Artificial Intelligence In Our Lives

[Analog Kid]

If anyone is in this thread complaining about AI is also in another thread complaining that Apple doesn't add features or fix bugs fast enough, it's worth stepping back and reconciling your belief systems.

 

[Luftkopf]

Excellent question.

If you mean productivity as unit output by unit time, yes definitely. I just finished the work that was piloted by a team of contractors for 6 months alone in 3 (that being said, the scenario was in the goldilocks of what was optimal for models to manipulate).

Nevertheless, it took some experimentation to get there and verification is still a real cost given that current systems still collapse under complexity.

Now to address the second part of your statement, assuming a new equilibrium where everyone has access to such tools and you are assuming similar ability to yours from your competitors. No inherent moat (lasting business advantage in a market) can be created from the use of the technology itself.

You either create a lasting business advantage from being enabled in a tertiary function from the systems or cutting overhead. Most leadership is not capable enough to successfully pivot to achieve the first, hence why we are seeing widespread overhead cut.

Unless we start seeing material advances in materials sciences from the technology (which has transformative effects in healthcare, construction and engineering that would unlock more than just automation. As in the dichotomy between automation and transformative change (which leads to a net benefit).

We just added ressource overhead for power centralization and surveillance with no obvious quantitative benefit to humans (That is in the mass of productivity added to society under the assumption that the work that was then done by a thread of human intelligence is now being done by a computational thread with a radically different consumption and externality profile).

The answers to those issues are political, IP attribution, externalities mitigation (Pollution, Displacement, Social Change, Climate Change).

Yet we have just shifted into an era where the political for the masses has become pantomime, hence the pessimism.

I'm not asking to be dismissive, I'm just curious. Which LLM do you use to refine your posts?

 

[Flowstates]

I'm not asking to be dismissive, I'm just curious. Which LLM do you use to refine your posts?

That's good ol me.

Although I will concede that the "Excellent Question" open feels icky, it would seem that I have started to absorb the sycophancy.

 

[turbineseaplane]

I mean, it is a little concerning to think about where this leads us..

Lawyers know AI can hallucinate. Judges have warned them. Courts have sanctioned them for it. They keep citing fake AI cases anyway.

The trend of attorneys getting caught citing AI-hallucinated cases points to a broader problem: instead of checking AI’s work, people keep trusting it

www.scientificamerican.com

 

[Luftkopf]

That's good ol me.

Although I will concede that the "Excellent Question" open feels icky, it would seem that I have started to absorb the sycophancy.

I guess it was bound to happen that people start writing in the style of LLM output. Now I don’t trust my own internal AI radar!

Thanks for answering my question. 🙂

 

[BSDnostalgia]

Excellent question.

If you mean productivity as unit output by unit time, yes definitely. I just finished the work that was piloted by a team of contractors for 6 months alone in 3 (that being said, the scenario was in the goldilocks of what was optimal for models to manipulate).

Nevertheless, it took some experimentation to get there and verification is still a real cost given that current systems still collapse under complexity.

Pardon my ignorance, but, I've never used AI for coding, and, I have no idea how this works in a real project.

In a "traditional" large software development process, normally, actually writing the code is anywhere from 50% down to as low as 10% of the total effort. Project work, defining and dividing the work, defining and refining interfaces, defining the verification tests functionally, (coding), code reviews, writing test code and setting up the verification tests, documenting, etc., are the other 50%-90%.

All we hear about is AI writing code, but, how much of the other stuff can AI do? It sounds like AI can do the "fun" 10% and leave people with the tough stuff-- tough, like, long meetings stuff. But, I guess, "vibe" coding obviates the need for meetings? Are there any actual "scientific" tests comparing the processes?

 

[turbineseaplane]

Maybe in the interests of "good business", among other benefits, we should use human employees?

 

[Mainsail]

Pardon my ignorance, but, I've never used AI for coding, and, I have no idea how this works in a real project.

In a "traditional" large software development process, normally, actually writing the code is anywhere from 50% down to as low as 10% of the total effort. Project work, defining and dividing the work, defining and refining interfaces, defining the verification tests functionally, (coding), code reviews, writing test code and setting up the verification tests, documenting, etc., are the other 50%-90%.

