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The main way would be for people to use local models BEFORE the main AI labs take most of the excess economic activity. This creates demand for direct compute/land/energy rather than AI intelligence and as long as ownership of those stays with communities then a good economic model would be those rents subsidize the community (rather than say a UBI). Open source models will help majorly as long as people are willing to be 1 generation or so behind the latest model which currently isn't the case although I'm hoping it will do the job soon.

i.e. the community, rather than AI/big corp, would need to somehow own the scarce assets required for AI and extract economic rent from them. Whether it is energy, land, water, etc. I think its a better system then say UBI because both parties still provide something of value. This isn't my base case but it is possible. It also needs to be done while human power structures still have economic power (i.e. governments)

So it would be a combination of political will (i.e. you can't use frontier models unless they can be run by end users) and technical in that you need to have enough compute distributed with the profits of that going to local communities (e.g. data centre rent). When the AI labs engage the community that way they will pay "money" which creates a demand from large corps to local communities and adds life to the monetary system - a good thing.

Effectively compute needs to be a commodity that is rent-able/accessible to everyone at competitive prices and have multiple providers. That enables open source models, and allows a spread around the ownership of AI. It can't be hoarded by the AI labs, nor can the chips (e.g. GPU's) have only a few producers.

AI feudalism and/or monarchy although that could be quite awhile from now - there will be niches that are harder to integrate with AI that are protected for longer. A few owning everything; most other people surplus to requirements. Capitalism rewards scarcity with higher prices with both financial and social status for those with those scarce outputs - unfortunately what humans can do will become more less scarce relative to capital, land and other resources often owned by the wealthy. Economic rent will move away from skilled labor to other economic inputs.

Even people that go off grid and develop self sufficiency will eventually be subsumed by the need to feed more resources to the AI genie to grant more wishes. Whether it is land taxes, forced relocations, etc. Their land will be taken over, mined and or farmed - similar to colonies of old that were technologically less advanced than their invaders.

You are already IMV starting to see the beginning signs of the above as AI gets better. More competition in jobs, less certainity for the working class, businesses with other moats using AI to increase profits, data centres vs local communities taking land/energy/water over, AI required commodities increasing in value (e.g copper) and others. There will be more.

Modern times where we have democracy and capitalism are a relative recent phenomena when looking at the whole of human history that we take for granted when we shouldn't.

Real assets have utility of their own (i.e. a house to live in, commodity to build, etc). Money only exists to incentivize human economic actors to bother working, to relative price resources against each other and for governments to use as a tool - it isn't wealth on the aggregate scale.

AI invalidates a lot of the need for money to even exist as a concept anyway in some scenarios. If only a few people have all the stuff (huge inequality) you don't really need a large money system because you no longer need most people to get what you want (i.e. most are economically irrelevant). You have a magical genie called AI instead that can transform what you have into what you want as long as you have the raw materials, space and energy. The wealthy could then negotiate in large transactions via barter - I trade that plot of land for that copper mine. Most large transactions are negotiated in any case.

A very likely case (there are others) is that AI enables feudalism of some sort to come back - where the new lords are the owners of the other economic factors of production that remain scarce (capital, land, resources, social) - not intelligence and/or labor. This is the opposite of a meritocratic society. It would explain why people want to win the AI race; and are willing to burn uneconomic amounts of money to build it out. There is a race to the finish here.

For awhile yes. Its ironic that the least productive people in knowledge work with the cushiest jobs will probably survive the AI wave the most. Because they do little they were probably employed for reasons other than utility/output in the first place - there isn't much to automate anyway.

While all the grinding skilled workers get displaced the bureaucracy jobs will remain. Ironic.

There is a lot of reasons why automated companies pay more but it is usually to do with augmentation and the remaining skills required being higher on the skills pyramid and more scarce. Efficiency gains usually cause the next bottleneck to be hit requiring more skill and/or experience to fix (higher hanging fruit).

Usually the amount of pay increase no way compensates for the total pay lost across all workers - that's one of the incentives to continue with the efficiency gain of course. If it happens too fast only a select few will have jobs because the demand won't have time to match the new supply.

All the above assumes you need greater levels of intelligence to deal with the next bottleneck and that intelligence comes from humans as its only source. If AI is more intelligent than humans then this effect - known for most of human history - becomes an invalid assumption of the economic model; bottlenecks and the ability to solve them goes to the highest/cheapest intelligence.

IMV should AI do this it would invalidate most economic system assumptions including ones in capitalism, socialism, etc. My base case isn't a positive one sadly of what comes out on the other side.

I suspect this is a "what you are used to" and have trained yourself to look out for over many years of code reading.

