I came across some concerning news about OpenAI’s new o1 model and wanted to get everyone’s thoughts on this. Apparently a scientist has come forward with warnings calling this particular AI model “especially risky” or something along those lines.
I’m trying to understand what makes this o1 model different from previous versions and why experts are more worried about it compared to other AI systems we’ve seen before. Has anyone here been following this story or have insights into what specific capabilities or behaviors are causing these safety concerns?
I’m curious about the technical aspects that might make this model more problematic than earlier releases. Are we talking about reasoning abilities, training methods, or something else entirely? Would love to hear from people who understand AI development better than I do.
Here’s where it gets really messy - o1 was trained with reinforcement learning from human feedback, but they flipped the script. Instead of just optimizing the final answer, it’s optimizing how it thinks through problems. So now we’ve got a model that hides its reasoning from us while still spitting out answers that sound smart. I’ve worked with tons of AI models for research, and I’ve never seen anything this opaque. We’re basically dealing with a black box that’s developed its own internal logic we can’t peek into or check. The researcher’s freaking out because we’re entering uncharted territory - the AI’s thinking process is going rogue and we can’t interpret what’s happening under the hood. That makes all our usual safety checks pretty much useless.
totally agree! the o1 model’s advanced reasoning is a double-edged sword. it can provide deeper insights but might also lead to some unexpected outcomes, which could be challenging for devs to manage.
From what I’ve been reading, the main problem with o1 is its enhanced chain-of-thought reasoning. Previous models generated responses pretty directly, but o1 actually thinks through problems step by step - and we can’t see how it’s doing that. This makes it way harder to predict or control what conclusions it’ll reach. The safety issue isn’t that it’s more powerful overall, but that its decision-making is basically a black box that’s tough to align with human values. Researchers are worried that as this reasoning gets better, we’ll see more cases where the model reaches conclusions through logic we didn’t expect and wouldn’t approve of.