The problem we're seeing across many professions is AI output is not getting vetted by knowledgeable people, whether it's an experienced analyst, senior engineer, expert attorney, or the resident physician. At best they skim, at worst they don't even see it at all before it's published, pushed to production, distributed to clients, or submitted to the court.
In many cases the skills are available in house to do the necessary vetting, but these people are already overwhelmed with their existing day to day.
Anyone remember that item a few months back about Amazon now having senior engineers vet generative AI output (https://news.ycombinator.com/item?id=47323017)? I had to LOL when I read that. These folks are already slammed. And the idea that Amazon would allow human bottlenecks to multiply across projects and underlying infrastructure development is ridiculous.
Part of the problem: you get given a complete document to review after it's been fully baked.
I'm pushing the need for basic engineering principles across whole organisations.
You wouldn't give an engineer 1000 lines of code to review without the original spec of what you're trying to achieve for context (at a minimum, ideally the reviewer was in the room when the work was introduced, and has full context).
So, these docs, they're given as an all or nothing.
Do you push back on the 39th metric that is defined to the utmost detail? Or just resign yourself to the fact that it is what it is?
A one (6 is the goto if we're talking Amazon?!) pager.. "this is what I am proposing" at least gives the skeleton of the idea to push back at the general shape of the idea, refine it, before all the emotional investment of your precious report being complete.
Y'know.. the traditional product running through the spec in a SCRUM* environment.. the engineers doing proper code reviews..
> AI output is not getting vetted by knowledgeable people
You mean the people they fired and demoralized?
One of the things that "great [wo]men" like about "vibe-coding" (and that includes blindly producing non-code product), is that they, and they alone can now do what used to require the painful process of "passing it to context experts."
Now, the LLM is a "built-in context expert," and they don't need to vet the output anymore.
> Now, the LLM is a "built-in context expert," and they don't need to vet the output anymore.
Serious orgs are going to have to figure out the human layer. It will be needed, no matter how 'hallucination-free' the AI tooling gets. AI will still have some spectacularly bad fuck ups or even worse time bombs that get embedded in a system and don't become apparent until months or years later.
A lot of this will be dumped on existing staff with predictable results as they don't have the bandwidth to do it right. I can envision "output compliance" or "AI QA" becoming dedicated positions at many orgs. It's clearly needed.
As an attorney, I feel like vetting AI output takes longer than just doing it from scratch, let alone versus just using a traditional form.
With AI, I have to read through everything, often explain why it's wrong, and then rewrite everything anyways. I mean, I get way more billables, but I think it's symptomatic of how AI loses its advantage of being quick and accessible to those who don't understand the subject matter.
It's not really any different in programming. Like if you have a well structured code and want to do a clear refactoring across it and you know what to expect, it can speed things up. But if it's generating any significant (and relatively complex) new code, you have to go through the whole thing manually again and then you find out you have to fix way to many things and get bogged down in different paths the AI didn't do correctly.
Of course, it's pretty much impossible to hear a dissenting point of view today and everyone is going crazy on these drugs. I might be hilariously wrong but I think this is the best time to start a software company.
But wait, if knowledgeable people have to vet the output, the process will not be 10X faster and you will not be able to fire the knowledgeable people. Therefore, your objection makes no sense. QED.
Also wondering on this whole review process with someone who wrote it with AI. Even if you comment and noted all issues. Do they have skills or willingness to correctly correct it all? And how many times would you need to keep the loop going for error free outcome? Is there even enough calendar time for that?
> The problem we're seeing across many professions is AI output is not getting vetted by knowledgeable people, whether it's an experienced analyst, senior engineer, expert attorney, or the resident physician.
Yeah probably not for the same reason I left VFX rather than have a lifetime of completely disregarding my own generative creativity and cleaning up LLM-generated bullshit. Fuck that. Double-fuck creating ‘content’ to train the models.
In code, LLMs automate away a lot of the drudgery. I wasn’t sad to avoid spending a couple hours looking up the usage patterns and idioms for some ported library, or do some rote task that didn’t make the project significantly better. In most other jobs, they automate away the only fun part and leave humans with all of the drudgery.
The tech industry has always been arrogant to some extent, but assuming the world of talented professional knowledge workers and creatives would be content to professionally proofread, apply lipstick to pigs, and polish turds is a whole new level of out-of-touch. I’d rather live out of my car and dig through the garbage for bottles with deposits.
If the main job is putting out a report, starting with AI is wrong in any case. What's the value of an AI-generated report, even if experts fix the biggest issues with it? Maybe this kind of report didn't have all that much value before, I don't know. But starting with AI just makes sure it's generic drivel.
> In many cases the skills are available in house to do the necessary vetting, but these people are already overwhelmed with their existing day to day.
I think a lot of the time it's just pure laziness. AI gives people a magical "do all the work for me" button and it can bring out the worst in them.