You are thinking growth in product and opportunities. But that doesn't always require or translate to more engineering especially in the face of AI efficiency if that work to support that growth can come from AI (NOTE: I'm not saying it can; I believe some people believe and are acting like it can which is enough). For these people the new bottleneck to growth may be new market segments, adoption and integration which could mean more sales like staff - AI seems more of a boon to the non technical, AI hypers and sales pitchers IMO than it is to engineers. On a side note personally this makes the industry less desirable to work in - it devalues effort/intelligence/craftsmanship/product and values connections, marketing, status and "the hustle" a lot more.

As the supply curve of software becomes more vertical due to AI the argument that growth equals a proportional amount of engineering demand may be violated. We may see 2x growth in some companies even as the "people engineers" are cut. They could still be pursuing growth; it just that engineering costs are now lower or are less of a need to pursue that growth in general.

AI is the first technology that I've seen that has potentially hurt technology engineering demand rather than creating it; which is why the usual arguments don't always apply here.

My opinion is that it is because the measure isn't aimed at technical people. It's aimed at clients that just want to specify what they want -> then get what they want without an engineer. They are pitching to their investors, VC's, etc who just want to "will their stuff into existence" without engaging professional staff. Their end goal isn't augmentation, or a faster tool. It's replacement of expertise and capturing of that value to the AI labs. Similar to how I would love a new house to be magically built just by prompting it without having to engage anyone; or follow the process. Its great for marketing having the AI genie.

> A better move would be to stop allowing people to graduate in CS.

Its a free market if you are the one paying for it solely. If you are willing to pay for the degree then the demand is there for them to sell you the product. Buyer beware sadly. Its a question of what you see the purpose of the course is - to prep people for the job market or to teach knowledge? If it is the former to you then yes they should at least warn people of the competition and the contraction of the industry they may face - they can decide if it is worth it for them.

For many on this forum if they are honest with themselves given the pace of AI and the future risk/uncertainty they may not have taken this risk on. They've misallocated their own funds which is always not ideal - and sadly expected when there is rapid change; not all investments pay off. The only thing I can say is if you are young the time horizon is there to invest in something else and get back on your feet. There is more to life then work IMV especially as you get older; and an investment in your career needs enough time horizon to pay off. For many a job is a means to an end - they may enjoy it but being able to earn a long term living is the primary goal.

In other countries where the education is subsidized for the purposes of skill building for the economy then yes I actually think it might be pragmatic for them to offer less places. Otherwise its tax money going to waste with a misallocation of public resources without the associated society wide economic benefits.

If the industry is to shrink this is the best way it can. Stop people entering while they are young and can pivot into something with better returns. Keep the experienced people who are older and may find it harder to pivot and had some "good days" to help them ride them through these bad times. I've seen similar dynamics in other industries as they slowly die/move on (e.g. manufacturing, niche trades, etc). A slow decline is better than a boom/bust. If it ends up that we need software engineers later training is an easier problem than mid career death for the juniors in a few years time.

Eventually the market finds a new equilibrium of staff to demand ratio. You prefer that happen sooner so people don't make bad investments of their time (e.g. studying the wrong course based on inaccurate market signals).

My personal anecdote when I talk to people - everyone when talking about their job w.r.t AI is like "at least I'm not a software engineer!". To give a hint this isn't just a US phenomenon - seen this in other countries too where due to AI SWE and/or tech as a career with status has gone down the drain. Then they always go on trying to defend why their job is different. For example "human touch", "asking the right questions" etc not knowing that good engineers also need to do this.

The truth is we just don't know how things will play out right now IMV. I expect some job destruction, some jobs to remain in all fields, some jobs to change, etc. We assume it will totally destroy a job or not when in reality most fields will be somewhere in between. The mix/coefficient of these outcomes is yet to be determined and I suspect most fields will augment both AI and human in different ratios. Certain fields also have a lot of demand that can absorb this efficiency increase (e.g. I think health has a lot of unmet demand for example).

I find algo performance is a consideration, but so is overall system performance especially in the face of concurrency, staleness, update rate, data processing size, consistency of data, etc. I think persistent collections are just another tool which is sometimes appropriate; and it has saved me over the standard Concurrent collections in some interesting cases. There are significantly faster immutable collection libraries than the standard F# Map class though online you can use if I recall from awhile back - still not quite mutable perf though. It tends to be appropriate to use for almost the opposite case than a single thread in a tight loop which is the usual benchmark I guess. As usual YMMV/depends on problem at hand.

Agree. Anthrophic in particular have been quite clear in what they are trying to do. Every blog post about every new model almost dismisses every other use case other than coding - every other use case seems almost a footnote in their communication.