All we hear about is AI writing code, but, how much of the other stuff can AI do? It sounds like AI can do the "fun" 10% and leave people with the tough stuff-- tough, like, long meetings stuff. But, I guess, "vibe" coding obviates the need for meetings? Are there any actual "scientific" tests comparing the processes?

This is true of many white collar planning and analysis jobs. The up front work defining the goals and purpose and major assumptions are the most important and difficult part of the project. Most of my limited experience with AI has required that I feed that info into the model first before it generates much of anything useful. Granted, as a retired guy, my use is pretty limited, so maybe others have had other experiences .

 

[nnoble]

AI undoubtedly has the ability to improve our lives, even more so if it were better regulated. I am proud of the stand taken by mayor of London Sir Sadiq Khan against Palantir. We need AI but we do not want something that has the potential to be weaponised by hostile powers and dubiously led companies like Palantir.

 

[Flowstates]

Pardon my ignorance, but, I've never used AI for coding, and, I have no idea how this works in a real project.

In a "traditional" large software development process, normally, actually writing the code is anywhere from 50% down to as low as 10% of the total effort. Project work, defining and dividing the work, defining and refining interfaces, defining the verification tests functionally, (coding), code reviews, writing test code and setting up the verification tests, documenting, etc., are the other 50%-90%.

All we hear about is AI writing code, but, how much of the other stuff can AI do? It sounds like AI can do the "fun" 10% and leave people with the tough stuff-- tough, like, long meetings stuff. But, I guess, "vibe" coding obviates the need for meetings? Are there any actual "scientific" tests comparing the processes?

Echoing what has been said above, planning and requirements definition is still the lion's share of time spent.

The radical shift has been that AI has been handling the verification test definition, test code, verification test and documentation by itself.

We also rarely delegate tasks anymore and have a much higher ownership surface, what get's divvied up is high level ownership surface over a product / domain. Which I assume is the way successful orgs are going to restructure but bodes badly for low level (in the sense of reactive, not proactive) workers.

 

[Luftkopf]

Echoing what has been said above, planning and requirements definition is still the lion's share of time spent.

The radical shift has been that AI has been handling the verification test definition, test code, verification test and documentation by itself.

We also rarely delegate tasks anymore and have a much higher ownership surface, what get's divvied up is high level ownership surface over a product / domain. Which I assume is the way successful orgs are going to restructure but bodes badly for low level (in the sense of reactive, not proactive) workers.

It sounds like there won't be room for junior devs to come through any more. I think this is adding to the debt being built up. Things are going to be rough in ten years.

 

[Analog Kid]

It sounds like there won't be room for junior devs to come through any more.

I’ve seen studies that suggest there is less demand for junior devs, and “you need experience to get experience” isn’t something that started with the advent of AI. but I think it’s worth recognizing specifically what point @Flowstates is making:

low level (in the sense of reactive, not proactive)

The distinction being made is high level (big picture, lean forward, creative, willing to take risk and ownership) vs low level (transactional, small work batch, measure by lines of code written) personalities. This doesn’t directly map to junior versus senior. I’d argue there are some junior devs who have been held back by management that forces high functioning junior employees into low level roles. And senior employees have been lost early because they’re viewed as expensive per line of code.

What @Flowstates is correctly identifying, in my opinion, is that the nature of the gig is changing. This is going to mean junior employees are going to need different skills. I think the demand gap right now is because we aren’t training new grads with the right skills for this new era yet.

 

[Luftkopf]

I’ve seen studies that suggest there is less demand for junior devs, and “you need experience to get experience” isn’t something that started with the advent of AI. but I think it’s worth recognizing specifically what point @Flowstates is making:



The distinction being made is high level (big picture, lean forward, creative, willing to take risk and ownership) vs low level (transactional, small work batch, measure by lines of code written) personalities. This doesn’t directly map to junior versus senior. I’d argue there are some junior devs who have been held back by management that forces high functioning junior employees into low level roles. And senior employees have been lost early because they’re viewed as expensive per line of code.

What @Flowstates is correctly identifying, in my opinion, is that the nature of the gig is changing. This is going to mean junior employees are going to need different skills. I think the demand gap right now is because we aren’t training new grads with the right skills for this new era yet.

