100 篇研究重做，為什麼大多做不出來？

00:00 開場：一百篇研究重做，只剩三分之一 00:41 休謨（牛津 Millican 原聲）：太陽明天會升起嗎 02:18 羅素的雞與一隻黑天鵝 04:28 Popper 與阿德勒：一千零一次 05:36 1919年日食：一次可能落空的預測 07:39 輔助假設：救理論，還是硬救 08:47 海王星與祝融星：同一招，一成一敗 10:05 Kuhn：典範、異常與科學革命 11:41 2011年比光還快的微中子 12:40 再現危機：預知未來的論文與抽屜裡的實驗 14:43 一百篇重做剩 36%，Amgen 53 篇剩 6 篇 17:24 AI 開始做研究：Sakana AI 與 Google 18:56 回答：科學怎麼知道自己是對的 科學怎麼知道自己是對的？2015年，兩百多位研究者把一百篇已經發表的心理學研究重做一次，原本幾乎每一篇都有效果，重做之後只剩三分之一多。這一集從休謨的歸納問題講起，經過 Popper 的可否證性、Kuhn 的典範與科學革命，走到再現危機，最後回到 AI 開始提出假說、做實驗的今天。 【說明】畫面全部是程式繪製的扁平插畫，人物是示意角色，不是本人肖像。旁白為 AI 配音，製作流程有使用 AI 工具。「我們自己重做的一次」是本頻道上一集的自測（50 題、每題兩次），只能看大方向。 🎓 講者原聲出處（University of Oxford Podcasts，授權 Creative Commons Attribution-NonCommercial-ShareAlike 2.0 UK: England & Wales，https://creativecommons.org/licenses/by-nc-sa/2.0/uk/ ；片中剪輯片段並加上中英字幕） • Peter Millican，General Philosophy (2018), Lecture 3: Scepticism and Induction，University of Oxford：https://podcasts.ox.ac.uk/genphil-20183-scepticism-and-induction • Peter Millican，General Philosophy (2010), 3.2 Responses to Hume's Famous Argument，University of Oxford：https://podcasts.ox.ac.uk/32-responses-humes-famous-argument • Brian Earp，Solving the Replication Crisis in Psychology: Insights from History and Philosophy of Science，University of Oxford：https://podcasts.ox.ac.uk/solving-replication-crisis-psychology-insights-history-and-philosophy-science 📎 資料來源 • David Hume, An Enquiry Concerning Human Understanding（1748，Project Gutenberg） https://www.gutenberg.org/ebooks/9662 • Bertrand Russell, The Problems of Philosophy（1912）第六章 On Induction（Project Gutenberg） https://www.gutenberg.org/ebooks/5827 • Karl Popper, Science: Conjectures and Refutations（收於 Conjectures and Refutations） https://www.stephenhicks.org/wp-content/uploads/2024/02/PopperK-Science-as-Falsification-text-full.pdf • Stanford Encyclopedia of Philosophy：Karl Popper https://plato.stanford.edu/entries/popper/ • Stanford Encyclopedia of Philosophy：Thomas Kuhn https://plato.stanford.edu/entries/thomas-kuhn/ • Clifford Will：The 1919 measurement of the deflection of light https://arxiv.org/abs/1409.7812 • Daniel Kennefick：Not Only Because of Theory: Dyson, Eddington and the Competing Myths of the 1919 Eclipse Expedition https://arxiv.org/abs/0709.0685 • MacTutor：Urbain Le Verrier https://mathshistory.st-andrews.ac.uk/Biographies/Le_Verrier/ • Open Science Collaboration (2015) Estimating the reproducibility of psychological science, Science https://doi.org/10.1126/science.aac4716 • Begley & Ellis (2012) Raise standards for preclinical cancer research, Nature https://www.nature.com/articles/483531a • Prinz, Schlange & Asadullah (2011) Believe it or not, Nature Reviews Drug Discovery https://doi.org/10.1038/nrd3439-c1 • Errington et al. (2021) Investigating the replicability of preclinical cancer biology, eLife https://elifesciences.org/articles/71601 • Doyen et al. (2012) Behavioral priming: it's all in the mind, but whose mind?, PLoS ONE https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0029081 • Ritchie, Wiseman & French (2012) Failing the future, PLoS ONE；Goldsmiths 新聞稿 https://www.sciencedaily.com/releases/2012/03/120315094737.htm • Scheel, Schijen & Lakens (2021) An excess of positive results, AMPPS https://doi.org/10.1177/25152459211007467 • Sakana AI：The AI Scientist https://sakana.ai/ai-scientist/ • Lu et al. (2026) Towards end-to-end automation of AI research, Nature https://www.nature.com/articles/s41586-026-10265-5 • Google Research：Accelerating scientific breakthroughs with an AI co-scientist https://research.google/blog/accelerating-scientific-breakthroughs-with-an-ai-co-scientist/ • Penadés et al. (2025) AI mirrors experimental science to uncover a novel mechanism of gene transfer crucial to bacterial evolution（bioRxiv） https://www.biorxiv.org/content/10.1101/2025.02.19.639094v1 • Beel et al. (2025) Evaluating Sakana's AI Scientist（arXiv） https://arxiv.org/abs/2502.14297 • Sparks of Weight-Space Programming（部落格，2026-11-02） https://rikiyat.github.io/blog/weight-space-programming/ • 封面影像：Pillars of Creation（2014），NASA、ESA、Hubble Heritage Team，公有領域；Baltic Sea sunrise（Wikimedia Commons，CC BY 2.0）https://commons.wikimedia.org/wiki/File:Baltic_Sea_sunrise_-_16667379220.jpg ；Black Swans (Cygnus atratus)（Wikimedia Commons，CC0）；A group of scientists working in a laboratory（Esculab，Wikimedia Commons，CC0） --- Jim AI Notebook | Note the Future 每日深度解析 AI 最新進展 #科學哲學 #再現危機 #科學方法