Ben White

The Thin World

10.16.25 // Miscellany

Karl Ove Knausgaard, writing in Harper’s earlier this year:

It feels as if the whole world has been transformed into images of the world and has thus been drawn into the human realm, which now encompasses everything. There is no place, no thing, no person or phenomenon that I cannot obtain as image or information. One might think this adds substance to the world, since one knows more about it, not less, but the opposite is true: it empties the world, it becomes thinner. That’s because knowledge of the world and experience of the world are two fundamentally different things. While knowledge has no particular time or place and can be transmitted, experience is tied to a specific time and place and can never be repeated. For the same reason, it also can’t be predicted. Exactly those two dimensions – the unrepeatable and the unpredictable – are what technology abolishes. The feeling is one of loss of the world.

Knausgaard is best known for his voluminous autobiographical writing (his memoirs are in six[!] volumes). It’s perhaps not surprising then that this piece is less about the and more about his experience of technology. I don’t know about the prediction limitation (Asimov might disagree), but I still think he’s on to something.

One corollary to education is that while simulation is powerful and even necessary, the emotional valence of true experience is impossible to replicate entirely.

All the images I’ve seen of places I’ve never been, people I’ve never met create a kind of pseudomemory from a pseudoworld that I don’t participate in.

We are physical creatures living in a physical world with other physical creatures. The question is—as was perhaps most enjoyably explored in the nostalgia romp that is Ready Player One—how much is lost in the virtual world, how strong is the draw to the physical world, and how much of it do we need to live full lives?

Automate or Collaborate

10.13.25 // Miscellany

Popular essays about AI published in our current media like to cycle between utopianism to massive dystopian automation/disruption to the “plea for collaboration.” The latter, from “A Better Way to Think About AI” by David Autor and James Manyika in The Atlantic:

In any given application, AI is going to automate or it’s going to collaborate, depending on how we design it and how someone chooses to use it. And the distinction matters because bad automation tools—machines that attempt but fail to fully automate a task—also make bad collaboration tools. They don’t merely fall short of their promise to replace human expertise at higher performance or lower cost, they interfere with human expertise, and sometimes undermine it.

This is the no man’s land that explains why articles about AI in medicine don’t reflect reality and why everyone I talk to thinks that all radiologists spend their days awash in useful AI.

Human expertise has a limited shelf life. When machines provide automation, human attention wanders and capabilities decay. This poses no problem if the automation works flawlessly or if its failure (perhaps due to something as mundane as a power outage) doesn’t create a real-time emergency requiring human intervention. But if human experts are the last fail-safe against catastrophic failure of an automated system—as is currently true in aviation—then we need to vigilantly ensure that humans attain and maintain expertise.

The permanent cousin of automation bias will be de-skilling. Pilots who can’t actually take the yoke and land planes anymore are de-skilled. If there is a gap between useful AI and magical super-human AI, then mitigating de-skilling and preventing never-skilling are critical components to any future workflow:

Research on people’s use of AI makes the downsides of this automation mindset ever more apparent. For example, while experts use chatbots as collaboration tools—riffing on ideas, clarifying intuitions—novices often treat them mistakenly as automation tools, oracles that speak from a bottomless well of knowledge. That becomes a problem when an AI chatbot confidently provides information that is misleading, speculative, or simply false. Because current AIs don’t understand what they don’t understand, those lacking the expertise to identify flawed reasoning and outright errors may be led astray.

The seduction of cognitive automation helps explain a worrying pattern: AI tools can boost the productivity of experts but may also actively mislead novices in expertise-heavy fields such as legal services. Novices struggle to spot inaccuracies and lack efficient methods for validating AI outputs. And methodically fact-checking every AI suggestion can negate any time savings.

Beyond the risk of errors, there is some early evidence that overreliance on AI can impede the development of critical thinking, or inhibit learning. Studies suggest a negative correlation between frequent AI use and critical-thinking skills, likely due to increased “cognitive offloading”—letting the AI do the thinking. In high-stakes environments, this tendency toward overreliance is particularly dangerous: Users may accept incorrect AI suggestions, especially if delivered with apparent confidence.

The rise of highly capable assistive AI tools also risks disrupting traditional pathways for expertise development when it’s still clearly needed now, and will be in the foreseeable future. When AI systems can perform tasks previously assigned to research assistants, surgical residents, and pilots, the opportunities for apprenticeship and learning-by-doing disappear. This threatens the future talent pipeline, as most occupations rely on experiential learning—like those radiology residents discussed above.

Learners will not truly learn if they don’t take on tasks independently.

