I am going to try to write more (and I need your help)

Some..."news?" This little newsletter is close to reaching an extremely modest milestone. About 100 of you now subscribe, and I only know about half of you personally! Given the positive feedback on my last few posts, I'd like to make a go at growing it a bit more, because writing critical tech/media analysis from a place of deep experience is one of the things I most enjoy doing.

Problem is, as most of you will know, it's really hard to get out of your own head and figure out what the heck people really value and want from you. So, I figured I'd just ask: what do you people want from me?!

Okay, I'll be a little more specific than that. If you have the time and inclination, I'd love for you to take a few minutes to respond to this email with short answers to three simple questions:

1. How would you describe what you get out of my writing to a close friend?
2. What do I provide that you value because you don't find it elsewhere, if anything?
3. What do I provide that you think I should stop doing because others do it better, if anything?

Please don't put a lot of time or effort into this – in some ways, your off-the-cuff, gut reactions are more valuable for this exercise than your considered thoughts. And feel free to be as brutally honest as you want. I can take it, hopefully.

One final ask before I get on with some fun stuff: consider recommending me to one other person who you think might enjoy my work. I'm deliberately avoiding the usual growth paths because I really can't tolerate social media. So if this thing is gonna grow, it'll be thanks to you.

Okay, on to the show.

Threads

Er, one more meta note. I'm trying out a new "format" of sorts that I'm just gonna call "Threads" for now. More considered essays like my last piece on the shared ideology of big tech and Trumpism take weeks of time and effort, especially making them short and concise, and I can only do so many given my full-time job. But I frequently find myself wanting to share early versions of the connections I'm making in dialog with folks (including many of you), so I'm going to give myself permission to do quick, paragraph-length hits of half-formed thoughts. You know, Threads! It's specifically not meant to be a "briefing" or "link roundup" or that kind of thing (though there may be links). Not that there's anything wrong with those formats, but so many people do it better than I can. I suspect not every thread will interest all of you. But if any of these resonate with you, please do get in touch and let's go deeper! Right then.

1. Vibe productivity: generative AI is popular because it's good at simulating work. It's an open secret in tech that many well known companies are fabulously unproductive in terms of code shipped. This makes a certain kind of sense. Software isn't a factory. Once you build a profitable platform, you don't actually need to make anything new. You just need to keep the platform online. But shareholders and investors demand growth, so companies keep development teams around to basically pretend to work, even though most actual growth in big tech these days comes from margin-squeezing, not new features. What these teams mostly do is generate artifacts that symbolize productivity: roadmaps, sprint plans, requirements and specifications, pull requests, code reviews, and so on. Some code gets written and pushed to production, but it rarely moves the needle. Maybe a rewrite of a system ekes out a small efficiency gain, or a new login system gets good feedback on a user survey and you have a pizza party. But again, the point of the work isn't really to do the work, it's to demonstrate that people are working, to prove to investors that growth is a function of innovation and not financial engineering. My theory is that over time, in the fashion of Baudrillard, many executives and workers alike have internalized the symbols of productivity as the real thing. So when a tool comes along that can produce the accepted artifacts of productivity much more rapidly and inexpensively than humans, it is celebrated as a massive productivity booster, if not a replacement for humans altogether. In a certain sense, it is both, because like the ones many tech workers produce for a living, the contents of the artifacts it produces aren't the point – the existence of the artifact is. Internalizing this logic is how you get truly idiotic ideas like "vibe physics" and positively comparing knowledge work to video games. I suspect it's also why tech workers are so divided on generative AI, and real businesses keep reporting poor ROI on their implementations. If you're used to actually being productive, not just generating evidence of it, it's hard to understand why so many people are so thrilled that they can save time producing useless documents. But I think we should all be asking a far more important question: when will investors get wise to the fact that many of these companies are running on vibe productivity all the way down, and what will that mean for the industry?
2. Does open science increase public trust in science? I'm about as radical of an advocate for open science as they come, but as conspiracy theorists and right-wing movements continue to weaponize it, it seems worth revisiting some of the basic media theory behind the practice. There's no doubt in my mind that open science – particularly the pre-publication sharing of preprints and data – has accelerated the practice of science. But it's also changed the way science is reported on on and shared. As we've found with the internet and social media generally, and everything from science communication to artificial intelligence, combatting misinformation and even making important decisions specifically, having access to more information does not guarantee better outcomes on its own. And yet many people in open science assume, without much evidence, that transparency and accessibility will automatically lead to increased trust. I don't think we can or should try to stop open science. But I think it's worth considering the impacts of open science on journalist, policymaker and general audiences, and the responsibility researchers, advocates, and infrastructure providers have to understand and mitigate those impacts.
3. American society is not cognitively prepared to deal with actively hostile institutions. I keep having conversations with friends and colleagues who "can't understand" why the Trump administration is doing something stupid and terrible. I keep reading articles that try to decipher Trump's strategy, uncritically report officials’ obviously post-hoc explanations to justify their failures, or worst of all, invent hypothetical strategy for the administration where none exists by trying to divine what it could be from vague inter-agency memos, interviews with friendly officials, and off-the-cuff remarks like some kind of bureaucratic astrology. I understand this tendency to try to apply logic to the administration’s decisions. For most of our lives, America’s executive bureaucracies have acted based on various forms of institutionalism which, while often irrational and Byzantine, at least broadly conformed to a knowable internal logic. It’s far more comfortable to believe that there’s still some semblance of strategy at work, even if it’s terrible, than to admit what’s really happening, which is that this administration is effectively a criminal enterprise run by people whose main goal, when they have one, is to loot the very institutions they lead for their own private gain. The sooner we can come to grips with this reality, the sooner we can stop trying to figure out how to work with these people and get to the urgent work that needs to be done to ultimately reclaim, restore, or replace these institutions: build a movement outside of politics that rallies people to understand just how dangerously hostile and incompetent this administration is and take direct action to oppose it.