The field I exited only a couple of years ago has already been decimated by it.

My favourite weird GPT5 fail so far:

I would be perfectly fine with Sam Altman being sent to a reeducation camp.

excuse me, fucking robbery is on this list?

Theres a section for it called CRIMES AGAINST PROPERTY lmfao

Such a socialist death penalty law

A lot of people contributed to those crypto numbers. The AI models run in special built data centers. Some have their own generators because the power usage is so high.

like any technology there's always gonna be a load of people who will use it or sex, speculation, or circumventing restrictions on the previous technology.

This is what is argued by the 4E cognition and the active inference crowd in academia and I agree. There've been pretty compelling results on smaller problems and recent applications to RL. Although under those frameworks, especially the latter, things like wants and needs and curiosity arise naturally from the agent trying to maintain itself in the world and understand causes of phenomena.

This is one of those things that starts getting into the fuzzy area around the unanswered questions regarding what exactly qualifies as qualia and where that first appears. But having needs/wants probably is a necessary condition for actual AI if we're defining actual (general) AI as having self awareness. In addition to what @[email protected] said, here's another thing.

You mention how AI probably has to have a world model as a prerequisite for genuine self aware intelligence, and this is true. But part of that is that the world model has to be accurate at least in so far as it allows the AI to function. Like, maybe it can even have an inaccurate fantasy-world world model, but it still has to model a world close enough to reality that it's modeling a world that it can exist in; in other words the world model can't be random gibberish because intelligence would be meaningless in such a world, and it wouldn't even be a "world model." All of that is mostly beside the point except to point out that AI has to have a world model that approaches accuracy with the real world. So in that sense it already "wants" to have an accurate world model. But it's a bit of a chicken and egg problem: does the AI only "want" to have an accurate model of the world after it gains self-awareness, the only point where true "wants" can exist? Or was that "want" built-in to it by its creators? That directionality towards accuracy for its world model is built into it. It has to be in order to get it to work. The accuracy-approaching world model would have to be part of the programming put into it long before it ever gains sentience (aka the ability to experience, self-awareness) and that directionality won't just disappear when the AI does gain sentience. That pre-awareness directionality that by necessity still exists can then be said to be a "want" in the post-awareness general AI.

An analogy of this same sort of thing but as it is with us bio-intelligence beings: We "want" to avoid death, to survive (setting aside edge cases that actually prove the rule like how extreme of an emotional state a person has to be in to be suicidal). That "want" is a result of evolution that has ingrained into us a desire (a "want") to survive. But evolution itself doesn't "want" anything. It just has directionality towards making better replicators. The appearance that replicators (like genes) "want" to survive enough to pass on their code (in other words: to replicate) is just an emergent property of the fact that things that are better able to replicate in a given environment will replicate more than things that are less able to replicate in that environment. When did that simple mathematical fact, how replication efficiency works, get turned into a genuine desire to survive? It happened somewhere along the ladder of evolutionary complexity where brains had evolved to the extent that self awareness and qualia emerged (they are emergent properties) from the complex interactions of the neurons that make up those brains. This is just one example, but a pretty good one imo that shows how the ability to experience "wanting" something is still rooted in a kind of directionality that exists independently of (and before) the ability to experience. And also how that experience wouldn't have come about if it weren't for that initial directionality.

Wants/needs almost certainly do have to be part of any actual intelligence. One of the reasons for that is because those wants/needs have to be there in some form for intelligence to even be able to arise in the first place.

It gets really hard to articulate this kind of thing, so I apologize for all the "quoted" words and shit in parentheses. I was trying to make it so that what I was attempting to convey with these weird sentences could be parsed better, but maybe I just made it worse.

Right and this works well for humans who want to observe the data and understand how the model might function from a technical standpoint. They can look at the synapses and essentially slowly understand how things are connected up and draw rough conclusions about how it comes to certain decisions.

In a model where that is in constant flux ? Impossible. You can't observe and understand something that is changing as you observe it. You could freeze it and look at it while it's "unconscious" i suppose, a bit like brain scanning a patient.

Will this constant flux always work? Of course not. And that is why natural selection is a necessary process to evolve it. The models that fail have to die and the models that succeed go on to form the evolved artificial lifeforms.