Either way, it's going to be disruptive, and we're all in for a lot of pain before things even out.

 

[throAU]

Sometimes, when I read all this, I get the feeling that people are listing the pros and cons
and passing judgment without even looking at what AI can actually do for people today !

Many people, even in industrialized nations, will hardly be able to use AI effectively because
the average person is unlikely to ask the right, detailed questions to get the (thoughtful)
answers that will help them move forward in life. So it won’t raise personal educational standards.

If people are thinking of AI as a basic chatbot and thinking "hurrr, it got the answer to this trivia question wrong! AI is dumb!" they're so far behind the reality of what is happening they may as well be living in the 1980s.

 

[throAU]

That's a good point, I've installed Linux (an Arch derivative ) and I've run into some issues, here and there. googling was fruitless, unless I wanted to watch a 20 minute video which may or may not help me. I got the exact steps from claude.

I've been experimenting with openclaw in a VM.

Its really interesting having the machine able to configure and diagnose itself by just talking to it.

Also interesting to get it to give me a daily briefing based on criteria I ask it to keep an eye on, on the internet.

I told it (Bob) to generate an email template in the style of the OpenClaw website as it saw fit.

 

[Analog Kid]

Either way, it's going to be disruptive, and we're all in for a lot of pain before things even out.

The people who think they can put their head in the sand and hope it goes away are in for the most pain.

 

[Luftkopf]

The people who think they can put their head in the sand and hope it goes away are in for the most pain.

Yes and no. Middle management should be scared, and people in IT need to start learning quickly, but there are a great number of fields in which AI is pointless.

AI isn't the messiah come to free us from drudgery. It's going to disrupt IT and management, and other information heavy roles, then it will settle down, but not before ruining the lives of many.

 

[Flowstates]

The distinction being made is high level (big picture, lean forward, creative, willing to take risk and ownership) vs low level (transactional, small work batch, measure by lines of code written) personalities. This doesn’t directly map to junior versus senior. I’d argue there are some junior devs who have been held back by management that forces high functioning junior employees into low level roles. And senior employees have been lost early because they’re viewed as expensive per line of code.

Exactly !

To whit, I'm not quite sure that the seniority might become the line on which employability might hinge. Juniors, unburdened by archaic processes and pre-ai scoping mentality might have a leg up.

Some orgs are already shedding senior layers in preference for junior headcount.

The experience premium in specialization along language lines has already all but dissolved. Whereas knowing what to build (that is having an embodied understanding the business context might become an enabler).

I do believe in a blurring of the lines between (PrM , TPM, SWE) but only for those that have an innate understanding of the new work requirements.

It's going to disrupt IT and management, and other information heavy roles, then it will settle down, but not before ruining the lives of many.

We (as in the market) are actively working to make all back office functions automated, and I do expect software engineers to fare much better than the telephone secretaries in re-skilling.

The layer of the infra on which the value will materialize seems to be unclear. Power seems to be a good candidate, HW is just bottlenecked, to see if the value remains once production catches up (see solar panels and china).

Models seems to be vulnerable to distillation and the gap between closed source and open source is closing fast (although the close source providers seem to want to sell you State of the Art as the absolute premium. Harnesses ... hard to know the prevailing paradigm has changed at least 5 times in the last 4 years.

Time will tell, but I am definitely keeping my savings rate much higher than before.

Good luck everyone, take time to enjoy your loved ones in turbulent times, community is the ressource.

 

[throAU]

Yes and no. Middle management should be scared, and people in IT need to start learning quickly, but there are a great number of fields in which AI is pointless.

AI isn't the messiah come to free us from drudgery. It's going to disrupt IT and management, and other information heavy roles, then it will settle down, but not before ruining the lives of many.

Anyone in content production needs to figure out an exit strategy or at least a pivot towards direction because you can already do proper ads and decent quality short movie content for pennies on the dollar vs. getting real actors and sets for it.

It's not just IT, and coding.

 

[Luftkopf]

Anyone in content production needs to figure out an exit strategy or at least a pivot towards direction because you can already do proper ads and decent quality short movie content for pennies on the dollar vs. getting real actors and sets for it.

It's not just IT, and coding.

