On 2026-05-30, the Mastodon server I run started getting a flood of implausible signup requests. We think these are likely bots because our server rules and signup form clearly tell users to talk about their interest in gay leather. Most people sign up with something like “42 yo levis enthusiast into piss” or “Hi! I’m Snoofles the pup! I love bones and being a good girl for Madam!”. Instead the applications are either friendly, generic text… I value online communities that are moderated with care and that encourage constructive interaction. I plan to use my account to share interesting stuff,…
Back in 2023, I hired Flat Rate Movers (A.K.A. Flat Rate Moving) for an interstate move. They subcontracted to a third party who showed up under-staffed, under-equipped, and very confused; the whole mess wound up causing a good deal of damage to my belongings and home. I filed a claim with Flat Rate and also requested they issue a partial refund. They refused to talk to me or their insurance company, and after six months of calling, emailing, and writing, I got overwhelmed by other life struggles and gave up. I did manage to file a claim with their backing insurance company, but got nothing…
This video is brought to you by PodPitch, the AI-powered platform for PR experts. PodPitch is the first and only software that finds, writes, and sends pitches to podcast hosts from your actual email address. Whether or not you’re already pitching podcasts, PodPitch will make sure you get podcast bookings – guaranteed. And so long as PodPitch’s AI keeps confusing me with Kyle Kingsbury, MMA fighter and famous podcast host, some of those bookings… just might be with me. My name is Kyle Kingsbury, I am not as popular nor ruggedly handsome as Kyle Kingsbury, and I have never hosted a podcast in…
For the last few weeks publicists have bombarded me with emails asking if I’d interview their clients on the Kyle Kingsbury podcast. While my name is Kyle Kingsbury, and I have been a guest on several podcasts, I’ve never hosted one myself. I called one of the PR firms to ask if they might have me confused with the MMA fighter of the same name, but the woman I reached was so friendly and eager to tell me about all the potential guests I might interview and, well… things just got out of hand. Now I’m doing background research, writing questions, learning Riverside, and struggling mightily to…
This has been bugging me for years: you often run a JVM by a shell script wrapper, then want to jstack it to figure out what it’s doing, but can’t figure out what PID to ask for. Running jps gives remarkably unhelpful output, especially for tools like Leiningen. I wrote a hacky little Ruby script to dig into the process tree of everything matching a given pattern, find any JVMs those processes spawned, and hit the highest numbered one (presumably the last one started) with jstack. This is definitely wrong (PID rollover!) but it’s been surprisingly useful for debugging. $ jstack+ lein test…
Table of Contents This is a long article, so I've broken it up into a series of posts, listed below. You can also read the full work as a PDF or EPUB. Introduction Dynamics Culture Information Ecology Annoyances Psychological Hazards Safety Work New Jobs Where Do We Go From Here Previously: New Jobs. Some readers are undoubtedly upset that I have not devoted more space to the wonders of machine learning—how amazing LLMs are at code generation, how incredible it is that Suno can turn hummed melodies into polished songs. But this is not an article about how fast or convenient it is to drive a…
Table of Contents This is a long article, so I've broken it up into a series of posts, listed below. You can also read the full work as a PDF or EPUB. Introduction Dynamics Culture Information Ecology Annoyances Psychological Hazards Safety Work New Jobs Where Do We Go From Here Previously: Work. As we deploy ML more broadly, there will be new kinds of work. I think much of it will take place at the boundary between human and ML systems. Incanters could specialize in prompting models. Process and statistical engineers might control errors in the systems around ML outputs and in the models…
Table of Contents This is a long article, so I've broken it up into a series of posts, listed below. You can also read the full work as a PDF or EPUB. Introduction Dynamics Culture Information Ecology Annoyances Psychological Hazards Safety Work New Jobs Where Do We Go From Here Previously: Safety. Software development may become (at least in some aspects) more like witchcraft than engineering. The present enthusiasm for “AI coworkers” is preposterous. Automation can paradoxically make systems less robust; when we apply ML to new domains, we will have to reckon with deskilling, automation…
Table of Contents This is a long article, so I've broken it up into a series of posts, listed below. You can also read the full work as a PDF or EPUB. Introduction Dynamics Culture Information Ecology Annoyances Psychological Hazards Safety Work New Jobs Where Do We Go From Here Previously: Psychological Hazards. New machine learning systems endanger our psychological and physical safety. The idea that ML companies will ensure “AI” is broadly aligned with human interests is naïve: allowing the production of “friendly” models has necessarily enabled the production of “evil” ones. Even…
Table of Contents This is a long article, so I've broken it up into a series of posts, listed below. You can also read the full work as a PDF or EPUB. Introduction Dynamics Culture Information Ecology Annoyances Psychological Hazards Safety Work New Jobs Where Do We Go From Here Previously: Annoyances. Like television, smartphones, and social media, LLMs etc. are highly engaging; people enjoy using them, can get sucked in to unbalanced use patterns, and become defensive when those systems are critiqued. Their unpredictable but occasionally spectacular results feel like an intermittent…
Table of Contents This is a long article, so I've broken it up into a series of posts, listed below. You can also read the full work as a PDF or EPUB. Introduction Dynamics Culture Information Ecology Annoyances Psychological Hazards Safety Work New Jobs Where Do We Go From Here Previously: Information Ecology. The latest crop of machine learning technologies will be used to annoy us and frustrate accountability. Companies are trying to divert customer service tickets to chats with large language models; reaching humans will be increasingly difficult. We will waste time arguing with models.…
Table of Contents This is a long article, so I've broken it up into a series of posts, listed below. You can also read the full work as a PDF or EPUB. Introduction Dynamics Culture Information Ecology Annoyances Psychological Hazards Safety Work New Jobs Where Do We Go From Here Previously: Culture. Machine learning shifts the cost balance for writing, distributing, and reading text, as well as other forms of media. Aggressive ML crawlers place high load on open web services, degrading the experience for humans. As inference costs fall, we’ll see ML embedded into consumer electronics and…
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