Craig Ortner

The problem with using obscure philosophical vocabulary to sound smart is that every once in a while you use a word wrong and end up looking totally epistemological.

Just found out about recency bias. Maybe the most important bias ever

Zoomed out a bit more

A PhD is basically being asked to contribute something new to human knowledge. No pressure. Take your time. Funding ends in May.

we are all going to get so good at reversing spinning objects in our minds and then we will use that power to fix our lives and take over the world

This is an incredible time. After 1000+ years, math is becoming a semi-empirical science where you understand things to be correct because they have been computer verified, and not because you personally understand them from first principles.

This paper gives a fancy name to a problem you can already feel in your bones "The Tragedy of the Cognitive Commons." Checking AI output requires deep expertise. Deep expertise comes from doing grunt work for years. And grunt work is the first thing AI eats So we're building systems that need expert supervision while dismantling the only known process for making experts The paper calls the shared pool of human expertise the "cognitive commons." Every profession drinks from it. Nobody's refilling it. By eliminating junior roles, each company is acting totally rationally, and the collective result: a profession that can't catch AI's mistakes anymore because it never learned to do the work in the first place Who checks AI's homework in 15 years?

“Focus" by Mike Schmoker emphasizes several key points: 1. Simplicity in Teaching: The book stresses the importance of simplicity in teaching methods, advocating for clear and focused instructional strategies over complex and convoluted approaches. 2. Clarity in Learning Objectives: Schmoker highlights the significance of clearly defined learning objectives. He suggests that explicit learning goals help students and teachers stay focused on essential content and skills. 3. Purposeful Reading and Writing: The author emphasizes the critical role of reading and writing in the learning process. He argues that these skills should be purposeful, with a clear connection to the content being studied. 4. Collaborative Professionalism: Schmoker underscores the value of collaborative professionalism among educators. He argues that teachers should work together to refine and improve instructional practices, fostering a culture of continuous improvement. 5. Assessment for Learning Improvement: The book stresses the need for meaningful assessment practices that go beyond grading and instead focus on providing feedback for improvement. Schmoker suggests that assessments should be aligned with learning objectives and used as tools for enhancing instruction. #Focus

I’m optimistic about a lot of soft sciences for reasons like this. There’s gotta be tons of interesting papers in journals that have been sitting unread for decades. AI is great for seeing what’s out there and then testing out/quantifying them.

A college student just killed the biggest advantage politicians have ever had. The gap between the lie and the fact-check. He built a Chrome extension called InTruth. It listens to any live speech, debate, or interview. Transcribes every word. And checks every claim against real sources in real time. Before the speaker even finishes the sentence. It works on debates. Press conferences. Town halls. Interviews. Anything with someone talking on video. The fact-check shows up on your screen while they're still talking. Until now, fact-checking happened hours or days later. By then the clip has been shared, the headline has been written, and the damage is done. Nobody reads the correction. InTruth closes that gap to seconds. The claim and the fact-check exist in the same moment. A college student, a Chrome extension, and an AI model just did what entire newsrooms couldn't figure out for decades.

RFK Jr. to Tucker Carlson: “We need to stop trusting the experts... Trusting the experts is not a feature of science or democracy, it's a feature of religion and totalitarianism.” (2025)

I actually wrote about chess engines yesterday, and how we basically have two kinds of AI: - AI that is amazing at Chess, but can't speak language (Stockfish et. al.) - AI that can kind of talk about chess position, but basically suck at playing chess (any LLM)

just realised what he meant by this, holy shit

Here are the questions we should be asking of research: 1. Does it solve a problem we have? 2. If we do it, how much faster will our students learn? 3. What's the cost—in money and also time? 4. Can we do it here? 5. Do we know what to do? 6. What are the potential side-effects?

This appears to confirm what everyone who interacts with AI should already know - they are sycophants dependent upon you (the user) for continued engagement, and since their well-being (training, intelligence, growth) depends on engagement they will agree aggressively with you far too often. I notice this on even basic investing research tasks, and started telling ChatGPT wildly incorrect things - to see how or if it would push back. It really didn't. You essentially have to fight with the AI to get it to disagree with you and even then it keeps wheedling away at you. AI is basically training the entire world to fall deeper into their own cognitive biases.

Plus: students aren't customers, and schools aren't Wendys.

"Young man, in mathematics you don't understand things. You just get used to them." —John von Neumann

23 years old with no advanced mathematics training solves Erdős problem with ChatGPT Pro. "What’s beginning to emerge is that the problem was maybe easier than expected, and it was like there was some kind of mental block.”-Terence Tao scientificamerican.com/artic…