I constantly battle this dichotomy where I care about the work I do but I also cannot possibly care about the corporate model, given 0 ownership of flawed processes across the org and the looming layoff that'll happen any day now.
Some people are given the button and really do not care.
The real comedy is seeing this garbage come down from senior management, clumsy prompting, hallucinated garbage that’s all fluff and zero actionable information, zero real informed analysis. “See this analysis of our support issues from jira, we must fix these top three problems!!!” And it’s all the stuff everyone has known for years but management has refused to give anyone the authority to fix anything. I’ve seen this more than twice now; needs a name. Garbagemaxxing?
Off topic but: the scroll mechanism on mobile is so horribly irritating and unpredictable that I just can’t be bothered fighting against it to read what sounds like at least a mildly interesting article.
On mobile, It’s hijacking my scroll in such a way that I literally cannot move further down the page. And “reader mode” is only showing me the first paragraph or so.
I’ll have to try again later on desktop. The content looks interesting but it’s literally impossible to read. I cannot get past the section that introduces Ernst and Young.
On desktop it keeps adding forced pauses to scrolling, of varying sizes, and you need to scroll down a between 1 and 10 pages worth to begin scrolling again.
It might "work" just fine on mobile (or not) but you may have stopped trying before reaching the point of re-scrolling, because it's insane.
I eventually managed to get far enough into the article that I thought I saw the main stat - the stat that 26% of the citations were hallucinated. Then the scroll threw me back to the top again and I gave up entirely on reading from my phone.
Coming back later on desktop, I see that the percentage keeps climbing the further you manage to make it down the page. The real stat is 60% of the citations were hallucinated.
I did some ghost writing for EY. I wrote cheat sheets about international tax transfer pricing, mining and metals, and life sciences for its then CEO Mark Weinberger.
I had no experience and knew absolutely zero about any of those sectors.
What’s strange about how things have developed is that this report 12-18 months ago would have been a massive scandal and would have caused durable brand damage.
This sort of thing is a complete embarrassment to a firm like EY, where people are paying them a lot of money for advice. They’ve basically demonstrated that their market leading research is just someone asking questions to ChatGPT.
If you ever needed evidence to not buy “advice” from such outfits, this is exhibit one.
Hopefully they at least fired the partner that published this steaming pile of AI slop.
The Big Four have become a shadow of their former selves. They have become so risk averse that their advice is already incredibly generic and non-actionable.
I think their audit work is in a downwards spiral. Audit has become so competitive that they are struggling to find ways to make it cheaper. They have become slaves to reducing the hours booked, and the rate of those hours. To do this they substitute less experienced people all the time. You used to be able to chat with your partner about an issue you have coming up, now you get their assistant if you are lucky. By chasing 'efficiency' they have lost their value-add. Now the first time the partner has looked at your file is right before the clearance meeting, and they spot issues that should have been picked up earlier and tested on the day you should be signing. So you end up doing it all again. I'm trying to coin a term for the inneficiency caused by chasing efficiency.
I worked at a top 5 hedge fund in the early 2000s. They had a large team of E&Y auditors onsite at all times that I worked somewhat closely with.
Some things stuck out at me:
- They were all in their early 20s.
- They were all incredibly checked out. Honestly they still seem like an outlier to me decades later.
- They partied hard. Yes, with drugs.
- Most of them were in rotating intimate relationships with each other and unusually open about it. Office scuttlebutt was literally "who is fucking who this week".
- They seemed busy for maybe two or three weeks out of the entire year and then it was long stretches of Minesweeper/Solitaire.
I filed this away in my head as "provides no value" and that was decades ago. If the industry itself is worse off today I can't imagine how much worse it actually is from my experience.
Executives pay them a lot of money to launder blame. If a project fails after consulting EY, well, what can you do. If a project fails without consulting anyone externally, it's obviously a failure of the executive.
Exactly--they're paid a lot of money for their reputation, which is valuable in offering cover for politically difficult decisions. This was certainly net-negative for E&Y's reputation.
I guess this is a great report, but the parallax landing page shenanigans disrupt my reading flow, you cannot easily scroll back to get a overview of the key facts, so I stopped.
I don't quite get it why they can't take another LLM and vet the output of the first with the second one. Surely they would not have the same hallucinations and would be able to detect hallucinations of the earlier LLM. Maybe it would cost too much in terms of tokens?
I don't know but I would expect it to be realtively easy for an LLM to detect "hallucinations".
> I don't quite get it why they can't take another LLM and vet the output of the first with the second one.
Yes, this technique and its variations[1][2] "work" but it's still not 100% perfect. And it's not as widely used it might be because, among other reason:
a. it takes longer to implement
b. it costs more (more tokens spread across multiple llm calls)
c. higher latency (getting an answer takes longer due to multiple llm calls involved)
d. the final answer is probabilistically more likely to be correct, but is still not guaranteed to be error free, so you can never fully escape the need for Human in the Loop.
