Care to elaborate?

Here's my series about misconceptions: https://simonwillison.net/series/llm-misconceptions/

It's like criticizing a "Hello World" program for not having proper error handling and security protocols. While those are important for production systems, they're not the point of a demonstration or learning example.

Your response seems to take these examples and hold them to the standard of mission-critical systems, which is a form of technical gatekeeping - raising the bar unnecessarily high for what counts as a "valid" technical demonstration.

To my surprise, on re-reading that post I didn't mention that you need to double-check everything it does. I guess I forgot to mention that at the time because I thought it was so obvious - anyone who's paying attention to LLMS should already know that you can't trust them to reliably extract this kind of information.

I've mentioned that a lot in my other writing. I frequently tell people that the tricky thing about working with LLMs is learning how to make use of a technology that is inherently unreliable.

Update: added a new note about reliability here: https://simonwillison.net/2024/Oct/17/video-scraping/#a-note...

Second update: I just noticed that I DID say "You should never trust these things not to make mistakes, so I re-watched the 35 second video and manually checked the numbers. It got everything right." in that post already.

> You seem to be confusing me with someone that hasn't been asking you repeatedly to address these kinds of concerns

Where did you do that?

When it was Open?

More substantively, we can check our vibe. OpenAI is just as active as it ever was w/notebooks. To an almost absurd degree. 5-10 commits a week. https://github.com/openai/openai-cookbook/activity

This matters mostly when things go wrong. Who's responsible? The airline whose AI agent gave out wrong info about airline policies found, in court, that their "intelligent agent" was considered an agent in legal terms. Which meant the airline was stuck paying for their mistake.

Anthropic's definition: Some customers define agents as fully autonomous systems that operate independently over extended periods, using various tools to accomplish complex tasks.

That's an autonomous system, not an agent. Autonomy is about how much something can do without outside help. Agency is about who's doing what for whom, and for whose benefit and with what authority. Those are independent concepts.

I ask because you seem very confident in it - and my biggest frustration about the term "agent" is that so many people are confident that their personal definition is clearly the one everyone else should be using.

But I'm not sure if that's true. The court didn't define anything, in contrary they only said that (in simplified terms) the chatbot was part of the website and it's reasonable to expect the info on their website to be accurate.

The closest I could find to the chatbot being considered an agent in legal terms (an entity like an employee) is this:

> Air Canada argues it cannot be held liable for information provided by one of its agents, servants, or representatives – including a chatbot.

Source: https://www.canlii.org/en/bc/bccrt/doc/2024/2024bccrt149/202...

I'm not saying it's not a valid definition of the term, I'm pushing back on the idea that it's THE single correct definition of the term.

Bank: financial institution, edge of a river, verb to stash something away

Spring: a season, a metal coil, verb to jump

Match: verb to match things together, noun a thing to start fires, noun a competition between two teams

Bat: flying mammal, stick for hitting things

And so on.

If we're redefining common words to market this stuff to non-tech people, and then we're conveniently not telling them that we redefined words, and thus allowing them to believe implicit falsehoods about the product that have serious consequences, we're being disingenuous.

Sort of interesting that we've coalesced on this term that has many definitions, sometimes conflicting, but where many of the definitions vaguely fit into what an "AI Agent" could be for a given person.

But in the context of AI, Agent as Anthropic defines it is an appropriate word because it is a thing that has agency.

That seems circular.

Perhaps you mean tautological. In which case, an agent having agency would be an informal tautology. A relationship so basic to the subject matter that it essentially must be true. Which would be the strongest possible type of argument.

"Anything that can be viewed as perceiving its environment through sensors and acting upon that environment through actuators"

https://en.wikipedia.org/wiki/Intelligent_agent#As_a_definit...

You can think of this in video game terms: Players have agency. NPCs are "agencs", but don't have agency. But they're still not just objects in the game - they can move themselves and react to their environment.

An AI "agent" is the same way, it is not culpable for its actions, the humans who set it up are.

Another great example of this trick is "essential" oils. We all know what the word "essential" means, but the companies selling the stuff use the word in the most uncommon way, to indicate the "essence" of something is in the oil.

Maybe I'm wildly off base here, I have admittedly been wrong about a lot in my life up to this point. I just think the backlash that crops up when people realize what's going on (for example, the airline realizing that their chat bot does not in fact operate under the same rules as a human "agent," and that it's still a technology product) should lead companies to change their messaging and marketing, and the fact that they're just doubling down on the same misleading messaging over and over makes the whole charade feel disingenuous to me.

What is the 'product' here? It's a university textbook. Like, where is the parallel between https://en.wikipedia.org/wiki/Intelligent_agent and 'essential oils'.

Knowing that your target market (non-tech folks) isn't using the same language as you, but persisting with that language because it creates convenient sales opportunities due to the misunderstandings, feels disingenuous to me.

An "agent" in common terms is just someone acting on behalf of another, but that someone still has autonomy and moral responsibility for their actions. Like for example the airline customer service representative situation. AI agents, when we pull back the curtains, get down to brass tacks, whatever turn of phrase you want to use, are still ultimately deterministic models. They have a lot more parameters, and their determinism is offset by many factors of pseudo-randomness, but given sufficient information we could still predict every single output. That system cannot be an agent in the common sense of the word, because humans are still dictating all of the possible actions and outcomes, and the machine doesn't actually have the autonomy required.

If you fail to keep your tech product from going off-script, you're responsible, because the model itself isn't a non-deterministic causal actor. A human CSR on the other hand is considered by law to have the power and responsibility associated with being a causal actor in the world, and so when they make up wild stuff about the terms of the agreement, you don't have to honor it for the customer, because there's culpability.

I'm drifting into philosophy at this point, which never goes well on HN, but this is ultimately how our legal system determines responsibility for actions, and AI doesn't meet those qualifications. If we ever want it to be culpable for its own actions, we'll have to change the legal framework we all operate under.

Edit: Causal, not casual... Whoops.

Also, I think I'm confusing the situation a bit by mixing the legal distinctions between agency and autonomy with the common understanding of being an "agent" and the philosophical concept of agency and culpability and how that relates to the US legal foundations.

I need to go touch grass.

https://www.etymonline.com/word/autonomous

But that's not their definition, and they explicitly describe that definition as an 'autonomous system'. Their definition comes in the next paragraph:

"At Anthropic, we categorize all these variations as agentic systems, but draw an important architectural distinction between workflows and agents:

* Workflows are systems where LLMs and tools are orchestrated through predefined code paths. Agents, on the other hand, are systems where LLMs dynamically direct their own processes and tool usage, maintaining control over how they accomplish tasks.

* Agents, on the other hand, are systems where LLMs dynamically direct their own processes and tool usage, maintaining control over how they accomplish tasks."

Disclaimer: I'm the author of the framework.