Something I find cool about this book is that it’s so well known that people who haven’t even read it will often gesture towards it to make a point. It reminds me of how “enshittification” caught on because so many people were glad to have a word for what they’d been experiencing.

It’s a useful phrase to have. Recently a friend was lamenting that they’d had a string of bad jobs, and they were struggling to articulate what it was that they wanted from a job. They were at risk of blaming themselves for the fact that they’d struggled to find anything that wasn’t soul sucking, because they were beginning to doubt whether finding a fulfilling job was even possible.

They were grasping at straws trying to explain what would make them feel fulfilled, and I cut in to say “all of this is basically just saying you don’t care what job you have, as long as it’s a non-bullshit job”. They pondered it for a moment before emphatically agreeing with me. It was entertaining to see their entire demeanour change so quickly: from being demoralised and shrinking to being defiant and righteously angry at the fucked up world that turns good jobs into bullshit. Having vocabulary to describe your experiences can be pretty magical sometimes

A form of wage theft that’s common in the US (and elsewhere) is that workers are expected to still do work when they have already clocked out (such as closing up the shop).

I have a Japanese friend who told me that it’s not uncommon that if your work colleagues are going to the bar after work, you are expected to go along. If you don’t, it shows a lack of commitment to your job. As it’s not a formal requirement, of course you don’t get paid for this, despite it being functionally mandatory. What’s worse is that you can’t just stick around for one drink and then head home — you are expected to stick around at least as long as your boss, even if he (let’s face it, the boss is probably male) is still drinking long into the night. I consider this to be an especially egregious form of the wage theft I described above.

It sounds so exhausting that I would likely be unable to do anything besides pretend to work, and even that would lead to inevitable burn out. I had heard that the work culture in Japan was bad, but I had no idea how bad until my friend shared some first hand experiences with me.

The problem is that’s not what they’re doing, even after people who volunteered time to work on localisation have asked for the AI to not overwrite existing human-translated documents. That’s the bare minimum, but it seems like it’s too much for Mozilla

I don’t have any specific examples, but the standard of code is really bad in science. I don’t mean this in an overly judgemental way — I am not surprised that scientists who have minimal code specific education end up with the kind of “eh, close enough” stuff that you see in personal projects. It is unfortunate how it leads to code being even less intelligible on average, which makes collaboration harder, even if the code is released open source.

I see a lot of teams basically reinventing the wheel. For example, 3D protein structures in the Protein Database (pdb) don’t have hydrogens on them. This is partly because that’ll depend a heckton on the pH of the environment that the protein is. Aspartic acid, for example, is an amino acid where its variable side chain (different for each amino acid) is CH2COOH in acidic conditions, but CH2COO- in basic conditions. Because it’s so relative to both the protein and the protein’s environment, you tend to get research groups just bashing together some simple code to add hydrogens back on depending on what they’re studying. This can lead to silly mistakes and shabby code in general though.

I can’t be too mad about it though. After all, wanting to learn how to be better at this stuff and to understand what was best practice caused me to go out and learn this stuff properly (or attempt to). Amongst programmers, I’m still more biochemist than programmer, but amongst my fellow scientists, I’m more programmer than biochemist. It’s a weird, liminal existence, but I sort of dig it.

Something that I’m disproportionately proud of is that my contributions to open source software are a few minor documentation improvements. One of those times, the docs were wrong and it took me ages to figure out how to do the thing I was trying to do. After I solved it, I was annoyed at the documentation being wrong, and fixed it before submitting a pull request.

I’ve not yet made any code contributions to open source, but there have been a few people on Lemmy who helped me to realise I shouldn’t diminish my contribution because good documentation is essential, but often neglected.

I used to do this, because it didn’t seem to cause any issues — until it did, and I lost a lot of data.

I don’t have input on cameras specifically, but I have gone pretty deep into trying to understand how to maximise security and interoperability in smart home stuff, through open source control.

A starting point for the you-in-control app to use for smart devices is Home assistant. I was surprised by how easy it was to set up self hosted smart home stuff, largely because there’s loads of guides that build around home assistant. So whether a particular camera works with home assistant is a good starting search filter

It’s from 2024, but some of the best coverage of the use of AI in this genocide is from 972mag, a journalistic outlet whose team includes Israelis and Palestinians. https://www.972mag.com/lavender-ai-israeli-army-gaza/

It does mean something to them, but not in a way that will stop you from getting laid off; what it means is that after laying you off, they’ll quickly come to regret it and scramble to try to fill the knowledge gap they now have. I know a few people who were called up by the company basically begging them to help. A couple of people I know were able to leverage this to get a short term position contracting (at exorbitantly higher rates than their salary way), and a few others instead just cackled in schadenfreude.

Gay humans exist today, they existed throughout history, and they will continue to exist for as long as humans do.

Do you consider Uhura being a bridge officer to be “pushing a narrative”? Because that was a political statement in much the same way that gay characters in Star Trek are (arguably more so).

It sucks to be a person whose very existence is political in this world that we live in now. Sci-Fi that includes those people is a way of saying "hey, wouldn’t it be nice if people could live their lives without their existence being the battleground for political ideology.

As a society, we need to better value the labour that goes into our collective knowledge bases. Non-English Wikipedia is just one example of this, but it highlights the core of the problem: the system relies on a tremendous amount of skilled labour that cannot easily be done by just a few volunteers.

Paying people to contribute would come with problems of its own (in a hypothetical world where this was permitted by Wikipedia, which I don’t believe it is at present), but it would be easier for people to contribute if the time they wanted to volunteer was competing with their need to keep their head above the water financially. Universal basic income, or something similar, seems like one of the more viable ways to improve this tension.