It's going to be interesting how the market accepts AI content. So far, it's being rejected as slop. I think I read the other day that AI submissions make up 30% of new Apple Music submissions, but they just aren't being listened to.

Personally I think AI can excel as a suite of technologies to make better tools for artists to use. As a generator of end product though. I’m not buying it, and the pushback from regular people is getting stronger.

 

[Pacific1972]

If people are thinking of AI as a basic chatbot and thinking "hurrr, it got the answer to this trivia question wrong! AI is dumb!" they're so far behind the reality of what is happening they may as well be living in the 1980s.

I think 95% of people have no idea just how far AI has actually come today (and that is most dangerous)...

Development is advancing at an ever-faster pace, and AI can now instantly provide answers to questions
that would take humans days to think through - even on topics that are normally quite simple !

When I read that in Singapore, 9-year-olds are already being trained to use computers so that AI can verify
question-and-answer results - because in that country, many jobs are set to be replaced by AI (resulting in
a loss of prosperity for thousands of people as well as a loss of tax revenue for the state of Singapore) -
then this will apply (early or later) to all nations of the world !

AI will not bring prosperity to everyone (that's the biggest lie) - rather, it will lead to a redistribution
of wealth from the bottom to the top - humans will no longer be the first choice when it comes to job
allocation, but only the second choice !

 

[eltoslightfoot]

I think 95% of people have no idea just how far AI has actually come today (and that is most dangerous)...

Development is advancing at an ever-faster pace, and AI can now instantly provide answers to questions
that would take humans days to think through - even on topics that are normally quite simple !

When I read that in Singapore, 9-year-olds are already being trained to use computers so that AI can verify
question-and-answer results - because in that country, many jobs are set to be replaced by AI (resulting in
a loss of prosperity for thousands of people as well as a loss of tax revenue for the state of Singapore) -
then this will apply (early or later) to all nations of the world !

AI will not bring prosperity to everyone (that's the biggest lie) - rather, it will lead to a redistribution
of wealth from the bottom to the top - humans will no longer be the first choice when it comes to job
allocation, but only the second choice !

Everyone that says this cannot show clear evidence of a qualitative change in LLMs. All they show is quantitative improvements, per se. It is just refinement. My biggest fear isn't even the impact of AI, it's the powers-that-be thinking it can have more of an impact than it possibly can. In other words, it's the difference between laying off 25% of your developers and having the rest use AI for certain things, while being careful not to add vibe coding debt, etc., and laying off 100% of your developers and saying the subject matter analysts can do it all with vibe coding because they know everything about how our processes work anyway.

Then when tokens start going up 11x overnight (already happened) and keep on increasing, suddenly they need those people back.

Look at it this way. No company has ever made money selling their LLMs. Not Google, not Microsoft, not Apple, not OpenAI (definitely not them. They are buy out candidate within 6 months), not Meta, not xAI, and not Anthropic.

After some major f-ups, everyone is going to realize that AI can't be held responsible for anything like a human worker, and that, combined with ever present drop in quality, will make everyone realize what a study in radiology showed years ago.

AI combined with a radiologist (with the radiologist in charge of the AI) found more instances of cancer than either could alone.

The other problem here is that the difference between models isn't stark enough to ever charge enough per token to justify the cost of AI (and that's without getting into power or water costs). In other words, say Anthropic 10x (again) their token costs. Everyone just switches to OpenAI. Then OpenAI switches, and people start figuring out how to run Deepseek on their local computers.

Eventually these costs will rise to where profits need to be made and everyone will realize they can only afford to use AI for actual important things--such as figuring out what compounds could make new antibiotics, etc.,

And as far as entertainment, everyone wants uniqueness and care. They do. not. want. AI slop. It will eventually be used in small ways to speed up digital work, but that's it. We want connections in our art, and AI has none.

Edited to add: So it appears I was incorrect about that oft cited radiology study. Here is an interesting follow up:

Why Radiology AI Didn’t Work and What Comes Next | Out-Of-Pocket

FDA Approvals, PACS Pain, Selling Point Solutions, and Why Radiology AI Needed a Rethink

www.outofpocket.health

 

[BSDnostalgia]

The radical shift has been that AI has been handling the verification test definition, test code, verification test and documentation by itself.

