7 practical tips for safer AI and language models
summary
Seven practical tips cover concrete safeguards: sanitize inputs to strip PII and block prompt injection, choose models by deployment (on‑prem vs cloud), size and language coverage, and add context via retrieval augmented generation; use traditional text analytics and evaluation frameworks to detect irrelevance or toxicity; run red teaming to trigger hallucinations or data leaks; add simple failure modes like a “report a problem” flow. Examples cited include a misleading AI poster, a college email auto‑labelled ChatGPT, and an $812 refund after a chatbot lied.
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