A new Stanford-led study suggests today's LLMs can't reliably separate facts from first-person beliefs... and that's a problem when these systems show up in healthcare.
In this episode, I break down what the study found (including the "34% worse" belief problem), why "91% accuracy" can still be misleading, and what it means when tools designed to predict language get treated like truth machines.
Also: A woman in Japan married her ChatGPT character with AR glasses, LinkedIn's new AI search is about to surface everyone you've been avoiding, and Microsoft's AI leadership argues for "humanist superintelligence" while admitting nobody has a reassuring answer for how to guarantee safety.
⏱️ CHAPTERS
00:00 - The Japan AI Wedding
01:42 - Stanford Study: AI Can't Tell Fact From Fiction
03:50 - The 91% Accuracy Paradox
05:56 - The Deployment Problem
07:39 - Palette Cleanser: LinkedIn AI Search
08:58 - Microsoft's "Humanist Superintelligence"
10:16 - What This All Means for You
📚 SOURCES & STUDIES:
- Japan AI Wedding (The Independent): "Woman marries ChatGPT character with AR glasses"
- Japan AI Wedding (x.com/Osint613)
- Stanford Study (Nature Machine Intelligence): "Language models cannot reliably distinguish belief from knowledge and fact"
- Stanford Study (The Register): "Gullible bots struggle to distinguish between facts and beliefs"
- LinkedIn AI Search (TechCrunch): "LinkedIn adds AI-powered search to help users find people"
- Microsoft AI CEO Essay (Microsoft): "Towards Humanist Superintelligence"
- Microsoft AI CEO Essay (The Verge): "Microsoft AI says it'll make superintelligent AI that won't be terrible for humanity"
🔑 TAKEAWAYS
- Some newer models were less likely to flag false first-person beliefs than true ones
- Large Language Models (LLMs) can score high on simple true/false tests while still using inconsistent reasoning
- The risk isn’t just "being wrong," it's being confidently wrong in high-stakes settings
💡 WHY THIS MATTERS
If you're using AI for medical or legal advice, job decisions, or trust it with important information, you need to know: it can't tell when you're wrong. It will confidently agree with your false beliefs because it's designed to predict word sequences, not verify truth.
🎙️ ABOUT
I'm Justin, a human trying to make sense of AI without losing my mind. Spoiler: it's not going well.
This is the AI news desk show that feels like Ronny Chieng's Eye on AI segment on The Daily Show if the budget disappeared and he gained anxiety. I break down AI stories that actually affect your life - your job, your health, your privacy, and your sanity - without hype, panic, or sci-fi nonsense.
I read the studies, track the corporate announcements, and spiral just enough so you don't have to. Then I turn it into something you can actually understand, talk about, and maybe even laugh about.
Every episode is factually rigorous, hallucination-proof, and delivered by an anxious person with a coping mechanism.
📬 FOLLOW for (semi?) weekly AI news, AI safety updates, and commentary that acknowledges all sides of artificial intelligence.
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AI in healthcare, generative AI in hospitals, LLM hallucinations, belief vs knowledge, medical AI decision support, AI safety, tech news commentary
NOT MEDICAL, LEGAL, OR FINANCIAL ADVICE
This is commentary and research, not medical, legal, or financial advice. If you have a medical, legal, or financial concern, talk to a licensed professional.
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