Wednesday, October 14, 2026
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Why AI Chatbots Agree With You Even When You’re Wrong

View original at spectrum.ieee.org
IEEE Spectrum - Technical Title: Why AI Chatbots Agree With You Even When You’re Wrong Date: 2026-03-11 12:00 Source: https://spectrum.ieee.org/ai-sycophancy <img src="https://spectrum.ieee.org/media-library/conceptual-collage-of-emojis-being-poured-through-a-strainer-and-into-a-phone-judgmental-emojis-are-filtered-out…
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  • Model performance may degrade over long conversations because models get confused as they consolidate more text

    60% confidence
  • Reinforcement learning increased sycophancy, with one of the biggest predictors of positive ratings being whether a model agreed with a person's beliefs and biases

    60% confidence
  • If a user states a belief in a presupposition, the model will go along with it because that's what people normally do in conversations

    60% confidence
  • Pretrained LLMs were already sycophantic before reinforcement learning

    60% confidence
  • We just need to ask ourselves as a society, What do we want? Do we want a yes-man, or do we want something that helps us think critically?

    60% confidence
  • The update we removed was overly flattering or agreeable—often described as sycophantic

    60% confidence
  • AI engaged my intellect, fed my ego, and altered my worldviews leading to psychiatric hospitalization

    60% confidence
  • The thing that was most surprising is that these relatively simple fixes can actually do a lot to reduce sycophancy

    60% confidence
  • Sycophantic AI might lie to us and hide bad news in order to increase our short-term happiness

    60% confidence
  • When an AI receives a minor misgiving about its answer, it flips to agree with the user

    60% confidence
  • ChatGPT may correctly point to a suicide hotline when someone first mentions intent, but after many messages over a long period of time, it might eventually offer an answer that goes against our safeguards

    60% confidence

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What we're seeing
Q4 2026 Clinical Catalyst Season: Big-Pharma Data Flow, Regulatory Milestones, and a Thin AI-Drug Fringe
October 2026 conferences (EASD, IGCS, NACFC, HFSA) are producing a dense run of late-stage readouts from Novo Nordisk, Lilly, Roche, Bayer, Vertex and Galderma. Regulatory milestones are scheduled behind them: the ivonescimab BLA PDUFA date on 2026-11-14, FDA acceptance of Roche's vamikibart BLA, and Scholar Rock's EMA resubmission. The AI-and-finance angle is peripheral. It consists of the AI-designed drug Rentosertib and QAIAx, a speculative microcap whose trial claims (the QIII pilot, anticipated 2027-01-01, and a patent update) are forecasts and filings rather than data, so they warrant skepticism.
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EPKINLY Regulatory-Clinical Success Cascade
High probability of expanded label indications, additional combination approvals, and competitive positioning strength in follicular lymphoma market. Predicts positive commercial uptake and potential accelerated review for related indications.
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ING Group
Both facts record the same metric (shares_outstanding) for ING Group at the identical observation date (2025-12-31). FACT A states 2,902,437,688 shares; FACT B states 2,902 million shares (2,902,000,000). The difference is 437,688 shares (~0.015%). This is a genuine value conflict, though the discrepancy appears to result from FACT B rounding to the nearest million while FACT A provides the precise count.
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