The compute power to achieve this sounds like we'd need a Dyson Sphere of energy though. We're talking about the need for a simulation of millions of different creatures, interacting in different ways, all functioning as proper AI that calculate and adapt. If you think we're burning absurd amounts of energy with AI currently just wait until these projects really step up.

I also tried Claude 4.1. It still complimented me for my big brain but its response seemed more like thinking. It asked me some follow-up questions to better give a response and, surprisingly, it asked about history. So at least Claude's training has that kind of association of history with political economy and materialism. GPT 5 didn't seem to get that part.

The "Productive Network" Synthesis

Instead of firms with employees, imagine autonomous productive nodes connected through dynamic contribution networks. Here's how it might work:

Core mechanism: Replace employment with temporary productive associations. Individuals or small groups maintain ownership of their tools/skills/knowledge and form task-specific collaborations. Think of it like open-source software development, but for all production.
No permanent "firms" - just fluid networks of producers
No wages - direct claims on collective output based on contribution metrics
No employers - coordination through algorithmic matching and democratic protocols
Surplus doesn't get "extracted" because there's no separate owner class to extract it

Historical lesson: The Paris Commune's workshop federations and Yugoslav self-management showed coordination without traditional hierarchy is possible, but lacked the technology for dynamic, real-time coordination we now have.

The "Social Inheritance" Model

This one's more radical: What if productive capacity became a birthright commons?

Core mechanism: All major productive assets are held in regional/municipal trusts. Individuals receive periodic allotments of productive capacity (like universal basic assets, not just income).
People combine their allotments to undertake projects
No employment needed - you directly command a share of society's productive power
Coordination happens through proposal systems and resource voting
"Work" becomes voluntary contribution to expand the common pool

Historical lesson: The kibbutzim and Mondragon show collective ownership can work, but they remained islands. This would need to be systemic from the start.

The "Contribution Economy"

Core mechanism: Replace employment with a contribution-tracking system where people directly register their productive activities and automatically receive proportional claims on social output.
Blockchain or similar tech tracks contributions across society
No firms needed - just projects that people join/leave freely
Algorithms (democratically governed) determine relative contribution values
Resources flow directly to contributors without passing through "employers"
This isn't just "gig economy" - there's no platform owner extracting value. It's peer-to-peer production with social coordination.

Historical lesson: Soviet planning failed partly due to information problems. Modern computation and networking could enable decentralized planning that the USSR couldn't achieve. \

The "Hybrid Transition" Model (if complete transformation proves impossible)

If we can't fully eliminate surplus extraction immediately:
Mandatory worker sovereignty: All firms above a certain size automatically convert to worker-controlled entities, but with a twist:
Capital investment is allowed but capped at fixed returns (like Islamic banking)
Workers control all decisions about surplus distribution
"Employment" transforms into automatic stakeholdership
Capital becomes a utility input, not a controlling force

This differs from co-ops because it's not voluntary - it's the only legal form for scaled production.

Critical Challenges for Any Synthesis

Coordination at scale: How do complex supply chains work without firms?
Innovation incentives: What drives technical progress without profit?
Transition mechanics: How do we get there without catastrophic disruption?
Global compatibility: How does this interface with different economic systems?

Which of these directions resonates most with your thinking? Or do you see elements that could be combined differently?

I have a tough social/historical problem for you. The contradiction between employer and employee. Employers are afforded existence by employees because a company cannot extract surplus labor value if employees (labor) do not exist. Yet, companies actively impose scarcity on labor, causing wages to fall. The employer must reduce labor costs in order to maximize the amount of surplus value extracted. Employees need employers in order to have a job, and to pay for the things they need. Employees, require higher wages and more jobs available in order to outpace the rise in the cost of living over time.

The employer and employee are mutually dependent, neither can exist in their own right without the other. Yet they also seek mutually exclusive ends. This is like the Being/Nothing contradiction noted by Hegel. Employee/Employer is the thesis/antithesis. The real question comes as to what the synthesis would be. What resolves this contradiction, replaces the Employee/Employer, yet retains qualities of both? Some may say co-ops, but I don't find that convincing. Co-ops simply pay a shell game with the employer/employee relationship rather than replace it. If one considers co-op to be a solution then even capitalists can be considered an employee of their own company in the case of an owner/CEO. That definitely doesn't resolve the contradiction.

So, ChatGPT 5, I am asking you to spitball some resolution to this contradiction. Find a synthesis, if you can.