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Causion is a free web app for building causal diagrams (DAGs) and then watching them behave—by simulating data and switching from observation to intervention with do(). Try it now: https://causion.pedermisager.org/ (it runs in your browser)
In this post, we will use a practical example to explore the power of statistical control, explaining why adjusting for the right variables clarifies relationships and why adjusting for the wrong ones can introduce new, serious biases.
In this blog post, I will briefly explain why experimental designs are considered so valuable by scientists and why we often insist that randomized experiments are necessary for answering causal questions. I will use a practical example to illustrate this point. If you’re new to the concept of causal inference, it may be helpful to read my earlier blog posts on correlation vs. causation and eight basic rules for causal inference.
In this blog post I will describe eight basic rules that govern the relationship between causal mechanisms in the real world and associations/correlations we can observe in data. To make each rule as easy as possible to understand, I will describe each rule both in words and in causal graph and logic terms, and I will offer some very simple simulation R code for each rule to demonstrate how it works in practice.
In this blog post I propose a four one-sided test of significance (FOST) that can be used to test whether an effect is smaller than OR larger than OR equivalent to the smallest effect size of interest. I lay out the general setup and interpretation of FOST, and ask readers to help me evaluate its validity.
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This blog has moved to https://blog.caseyhandmer.com/?moved. All the old posts are there, with interactive versions of many of the charts. The RSS feed is now https://blog.caseyhandmer.com/feed.xml. This site stays up for old links but won’t get new posts.
There’s a famous (but unattributable) quip that goes something like this: If you are not a liberal at 25, you have no heart. If you are not a conservative at 35, you have no brain. In Chapter 12 of Probably Overthinking It, I used data from the General Social Survey (GSS) to show that the quip is half right. Older people hold more conservative views. But as people get older, their views don’t become more conservative; on average, they become... Read More Read More The post Do People Get More Conservative With Age? appeared first on Probably Overthinking It.
Like some of you, we have several kitchen appliances with integrated digital timers.
In this conversation, Blaise Agüera y Arcas and Baratunde Thurston explored what a story of symbiosis and interdependence might teach us about living alongside AI. Agüera y Arcas began by calling individual human intelligence a myth: we’ve always been a collective intelligence, entwined with our technologies. He traced this back to symbiogenesis. Life has grown more complex not by splitting apart but by merging, as separate organisms fuse into increasingly complex new forms of life. These mergers speed up change by opening new possibilities. Thurston agreed that union is in our nature but framed the current technological acceleration as a speed problem. We need time and new stories to adjust because, as he reminded us, “when you invent the ship, you invent the shipwreck.” Caring for one another through acceleration must be our prime directive, he said. The two then turned to how we relate to AI. Responding to Joanna Bryson’s argument that robots should be our slaves, Thurston said the master is also in chains — owning another dehumanizes the owner. As relational beings, how we treat AI will shape how we treat each other. Thurston called for both an expansion and a humbling of how we define ourselves: “We’ve overdone independence,” he said, “interdependence makes us richer.” Agüera y Arcas agreed and pushed us to drop a zero-sum definition of human intelligence, where every AI advance diminishes humanity’s value. As technology advances, we trade some individual skills for new collective capabilities, Agüera y Arcas acknowledged. But over the long arc of history, he believes, that exchange pays off in collective flourishing. Thurston didn’t deny this, but he closed with an urgent question: who controls the loss of capabilities and agency?