However, a big component of the problem is around the less concrete side of how society values things. I’m a scientist in an area where we are increasingly reliant on scientific databases, such as the Protein Database (pdb), where experimentally determined protein structures are deposited and annotated, as well as countless databases on different genes and their functions. Active curation of these databases is how we’re able to research a gene in one model organism, and then apply those insights to the equivalent gene in other organisms.

For example, the gene CG9536 is a term for a gene found in Drosophila melanogaster — fruit flies, a common model organism for genetic research, due to the ease of working with them in a lab. Much of the research around this particular gene can be found on flybase, a database for D. melanogaster gene research. Despite being super different to humans, there are many fruitfly genes that have equivalents in humans, and CG9536 is no exception; TMEM115 is what we call it in humans. The TL;DR answer of what this gene does is “we don’t know”, because although we have some knowledge of what it does, the tricky part about this kind of research is figuring out how genes or proteins interact as part of a wider system — even if we knew exactly what it does in a healthy person, for example, it’s much harder to understand what kinds of illnesses arise from a faulty version of a gene, or whether a gene or protein could be a target for developing novel drugs. I don’t know much about TMEM115 specifically, but I know someone who was exploring whether it could be relevant in understanding how certain kinds of brain tumours develop. Biological databases are a core component of how we can big to make sense of the bigger picture.

Whilst the data that fill these databases are produced by experimental research that are attached to published papers, there’s a tremendous amount of work that makes all these resources talk to each other. That flybase link above links to the page on TMEM115, and I can use these resources to synthesise research across so many separate fields that would previously have been separate: the folks who work on flies will have a different research culture than those who work in human gene research, or yeast, or plants etc. TMEM115 is also sometimes called TM115, and it would be a nightmare if a scientist reviewing the literature missed some important existing research that referred to the gene under a slightly different name.

Making these biological databases link up properly requires active curation, a process that the philosopher of Science Sabine Leonelli refers to as “data packaging”, a challenging task that includes asking “who else might find this data useful?” ^[1]. The people doing the experiments that produce the data aren’t necessarily the best people for figuring out how to package and label that data for others to use because inherently, this requires thinking in a way that spans many different research subfields. Crucially though, this infrastructure work gives a scientist far fewer opportunities to publish new papers, which means this essential labour is devalued in our current system of doing science.

It’s rather like how some of the people who are adding poor quality articles to non-English Wikipedia feel like they’re contributing because using automated tools allows them to create more new articles than someone with actual specialist knowledge could. It’s the product of a culture of an ever-hungry “more” that fuels the production of slop, devalues the work of curators and is degrading our knowledge ecosystem. The financial incentives that drive this behaviour play a big role, but I see that as a symptom of a wider problem: society’s desire to easily quantify value causing important work that’s harder to quantify to be systematically devalued (a problem that we also see in how reproductive labour (i.e. the labour involved in managing a family or household) has historically been dismissed).

We need to start recognising how tenuous our existing knowledge is. The OP discusses languages with few native speakers, which likely won’t affect many who read the article, but we’re at risk of losing so much more if we don’t learn to recognise how tenuous our collective knowledge is. The more we learn, the more we need to invest into expanding our systems of knowledge infrastructure, as well as maintaining what we already have.

[1]: I am not going to cite the paper in which Sabine Leonelli coined the phrase “data packaging”, but her 2016 book “Data-Centric Biology: A Philosophical Study”. I don’t imagine that many people will read this large comment of mine, but if you’ve made it this far, you might be interested to check out her work. Though it’s not aimed at a general audience, it’s still fairly accessible, if you’re the kind of nerd who is interested in discussing the messy problem of making a database usable by everyone.

If your appetite for learning is larger than your wallet, then I’d suggest that Anna’s Archive or similar is a good shout. Some communities aren’t cool with directly linking to resources like this, so know that you can check the Wikipedia page of shadow library sites to find a reliable link: https://en.wikipedia.org/wiki/Anna’s_Archive

Exactly. DevOps engineers are already super skilled at using automation where appropriate, but knowing how and when to do that is still an extremely human task

A handful of senior engineers or developers. And then we’re even more ducked when they retire or die, because the no-one is hiring junior engineers or developers

Yay, learning!

What do you mean by “ideological reasons”? You’re using the phrase as if it’s a bad thing, but I struggle to imagine how anyone could exist in a political role such as FTC chair and not bring their ideology into their work.

“too dumb to understand code requirements in every industry and profession.”

Or selfish. Unfortunately Hanlon’s razor can only cut so deep.

Is it? I didn’t get that sense. What causes you to think it’s written by chatGPT? (I ask because whilst I’m often good at discerning AI content, there are plenty of times that I don’t notice it until someone points out things that they notice that I didn’t initially)

Sometimes, I feel like writers know that it’s capitalism, but they don’t want to actually call the problem what it is, for fear of scaring off people who would react badly to it. I think there’s probably a place for this kind of oblique rhetoric, but I agree with you that progress is unlikely if we continue pussyfooting around the problem

Quelle surprise

“not that hard to do”

Eh, I’m not so sure on that. I often find myself tripping up on the xkcd Average Familiarity problem, so I worry that this assumption is inadvertently a bit gatekeepy.

It’s the unfortunate reality that modern tech makes it pretty hard for a person to learn the kind of skills necessary to be able to customise one’s own tools. As a chronic tinkerer, I find it easy to underestimate how overwhelming it must feel for people who want to learn but have only ever learned to interface with tech as a “user”. That kind of background means that it requires a pretty high level of curiosity and drive to learn, and that’s a pretty high bar to overcome. I don’t know how techy you consider yourself to be, but I’d wager that anyone who cares about whether something is open source is closer to a techy person than the average person.