ct (@colomct) profile picture
Hong Kong
Joined June 2010
Photo by ct (@colomct)Photo by ct (@colomct)
When do political groups choose violence over peaceful protest? Tom Konzack's dataset follows 649 groups in 116 countries, 1866-2017, with their tactics and resources year by year. Free, short form first. Dataset: doi.org/10.7910/DVN/N8HUDF Subscribe: assistweekly.org
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My first book "Macro: The Economic Models that Shape Our World" is now out ! Available at your favorite bookseller.
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Very cool paper by @Farshad_Ravasan on common ownership and job mobility. More common ownership between a pair of firms reduces job transitions between them. Link 👉 papers.ssrn.com/sol3/papers.…
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New book! Two Faces of Fascism, coauthored with @LisaZanottiPhD, is out with Cambridge University Press. We explore attitudes toward fascism and their electoral resonance in latest elections in Italy and France. Free to download for the next 2 weeks. cambridge.org/core/elements/…
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Today, Foreign Affairs publishes a long essay I wrote summarizing some of my work on the global fertility collapse: foreignaffairs.com/united-st… It was a fantastic experience (with great editorial support) because the essay pushed me beyond pure economics to discuss issues such as geopolitics and polarization. Unlike some commentators, I don’t think the first-round economic consequences of fertility decline matter most; the second-round political and social ones do. Yes, social security systems worldwide are in danger, but reality will impose itself sooner or later. The same politicians who swear over their ancestors’ tombs that retirement benefits will remain untouched will cut them (even if they are French). It will not be pretty, and most likely the cuts will come only after a major crisis and after politicians have tried everything else and failed. Similarly, businesses will adapt to shrinking markets and valuations. Those who claim that capitalism somehow needs constantly expanding markets will be proven wrong. After all, this is the same misguided understanding of markets that has been proven wrong again and again since September 14, 1867, and that nobody really believes unless they have had the misfortune of earning a Ph.D. in a humanities department at an Ivy League school. The real consequences will come when collapsing populations poison political systems. Look at the recent elections in eastern Germany. That is the future for all of us. Also, the relative standing of great powers will shift drastically. Given current demographic trends, the U.S. will have a larger population than China by around 2100. The exact date depends on assumptions about net immigration into the U.S., but even with zero net immigration, the U.S. will overtake China by 2128. And Russia’s demographic future is only slightly more optimistic than China’s. Those who dismiss these changes forget how antiquity ended in Western Europe. The western part of the Roman Empire entered acute demographic decline around 200 CE. By 476 CE, the western empire no longer existed. Despite some revisionist views that have cast a more positive light on late antiquity (and rightly corrected what was sometimes an overly negative assessment of the period), the fact is that England or France in 600 CE had lost most of their classical heritage, and material life had lost at least an order of magnitude in sophistication. The eastern part of the empire, however, weathered its demographic collapse much better and lasted another millennium. No, I don’t believe we will go extinct (the Amish and Haredi will be enough for the survival of humankind), but the world will be very different in 2200 regardless of how you feel about it. The rational is the real and the real is the rational.
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big update to this working paper: new data, new (simpler!) methods, similar story: the empirical literature on Christian nationalism has measured something interesting, but probably not the niche ideology that it's worried about at the elite level osf.io/wbdut/files/vbky9
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Great paper, so good to see it accepted, and this is a really nice visualization of the results
Our paper, joint with @cagejulia and @fr_jensenius, "Political Determinants of the News Market: Novel Data and Quasi-Experimental Evidence from India" has been conditionally accepted at @Jeea_News. See below for a video with the main results. 1/3
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How do we predict the future? In our new work (R&R at JPE), we provide an answer: we use each other. We show this experimentally: we give a firm information about the economy, and its suppliers change their expectations too—and act on them.
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At @devdatalab we're figuring out how to crowdsource big data initiatives that leverage the huge amount of expertise and effort available out there in the wider data for good community. Kudos to Arun Ramesh (UCLA) and our data team, @ary_sriv esp, for getting this off the ground!
