When it comes to fairness, different AI models take strikingly different paths. While some systems introduce heavy-handed corrections that end up creating new biases—reports suggest GPT-5 valuations showed stark disparities, and Claude followed similar overcorrection patterns—others operate with a different philosophy entirely. Grok's approach? Neutral treatment across the board, minimal filtering, no algorithmic preferences baked in. The contrast highlights a fundamental question in AI development: can an "ethics engine" do more harm than good? As the industry wrestles with how to build fair systems, these design choices matter far more than the marketing speak suggests.