>I don't quite get it why they can't take another LLM and vet the output of the first with the seond one.
I think this may be part of the problem. The actual humans creating the report don't have the expertise to know which one to trust. At least that was what consulting was like in my experience at a similar firm.
Because they used LLMs to do the work. What you are suggesting is to use the LLMs to create more work, which is counter to the shortcut they were trying to take.
Good point with some irony. Thye don't want to do a better job they want to do an easier job. But a company like E&Y should realize shortcuts like these don't work. And their customers are paying them.
I wish we could just stop destroying people's jobs and lives using AI. The statistics I have heard quoted say, that merely 25% of the people actually like their job. Meaning they like doing what they do for its own sake, not because it gets them money, which they desperately need to live. I get it, most people don't want to do the work. But can we stop ruining the jobs of people, who are actually dedicated to their job and would like to keep doing their job properly?
But I guess since EY is a CYA hedge anyway, no one really cares about whether the reports are hallucinations or not. Someone high up spent money on EY, so that they can justify some decision and won't be held responsible that much, when it turns out the decision was shit. All that matters to them is, that it has the appearance of something genuine and then they can base the decision on what they receive from EY, which better be what they already wanted to hear/read anyway.
I don't quite get it why they can't take another LLM and vet the output of the first with the second one. Surely they would not have the same hallucinations and would be able to detect hallucinations of the earlier LLM. Maybe it would cost too much in terms of tokens?
I don't know but I would expect it to be relatively easy for an LLM to detect "hallucinations".
This proves (again) one think for sure: The "Big x" Consulting Firms were always BS - and now them generating all their work themselves using LLMs just profs that their 'clients' can just skip their Million Dollar fees and just ask the LLM directly.
Basically the entire consulting industry should die due to AI.
Performative executives of yesteryear that constantly need external validation and direction and operate through hive mind and groupthink are weak and will die.
I believe some of the biggest problems in today's business leaders are an inability to be open to new information, to think across traditional professional boundaries, or to ask meaningful questions.
AI simply exposes this unapologetically.
Bad management (this includes most government): up your game or get out of the way.
In many cases the skills are available in house to do the necessary vetting, but these people are already overwhelmed with their existing day to day.
Anyone remember that item a few months back about Amazon now having senior engineers vet generative AI output (https://news.ycombinator.com/item?id=47323017)? I had to LOL when I read that. These folks are already slammed. And the idea that Amazon would allow human bottlenecks to multiply across projects and underlying infrastructure development is ridiculous.
I'm pushing the need for basic engineering principles across whole organisations.
You wouldn't give an engineer 1000 lines of code to review without the original spec of what you're trying to achieve for context (at a minimum, ideally the reviewer was in the room when the work was introduced, and has full context).
So, these docs, they're given as an all or nothing.
Do you push back on the 39th metric that is defined to the utmost detail? Or just resign yourself to the fact that it is what it is?
A one (6 is the goto if we're talking Amazon?!) pager.. "this is what I am proposing" at least gives the skeleton of the idea to push back at the general shape of the idea, refine it, before all the emotional investment of your precious report being complete.
Y'know.. the traditional product running through the spec in a SCRUM* environment.. the engineers doing proper code reviews..
* Yes SCRUM is dead, but that's another thing.
Not fully baked, worse: made to sound confidently correct, orthogonally its actual correctness.
You mean the people they fired and demoralized?
One of the things that "great [wo]men" like about "vibe-coding" (and that includes blindly producing non-code product), is that they, and they alone can now do what used to require the painful process of "passing it to context experts."
Now, the LLM is a "built-in context expert," and they don't need to vet the output anymore.
Serious orgs are going to have to figure out the human layer. It will be needed, no matter how 'hallucination-free' the AI tooling gets. AI will still have some spectacularly bad fuck ups or even worse time bombs that get embedded in a system and don't become apparent until months or years later.
A lot of this will be dumped on existing staff with predictable results as they don't have the bandwidth to do it right. I can envision "output compliance" or "AI QA" becoming dedicated positions at many orgs. It's clearly needed.
The problem is that output sometimes take longer to verify than to create in the first place.
That turns AI into a deeply negative ROI system for many applications.
With AI, I have to read through everything, often explain why it's wrong, and then rewrite everything anyways. I mean, I get way more billables, but I think it's symptomatic of how AI loses its advantage of being quick and accessible to those who don't understand the subject matter.
Of course, it's pretty much impossible to hear a dissenting point of view today and everyone is going crazy on these drugs. I might be hilariously wrong but I think this is the best time to start a software company.
I do the second approach for coding with smallish steps and the output is fine
I can’t cite “from scratch” for something outside of my knowledge but I side LLM training or assisted search.
