There's no comprehensive system that combines objective evidence (code commits, chat logs) with AI-powered analysis to fairly adjudicate group work disputes.
The researchers applied Netflix-style recommendation algorithms to education, asking "If streaming platforms can predict what movies you'll love, why can't universities predict which courses will advance your career?"
Modern AI agents are incredibly powerful - they can book flights, write code, manage your calendar, and even make purchases on your behalf. But there's a critical issue:the more capable these agents become, the harder it is for humans and AI to truly understand each other.
Do AI models succeed because they know facts, or because they reason well? And does the answer change depending on whether you're doing math or medicine?
Large Language Models (LLMs) excel at playing heroes but systematically fail at portraying villains. This research reveals a fundamental conflict - safety alignment makes AI models so "good" that they literally cannot be "bad" - even in fictional role-playing scenarios.