We also rarely delegate tasks anymore and have a much higher ownership surface, what get's divvied up is high level ownership surface over a product / domain. Which I assume is the way successful orgs are going to restructure but bodes badly for low level (in the sense of reactive, not proactive) workers.

Thank you for this concise description. Unfortunately, it fits my preconceptions perfectly.

It sounds like there won't be room for junior devs to come through any more. I think this is adding to the debt being built up. Things are going to be rough in ten years.

My thought exactly. In engineering, in general, there is a phase where people learn job-related reality by starting at the junior level and working your way up. In traditional engineering, someone becomes hire-able when they contribute more to the mid- and senior-level engineers than the time they use up by being a beginner. Traditionally, that was at, say, the BS or MS level.

What @Flowstates is correctly identifying, in my opinion, is that the nature of the gig is changing. This is going to mean junior employees are going to need different skills. I think the demand gap right now is because we aren’t training new grads with the right skills for this new era yet.

It isn't clear that there will exist a practical educational path for those coming up. Basically, what you experts are saying is that you already have to know how to do, e.g. "test definition, test code, verification test and documentation", so that the AI agent can do this for you, without your actually ever having had to do these tasks. It appears that AI is creating a situation where only mid- and senior-level engineers are needed and hireable, without an educational path for people to get to that level.

And, it appears that AI-enabled engineering is somewhat better than, say, law, where AI may pretty much abolish the need for assistants. So, where are the entry-level jobs going to come from?

 

[eltoslightfoot]

Thank you for this concise description. Unfortunately, it fits my preconceptions perfectly.

My thought exactly. In engineering, in general, there is a phase where people learn job-related reality by starting at the junior level and working your way up. In traditional engineering, someone becomes hire-able when they contribute more to the mid- and senior-level engineers than the time they use up by being a beginner. Traditionally, that was at, say, the BS or MS level.

It isn't clear that there will exist a practical educational path for those coming up. Basically, what you experts are saying is that you already have to know how to do, e.g. "test definition, test code, verification test and documentation", so that the AI agent can do this for you, without your actually ever having had to do these tasks. It appears that AI is creating a situation where only mid- and senior-level engineers are needed and hireable, without an educational path for people to get to that level.

And, it appears that AI-enabled engineering is somewhat better than, say, law, where AI may pretty much abolish the need for assistants. So, where are the entry-level jobs going to come from?

This is already backfiring and changing. Token costs are going up so much, junior devs are cheaper.

 

[skodises]

And, it appears that AI-enabled engineering is somewhat better than, say, law, where AI may pretty much abolish the need for assistants. So, where are the entry-level jobs going to come from?

The legal profession is experiencing a great deal of trouble in the use of AI. The issue is that the use of AI to research case law for precedent, or prior art in patent prosecution, is fraught with peril: hallucinations are all too common, and reviewing the output to separate the real from the slop is absolutely critical. The courts have demonstrated very little patience with counsel that carelessly bring slop into the proceedings, and rightly so.

AI absolutely can produce ungodly amounts of research output, arguably much more than the average team of attorneys and paralegals, but culling the slop requires very detailed checking line-by-line. And that will continue to take trained, knowledgeable, and experienced legal talent. I don’t see that changing soon…

I’ve served as an expert witness in patent prosecutions as a side gig for some years now, and the legal teams I’ve worked with have some deep concerns here, and well they should. Here’s a quick taste of some of it, for the interested student:

AI on Trial: Legal Models Hallucinate in 1 out of 6 (or More) Benchmarking Queries | Stanford HAI

A new study reveals the need for benchmarking and public evaluations of AI tools in law.

hai.stanford.edu

A legal practitioner’s guide to AI & hallucinations

Using AI carries both responsibilities and risks for legal professionals. Understand how generative AI works, what it does and does not do well, and how to use it responsibly.

www.ncsc.org

AI Hallucination Cases Database – Damien Charlotin

The most comprehensive database of AI hallucination cases in law: legal decisions from courts worldwide, searchable by country, party, AI tool, and outcome. Updated daily.

www.damiencharlotin.com

https://iardc.org/Files/TheFalloutOfAIHallucinationsInCourtFilings.pdf

AI, Liability, and Hallucinations in a Changing Tech and Law Environment | Stanford Law School

law.stanford.edu