New paper proposes AI alignment "bees" — classifier species that monitor LLMs continuously, can't be jailbroken, and produce both value and correction

Here's something that caught my attention — researchers are proposing a new way to keep AI aligned using what they call 'bees.' These aren't your typical classifiers; they're like a species that evolves over time, constantly watching and guiding large language models. According to /u/Accurate_Complaint48, these bees don’t reason or get jailbroken because they just pattern-match and give binary judgments — yes or no. They’re supervised by three parallel evaluators, acting as advocates, adversaries, and neutrals, making sure outputs stay on track. Now, here's where it gets fascinating — they’re designed to produce both value and correction, with memory decay managing what they remember, so transient mistakes fade while core principles stick. Multiple papers from Anthropic back up this architecture independently, showing a convergence of ideas around this bee concept. And get this — these classifiers aren’t just products; they’re a kind of evolving species, built to improve and adapt over time. As /u/Accurate_Complaint48 explains, this approach could address the circularity problem we face with current AI alignment methods, and it’s a huge step forward in making AI safer and more reliable.