Structured Procrastination

10.09.25 // Miscellany, Writing

From “Structured Procrastination” by John Perry, philosopher and author of The Art of Procrastination (delightfully subtitled: A Guide to Effective Dawdling, Lollygagging and Postponing):

The key idea is that procrastinating does not mean doing absolutely nothing. Procrastinators seldom do absolutely nothing; they do marginally useful things, like gardening or sharpening pencils or making a diagram of how they will reorganize their files when they get around to it. Why does the procrastinator do these things? Because they are a way of not doing something more important. If all the procrastinator had left to do was to sharpen some pencils, no force on earth could get him do it. However, the procrastinator can be motivated to do difficult, timely and important tasks, as long as these tasks are a way of not doing something more important.

Structured procrastination means shaping the structure of the tasks one has to do in a way that exploits this fact. The list of tasks one has in mind will be ordered by importance. Tasks that seem most urgent and important are on top. But there are also worthwhile tasks to perform lower down on the list. Doing these tasks becomes a way of not doing the things higher up on the list. With this sort of appropriate task structure, the procrastinator becomes a useful citizen. Indeed, the procrastinator can even acquire, as I have, a reputation for getting a lot done.

This is the story of my life. Everything I’ve written stems from this reality. This blog started in 2009 to escape studying as a medical student. I even started writing and publishing Twitter fiction (of all things!) to further fit something creative in the cracks of my day.

For most of my life, the easiest way to get anything done was to have an overly full plate and just juggle interesting distractions with the sheer terror of missing deadlines.

In real life, you can—to an exent—choose your community and who you hang out with. Online with social media, that’s much, much harder. This is a good video (“Something Strange Happens When You Trace How Connected We Are”) from Veritasium, and if you’re busy, that link takes you to the section on how the classic Prisoner’s Dilemma works when you add in network effects. Game theory tells us not to feed the trolls.

// 10.03.25

The Failed Experiment of Low Expectations

09.11.25 // Medicine, Miscellany

From “The Perverse Consequences of the Easy A,” published last month in The Atlantic:

When everyone gets an A, an A starts to mean very little. The kind of student that gets admitted to Harvard (or any elite college) wants to compete. They’ve spent their lives clawing upward. Khurana, the former dean, observed that Harvard students want success to feel meaningful. Getting all A’s is necessary, but insufficient.

This has created what Claybaugh called a “shadow system of distinction.” Students now use extracurriculars to differentiate themselves from their peers.

I also cared more about extracurriculars than classes when I was in college, and I graduated back in 2008. Part of it was that the classes were often not all that great and the other stuff was fun, but—

The parallels to pass/fail Step 1 and pass/fail medical schools are obvious. I don’t work with enough students to know if the proposed psychological benefits entirely failed to materialize—certainly the world is complicated and students are wrestling with broader societal trends, the Covid aftermath, social media despair, etc—but the impact on CV buffing is undeniable.

Medical school hasn’t changed all that much over the past century, but it seems like the recent drift in the status quo also isn’t really working?

But even at Harvard, change won’t be easy:

Now that they know that making college easier doesn’t reduce stress, Harvard administrators are attempting to rediscover a morsel of lost wisdom from the ancient past: School should be about academics. In March, the faculty amended the student handbook to emphasize the highly novel point that students should prioritize their schoolwork.

“For many big life choices, we only learn what we need to know after we’ve done it, and we change ourselves in the process of doing it.” – LA Paul

// 09.04.25

Morgan Housel, “Little Ways the World Works”:

Chamath Palihapitiya once noted that however fast your business grows, that’s the half-life for how quickly it can be destroyed. So many companies, flush with cheap money from previous years, are learning this right now. Every business and every industry has a natural growth rate – push beyond it and short-term growth comes at the cost of long-term quality, and eventually survival.

// 07.13.25

Job Unpacking

07.01.25 // Miscellany

From Face it: you’re a crazy person, about the importance of “unpacking” a job to understand your relationship to a potential career:

High-status professions are the hardest ones to unpack because the upsides are obvious and appealing, while the downsides are often deliberately hidden and tolerable only to a tiny minority.

[…]

Making matters worse, people are happy to talk about themselves and their jobs, but they do it at this unhelpful, abstract level where they say things like, “oh, I’m the liaison between development and sales”. So when you’re unpacking someone’s job, you really gotta push: what did you do this morning? What will you do after talking to me? Is that what you usually do? If you’re sitting at your computer all day, what’s on your computer? What programs are you using? Wow, that sounds really boring, do you like doing that, or do you endure it?

How important and yet almost impossible does that sound?There are wide chasms between expectation, perception, and reality. I’m not sure most people are truly psychologically willing to confront unpacking themselves, let alone comprehensively do it for others.