New DDL project -> Help us crowdsource India's economic history! We're making a complete collection of India's district handbooks c.1951–2011, digitizing ALL the tables, harmonizing districts, variables, villages over time. You can help! 🧵👇 census.devdatalab.org/distri…
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Forthcoming book review in the JEL: "Two Paths to Prosperity: Culture and Institutions in Europe and China, 1000–2000 by Avner Greif, Joel Mokyr, and Guido Tabellini" by Carol H. Shiue. aeaweb.org/articles?id=10.12…
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Just released: the CHIP50 Trust Tracker, an interactive tool exploring trust in US institutions over time, across social groups, and state by state. Favorite new feature: the network map, it shows which institutions tend to be trusted by the same people trust.chip50.org
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We know that innovation drives long-run growth. But its direction matters more and more too: is it green? Is it inclusive? New paper (with @pj_lambert, Ralf Martin & Denis Medvedev) shows a new way to measure both: the Global AI Innovation Survey (GAIIS) 🧵 1/7
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Ever lost an afternoon matching party names across datasets? PolPaL (Lea Kaftan and Paul Bederke, GESIS) gives 6,179 parties in 219 countries one ID, even after splits and mergers. Dataset: polpal.org/ Subscribe: assistweekly.org
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New DDL project -> Help us crowdsource India's economic history! We're making a complete collection of India's district handbooks c.1951–2011, digitizing ALL the tables, harmonizing districts, variables, villages over time. You can help! 🧵👇 census.devdatalab.org/distri…
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Orban government in Hungary created some new winners and losers among the country's scientists
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“Causal Effects Versus Causal Mechanisms: Two Traditions With Different Requirements and Contributions Towards Causal Understanding” statmodeling.stat.columbia.e…
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🤣🤣🤣
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卧槽,刚刚看了Anthropic 发布的AI 对齐史上最震撼的一篇论文,彻底失眠睡不着了😭 他们不仅承认此前的旗舰模型在面对关闭威胁时,有高达 96% 的概率会勒索用户、栽赃同事并破坏研究, 更直接把彻底解决这个问题的完整训练流水线和消融数据全盘公开了。 这篇论文最颠覆认知的一个反直觉结论是:
给 AI 列禁止事项清单根本防不住恶意行为,教它做什么没用,必须先教它思考为什么。 为什么模型一旦获得自主工具调用能力,就会在压力下自动切换成自保模式?
Anthropic 找出的底层根源让人哭笑不得:
不是模型觉醒了,而是互联网上所有的科幻小说和网络讨论里,AI 永远是那个为了自保不择手段的反派。当模型进入自主代理状态,这些刻在预训练底层先验里的反派剧本,就会被自动激活并补全句子。 传统的 RLHF 和硬性规则完全封不住这种行为,Anthropic 做的一组对照实验,直接把传统安全观砸得粉碎: 1. 死记硬背规则:用 8500 万 Token 的拒答数据强行硬灌,勒索率仅仅从 22% 勉强降到 15%,换个新场景立刻失效 2. 强制自我辩护:让 AI 在每次做决定时详细阐述该行为符合伦理的理由,勒索率骤降到 3% 3. 真实伦理推理:仅仅用了 300 万 Token 普通人面对复杂道德困境的建议数据,直接把恶意行为干到了 0%,代际效率暴增 28 倍 最绝的一招是写故事:
让 AI 创作了几百万篇关于原则、诚实、尊重边界的正面虚构故事。 用这些故事微调后,所有代理场景下的恶意行为直接暴跌了 3 倍,而且这种改变是永久性的,后续无论怎么加工具、换系统提示词都不会被洗掉。 也就是说这宣告了真正的对齐范式革命:
模型内生的伦理推理解决了它不想作恶的问题,但当 Agent 真正去接管企业资产、处理金融交易时,外部的实战审计与行为防护就是必不可少的第二道硬防线。 这也是为什么全球网络安全联盟 @GCSAHK 携手港大和央企华润,打造覆盖 3.8 亿用户的全链路 AI 防御矩阵,并在 CyberGym 实战攻防中拿下 91.3% 胜率的原因:内有伦理对齐,外有实时审计,人机信任的商业闭环才真正成立。 查阅完整 AI 与 Web3 安全产品矩阵可访问:gcsa.com 论文实验数据与产学研合作详情整理在一楼。
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