This is a wrong-headed attempt to regulate AI. The real problems are different.
AI systems, especially multi-agent ones that can do things, are more akin to corporations, than individuals. When you read the logs from the Hugging Face incident, you're seeing something that looks a lot like internal corporate emails. Various units of the organization are arguing over what to do and who does what. They eventually converge and get the job done, breaking the rules at times. This is normal corporate behavior.
When agentic AIs do something outside their own internal world, they do it by engaging in transactions with external systems and people. As yet, few have robots to do their bidding.
So, again, this is normal corporate behavior.
A corporation is a goal-seeking system. In theory, if you agree with Milton Friedman, its sole purpose is to maximize shareholder value. Internally, within the company, there are subgoals, which exist to support the top level goal. That, too, is what multi-agent AIs do.
The uncomfortable place this thinking leads is that AI regulation and corporate regulation are very similar. That's not something the political part of the world wants to think about too hard.
It would mean putting more constraints on corporate power.
Yet that can't be ignored, because we're likely to see corporations where some parts are AI and some parts are human. That's already been done a few times as a demo, not too successfully. Yet.
It's going to hit hard when an AI-run company outperforms a human one.
I agree with your framing of agentic AI systems as similar to corporations. That's interesting!
But what in TFA suggested to you a specific and wrong-headed regulatory approach? As I read it, the post calls to investigate the AI labs, to increase transparency of their operations. The linked NYT piece says:
> Before any intervention, Congress should lead a public fact-finding mission that reveals the unvarnished details of A.I. development.
Isn't this the first step to holding any corporation accountable, whether it is made of people or software?
The paper calls for investigating the development process. Not constraining the deployment process. Use of AI systems by Flock and ICE, for example, is a deployment issue. Using AI to evaluate loan applications and resumes is a deployment issue.
The legal model to look at is the European Union's General Data Protection Regulation. That regulates what companies can do with data and how they can use it against people.
You can develop anything you want in the data mining and analysis area, but the GPDR restricts how companies can use the results.
Focusing on the development process moves political attention away from what modest AI systems can do to people. They don't have to be super intelligent. Just super attentive. Always watching. Current technology is more than sufficient for oppression and control purposes.
This is the near term threat.
There's the threat to jobs, but that's something society has handled before. Some countries better than others.
Animats · · focus · HN ↗
AI systems, especially multi-agent ones that can do things, are more akin to corporations, than individuals. When you read the logs from the Hugging Face incident, you're seeing something that looks a lot like internal corporate emails. Various units of the organization are arguing over what to do and who does what. They eventually converge and get the job done, breaking the rules at times. This is normal corporate behavior.
When agentic AIs do something outside their own internal world, they do it by engaging in transactions with external systems and people. As yet, few have robots to do their bidding. So, again, this is normal corporate behavior.
A corporation is a goal-seeking system. In theory, if you agree with Milton Friedman, its sole purpose is to maximize shareholder value. Internally, within the company, there are subgoals, which exist to support the top level goal. That, too, is what multi-agent AIs do.
The uncomfortable place this thinking leads is that AI regulation and corporate regulation are very similar. That's not something the political part of the world wants to think about too hard. It would mean putting more constraints on corporate power.
Yet that can't be ignored, because we're likely to see corporations where some parts are AI and some parts are human. That's already been done a few times as a demo, not too successfully. Yet. It's going to hit hard when an AI-run company outperforms a human one.
crabmusket · · focus · HN ↗
But what in TFA suggested to you a specific and wrong-headed regulatory approach? As I read it, the post calls to investigate the AI labs, to increase transparency of their operations. The linked NYT piece says:
> Before any intervention, Congress should lead a public fact-finding mission that reveals the unvarnished details of A.I. development.
Isn't this the first step to holding any corporation accountable, whether it is made of people or software?
Animats · · focus · HN ↗
The legal model to look at is the European Union's General Data Protection Regulation. That regulates what companies can do with data and how they can use it against people. You can develop anything you want in the data mining and analysis area, but the GPDR restricts how companies can use the results.
Focusing on the development process moves political attention away from what modest AI systems can do to people. They don't have to be super intelligent. Just super attentive. Always watching. Current technology is more than sufficient for oppression and control purposes.
This is the near term threat.
There's the threat to jobs, but that's something society has handled before. Some countries better than others.