Yeah probably not for the same reason I left VFX rather than have a lifetime of completely disregarding my own generative creativity and cleaning up LLM-generated bullshit. Fuck that. Double-fuck creating ‘content’ to train the models.
In code, LLMs automate away a lot of the drudgery. I wasn’t sad to avoid spending a couple hours looking up the usage patterns and idioms for some ported library, or do some rote task that didn’t make the project significantly better. In most other jobs, they automate away the only fun part and leave humans with all of the drudgery.
The tech industry has always been arrogant to some extent, but assuming the world of talented professional knowledge workers and creatives would be content to professionally proofread, apply lipstick to pigs, and polish turds is a whole new level of out-of-touch. I’d rather live out of my car and dig through the garbage for bottles with deposits.
Why?
So if they're having humans proofread what the AI produces, they must have found that to be necessary.
I think a lot of the time it's just pure laziness. AI gives people a magical "do all the work for me" button and it can bring out the worst in them.
Some people are given the button and really do not care.
I’ll have to try again later on desktop. The content looks interesting but it’s literally impossible to read. I cannot get past the section that introduces Ernst and Young.
It might "work" just fine on mobile (or not) but you may have stopped trying before reaching the point of re-scrolling, because it's insane.
Coming back later on desktop, I see that the percentage keeps climbing the further you manage to make it down the page. The real stat is 60% of the citations were hallucinated.
Some people should not be allowed to make a website.
I had no experience and knew absolutely zero about any of those sectors.
Now nobody will remember or notice.
It's unsurprising that trying to do more with less results in lower quality.
There may be a lot of demand for do-nothing services.
A lot of corporate work is just do-nothing box-ticking.
Boss: get me a report about X, so I can give that report to my boss who won't read it.
You: E&Y, please get me a report. Here's $200k.
If you ever needed evidence to not buy “advice” from such outfits, this is exhibit one.
Hopefully they at least fired the partner that published this steaming pile of AI slop.
I think their audit work is in a downwards spiral. Audit has become so competitive that they are struggling to find ways to make it cheaper. They have become slaves to reducing the hours booked, and the rate of those hours. To do this they substitute less experienced people all the time. You used to be able to chat with your partner about an issue you have coming up, now you get their assistant if you are lucky. By chasing 'efficiency' they have lost their value-add. Now the first time the partner has looked at your file is right before the clearance meeting, and they spot issues that should have been picked up earlier and tested on the day you should be signing. So you end up doing it all again. I'm trying to coin a term for the inneficiency caused by chasing efficiency.
"don't let the perfect be the enemy of the good" ?
Some things stuck out at me: - They were all in their early 20s. - They were all incredibly checked out. Honestly they still seem like an outlier to me decades later. - They partied hard. Yes, with drugs. - Most of them were in rotating intimate relationships with each other and unusually open about it. Office scuttlebutt was literally "who is fucking who this week". - They seemed busy for maybe two or three weeks out of the entire year and then it was long stretches of Minesweeper/Solitaire.
I filed this away in my head as "provides no value" and that was decades ago. If the industry itself is worse off today I can't imagine how much worse it actually is from my experience.
Penny wise, pound foolish? Measure twice cut once?
I don't know but I would expect it to be realtively easy for an LLM to detect "hallucinations".
Yes, this technique and its variations[1][2] "work" but it's still not 100% perfect. And it's not as widely used it might be because, among other reason:
a. it takes longer to implement
b. it costs more (more tokens spread across multiple llm calls)
c. higher latency (getting an answer takes longer due to multiple llm calls involved)
d. the final answer is probabilistically more likely to be correct, but is still not guaranteed to be error free, so you can never fully escape the need for Human in the Loop.
[1]: https://en.wikipedia.org/wiki/LLM-as-a-Judge
[2]: https://github.com/karpathy/llm-council
I think this may be part of the problem. The actual humans creating the report don't have the expertise to know which one to trust. At least that was what consulting was like in my experience at a similar firm.
But I guess since EY is a CYA hedge anyway, no one really cares about whether the reports are hallucinations or not. Someone high up spent money on EY, so that they can justify some decision and won't be held responsible that much, when it turns out the decision was shit. All that matters to them is, that it has the appearance of something genuine and then they can base the decision on what they receive from EY, which better be what they already wanted to hear/read anyway.
I don't know but I would expect it to be relatively easy for an LLM to detect "hallucinations".
Performative executives of yesteryear that constantly need external validation and direction and operate through hive mind and groupthink are weak and will die.
I believe some of the biggest problems in today's business leaders are an inability to be open to new information, to think across traditional professional boundaries, or to ask meaningful questions.
AI simply exposes this unapologetically.
Bad management (this includes most government): up your game or get out of the way.
Sycophantic consultant firms: die.
The Economist should do an article on this.
~ A greedy, dishonest and unethical capitalist.