/image/e2a8f725-94ed-4683-8a53-fd1232f8a385.pnghttps://lemmy.world/pictrs/image/2c43a993-4cca-42ab-b8a9-8e3ddde35bca.png

Yeah, sure, humans would be so much better at this level of analysis within around 30 seconds. (It’s also worth noting that Claude 3 Opus doesn’t have the full context of the Gospel of Thomas accessible to it, so it needs to try to reason through entropic differences primarily based on records relating to intertextual overlaps that have been widely discussed in consensus literature and are thus accessible).

ArbitraryValue ,

The important thing here isn’t that the AI is worse than humans. It’s than the AI is worth comparing to humans. Humans stay the same while software can quickly improve by orders of magnitude.

SkyNTP ,

LLMs == AGI was and continues to be a massive lie perpetuated by tech companies and investors that people still have not woken up to.

maegul ,
@maegul@lemmy.ml avatar

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.

homesweethomeMrL ,

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.

Voroxpete ,

“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?

maegul ,
@maegul@lemmy.ml avatar

Yea, the “cheaper than droids” line in Andor feels strangely prescient ATM.

atrielienz , (edited )

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.

maegul ,
@maegul@lemmy.ml avatar

Thanks!

T00l_shed ,

From my experience that was the case. However it was with gpt 3, and I am a sample of 1.

testfactor ,

Well, not every metric. I bet the computers generated them way faster, lol. :P

Darkassassin07 ,
@Darkassassin07@lemmy.ca avatar

And for a much much smaller paycheck.

All corporate gives af about.

pennomi ,

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.

imPastaSyndrome ,

Part of the time.

jeena ,
@jeena@piefed.jeena.net avatar

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.

simple ,

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.

Gloria ,

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.

redscroll ,
@redscroll@lemmy.ml avatar

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.

homesweethomeMrL ,

Just a few more tens of millions of dollars, and it’ll be vastly improved to “pathetic” and “insipid”.

kromem ,

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.

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