What AI Won’t Tell You When It’s Wrong | Jonathan Schaeffer

<p>AI can sound confident, friendly, and brilliant, and still fabricate an answer.</p><p>In this episode of An Hour of Innovation podcast, Vit Lyoshin speaks with Jonathan Schaeffer, founder and CEO of Synsira and creator of Kind, about AI trust, hallucinations, privacy, local AI, and why today’s most impressive tools should still be treated as tools rather than intelligent authorities. Jonathan explains why large language models do not truly understand the questions they answer, why “hallucination” is a misleadingly soft word for fabrication and error, how users can reduce risk by grounding answers in curated data, and why private files may be safer when AI runs locally on the user’s own computer.</p><p>You’ll Learn</p><p>* Why calling AI tools “intelligent” can create dangerous misunderstandings</p><p>* Why hallucinations are better understood as fabrications, errors, or lies</p><p>* How ChatGPT changed public expectations after November 30, 2022</p><p>* Why students and everyday users can overtrust confident AI answers</p><p>* What Jonathan’s incorrect AI-generated biography revealed about band-aid fixes</p><p>* How curated datasets and source citations can make AI answers easier to verify</p><p>* Why local AI can analyze personal files without moving them to cloud AI providers</p><p>* What Kind does for documents, presentations, images, videos, and personal knowledge collections</p><p>* Why cloud AI creates privacy risk for books, intellectual property, company strategy, customer documents, and personal data</p><p>* Why 95 or 99 percent accuracy may still be unacceptable when users cannot tell which answers are wrong</p><p>* Why Jonathan prefers “augmented intelligence” over artificial intelligence as a product philosophy</p><p>* What basic AI education every user should have before trusting these tools</p><p>Jonathan Schaeffer is an AI researcher, founder and CEO of Synsira, and creator of Kind. He spent 40 years at the University of Alberta, where he worked in artificial intelligence, research, teaching, and public speaking before leaving the university to build a local AI product focused on privacy, verifiable answers, and user-controlled data. His background also includes pioneering work in game-playing AI, including Chinook and computer checkers, and recognition as an AAAI Fellow and Royal Society of Canada Fellow.</p><p>Timestamps</p><p>00:00 Introduction</p><p>01:18 Understanding AI Misconceptions</p><p>04:55 The Trust Dilemma in AI</p><p>13:19