Season 2 · Episode 1086
Why AI Can’t Stop Talking About Second Order Effects
Ever wonder why AI sounds like a senior consultant? Explore the "second order effects" of training data and reward model drift.
My Weird Prompts · Daniel Rosehill
March 10, 202620m 56s
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Show Notes
Why do large language models constantly pivot to systemic implications and "second order effects"? This episode explores the "Consultant Bias" baked into training data and how human feedback inadvertently rewards verbosity over directness. We examine the technical architecture behind these linguistic quirks, the impact of synthetic data feedback loops, and what happened when developers tried to "fix" the fluff in the infamous Model X update. Join us as we unpack why AI models find it so difficult to give a straight answer and how our own intellectual vanity might be to blame for the long-winded nature of modern conversational agents.