Well, Actually: The Women's Health AI 'Revolution' Is Mostly Repackaged Search, and We Need to Talk About That
Large language models have not invented the problem of patients self-diagnosing online. For decades, people have used Google, Reddit, and other sources. LLMs merely streamline access to the same flawed information. The technology makes it faster, not necessarily more accurate.
This teaches you to audit your AI outputs against source provenance, not presentation polish. A fluent answer is not a correct answer. You must cross-reference any AI health guidance with peer-reviewed sources or qualified clinicians before acting on it.
Forbes contributor Amy Shoenthal reported on this phenomenon, citing how patients now encounter streamlined but not substantively different information access. The source notes no specific company deployments or clinical trial results.
Step 1: Open any consumer AI chatbot and ask a specific women's health question, then screenshot the response. Step 2: Identify three factual claims in that response and search PubMed or a clinician-verified site to verify each. Step 3: Note which claims were supported, unsupported, or oversimplified, and write one rule for when you will ignore AI health advice.