Position: Levels of AGI for Operationalizing Progress on the Path to AGI
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Let's unpack a paper titled "Levels of AGI for Operationalizing Progress on the Path to AGI." What's the core idea here? Right on. The authors of this May 2024 paper lay out a framework for classifying the abilities and actions of artificial general intelligence AGI models and the steps leading up to them. That's a cool way to think about it. But why is defining these levels so important?

It's all about having a shared language to compare different AGI models, like having a universal rating system for movies.

It helps us see how far we've come, how far we have yet to go, and the risks that pop up at each stage. This shared understanding is super important for researchers, policymakers, and even the public. Okay, I get it. It's like a roadmap for AGI. Can you break down these levels for us a bit more? Absolutely. They've got five levels of performance, starting with emerging, where AGI

An AI might be as good as an untrained person on some tasks. Then it moves up to competent, performing like a skilled person, then expert and virtuoso, where it's outperforming most people. The final level is superhuman, where it's better than any human at a task. Whoa, superhuman AI, that's mind-blowing. But how do they measure the generality part?

Good question. That's where things get a bit tricky. It's about the range of tasks an AI can perform at a certain level. The authors don't set a specific list of tasks in this paper, but they do outline what a good benchmark should look like. So it's still a work in progress, but the idea is clear. This is pretty exciting stuff. Are there any existing AI models that fit into these levels? The paper suggests that as of September 2023,

Frontier language models like ChatGPT might exhibit competent performance levels for tasks such as short essay writing or simple coding, but they're still at emerging performance levels for other tasks like complex math problems or tasks requiring factuality. That makes sense. I can see how this framework could really change how we talk about AGI. But what about the risks you mentioned? Ah, yes. Risk is a big part of the discussion.

Each level of AGI comes with its own set of risks. For example, at the lower levels, it's more about human misuse of the technology, like spreading misinformation. But as we move up to the expert and virtuoso levels, we start to worry about things like job displacement and even the potential for the AI to act in ways we didn't intend. That sounds a bit scary.

How do we address these risks? The authors argue that it's not just about the AI's abilities, but also how we interact with it. They propose different levels of autonomy from AI as a tool where we're in full control to AI as an agent where it can act on its own.

By thinking about both the AI's capabilities and how we use it, we can make smarter choices about how to deploy these systems safely. This is all super interesting. I'm starting to see how this framework could be a game changer in the field of AI. Any final thoughts before we wrap up? I'd say this paper is a great starting point for a much needed conversation.

By defining levels of AGI and considering the risks at each stage, we can work together to make sure that as AI gets more powerful, it's also used responsibly and for the benefit of everyone. And this closes our discussion of levels of AGI for operationalizing progress on the path to AGI. Thank you.