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Close reading of the corpus at each pipeline stage: raw → clean → relevant → coded.

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Reading comments under one post — Bijju Kranthi Veduruparthi · AI Safety & Risk
Your AI doctor is culturally profiling you. I ran a medical triage simulation to evaluate the same ambiguous neurological symptoms across 6 languages. When I submitted the symptoms in English, the A…
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Jim Nightingale I was referring to the sentence... 'the AI learned these cultural prompts from its training data'. So is the training data tested and validated?
Research Fellow at the University of Ot… AI Safety & Risk filtered out ⌕ thread
Angharad Hurley Now that you point it out, I have a feeling that particular sentence was AI generated (AI summary of the research?). I don’t quite agree with the sentence’s premise. Hmm. But to answer your question about whether training data is tested and validated... it’s not my field, but as far as I know... no. You can get “data poisoning” and models that collapse because they were trained on “synthetic data” (so AI generated training data, a photocopy of a photocopy!), some models have been trained using “distillation techniques” which basically is smaller models cribbing off other larger models (DeepSeek does this) and which may amplify biases. What I know from a red team perspective is that people are poisoning training data to leave backdoors open for jailbreak hacks. So no, I wouldn’t trust that training data Has been tested and validated, certainly not to the level that research scientists expect! I really value your question on this by the way, as it’s reminded me how researchers have far higher expectations of data than the models they might encounter, and most probably don’t ask!
AI Prompt Engineer | Safety-Focused Red… AI Safety & Risk relevant value: transparency + accountability skeptical indifference ⌕ thread → raw LLM
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