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Cake day: June 9th, 2023

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  • I agree that season 1 is far more engaging but imo, that’s mainly because the level of intrigue that I felt at the beginning of the story was insane — they were great at keeping that intrigue rolling in an interesting way. But that kind of mystery can only last so long, because it grows weaker as the audience learns more about the characters and world.

    I think there was a part of me that felt disappointed by season 2 simply by the fact it couldn’t give me what I felt during season 1, and actually, I wouldn’t want that — the final episodes of a series shouldn’t have the same kind of tension of the beginning of the story.

    Overall, I’d say that season 1 is excellent (in particular, there were some visually impressive and stylish sequenced that I loved) — Riveting" was the word OP used. Season 2 is also decent. I don’t recall it feeling rushed, and it does end decently.



  • I didn’t especially hate Wesley, but I also didn’t enjoy his character. Part of it is that the narrative often framed Wesley from the perspective of Picard, who often seemed to be irked by Wesley, priming the audience to feel the same way. In many of his earlier appearances, before he was a cadet, I recall some Wesley plots involving him being over-keen and meddling with things he shouldn’t. But it all turns out fine in the end, because Wesley is so precocious and special. This is likely a reductionist and possibly incorrect summary, but it’s how I remember it.

    When I try to think about faults or arcs that Wesley had in TNG, I really struggle to think of anything that made him feel like an actual character. There was an episode where he was considering giving up after doing badly on the academy entrance test, until he had a rare bonding moment with Picard. Then there was the academy shuttle crash coverup in which Wesley doesn’t feel like he has any real agency or real conflict for his character.

    I agree with you that his key role was about giving the family aspect, which I think was useful, but especially when combined with the young genius trope, he felt more like a prop than a real character (part of this criticism is also aimed at how they explored themes of family through Beverly — I see what they were going for, but it didn’t fully land for me).

    Now that I’m writing this, I’m thinking of episodes I wish I could’ve seen to develop Wesley more. Such as a “Lower Decks” (the TNG episode) style look at other young people on the enterprise, before Wesley is allowed on the bridge. I could see him framing himself as having more access or knowledge than he actually does and lying to make himself seem impressive to his peers. Then he gets peer pressured into doing some dumb stuff to gain that access he pretends to have, and it causes complications that threaten to reveal Wesley’s deceit to both the crew and his peers.

    I’m just spitballing. My main point is just that he seemed simultaneously overused and underutilised — for the screen time he gets, he doesn’t really get to be an interesting character. He doesn’t need to be edgy — idealistic boy genius who can’t wait to join Starfleet fits in great with TNG’s general tone. However, without something to temper the optimism with, TNG could be saccharine sweet.


  • Something I’ve thought about a bunch re: recommendation engines is the idea of a “sweet spot” that balances exploration and safety

    Though actually I should start by saying that recommendation engines tend to aim to maximise engagement, which is why manosphere type content is so prevalent on places like YouTube if you go in with a fresh account — outrage generates engagement far more reliably than other content. I’m imagining a world where recommendation algorithms may be able to be individually tailored and trained, where I can let my goals shape the recommendations. I did some tinkering with a concept like this in the context of a personal music recommender, and I gave it an “exploration” slider, where at maximum, it’d suggest some really out-there stuff, but lower down might give me new songs from familiar artists. That project worked quite well, but it needs a lot of work to untangle before I can figure out how and why it worked so well.

    That was a super individualistic program I made there, in that it was trained exclusively from data I gave it. One can get individual goals without having to rely on the data of just one person though - listenbrainz is very cool — its open source, and they are working on recommendation stuff (I’ve used listenbrainz as a user, but not yet as a contributor/developer)

    Anyway, that exploration slider I mentioned is an aspect of the “sweet spot” I mentioned at the start. If we imagine a “benevolent” (aligned with the goals of its user) recommendation engine, and say that the goal you’re after is you want to listen to more diverse music. For a random set of songs that are new to you, we could estimate how close they are to your current taste (getting this stuff into matrices is a big chunk of the work, ime). But maybe one of the songs is 10 arbitrary units away from the boundary of your “musical comfort zone”. Maybe 10 units is too much too soon, too far away from your comfort zone. But maybe the song that’s only 1 unit away is too similar to what you like already and doesn’t feel stimulating and exciting in the way you expect the algorithm to feel. So maybe we could try what we think is a 4 or 5. Something novel enough to be exciting, but still feels safe.

    Research has shown that recommendation algorithms can change affect our beliefs and our tastes [citation needed]. I got onto the music thing because I was thinking about the power in a recommendation algorithm, which is currently mostly used on keeping us consuming content like good cash cows. It’s reasonable that so many people have developed an aversion to algorithmic recommendations, but I wish I could have a dash of algorithmic exploration, but with me in control (but not quite so in control as what you describe in your options 3). As someone who is decently well versed in machine learning (by scientist standards — I have never worked properly in software development or ML), I think it’s definitely possible.


  • Mine work somewhat okayish, which is within the margin of error I need them for. I think there was one that was terrible though.

    Mostly I use them for the temperature aspect, mostly for reminding me if it’s too hot or cold in my room (because due to my autism, I often don’t notice whether I’m at a comfortable temperature). I have a few scattered about my room and basically they act as a visual prompt to consciously ask myself if I’m at a comfortable temperature, and to act as a rough backup to whatever I’m feeling (because even when I’m consciously aware that my temperature is feeling Bad, I can’t reliably tell whether I’m too hot or cold, so these terrible thermometers at least help me answer “should I get a blanket, or open a window?”


  • I agree with you about the core of the problem, but the reason the monopoly is the thing being focussed on is because that’s the legal basis against Google that we have right now (speaking as someone who enthusiastically followed the proceedings).

    The crucial bit now that Google has been deemed an illegal monopolist is how this gets resolved, because of the possible remedies to this situation, some are better for user privacy, and some are worse. This is an opportunity to do some real good here on that front.

    Unfortunately, as I understand it, actually getting to a solution will take time, because of how Google will try to haggle down whatever remedy is suggested. This seems likely to be easier to do under a Trump administration.






  • When I was a teenager, the youth centre I went to did an activity where in teams, we had to come up with as many insulting words or phrases as possible (swearing was fine, slurs weren’t). Naturally we responded to this challenge with glee and came up with many insults. Afterwards, we reviewed all the phrases and sorted them into categories, showing that the vast vast majority of insults belonged to just a few categories (one of the largest of which being disability).

    Thanks for posting your comment. Ever since that youth centre session, I’ve been acutely aware of how ableist language can sneak its way into my vocabulary (and being disabled doesn’t exempt me from that risk), and yet I still find myself slipping up sometimes because of how normalised ableist language is.


  • To some extent, I don’t.

    Which is to say that in and around my field (biochemistry), I’m pretty good at sort of “vibe checking”. In practice, this is just a subconscious version of checking that a paper is published in a legit journal, and having a sense for what kind of topics, and language is common. This isn’t useful advice though, because I acquired this skill gradually over many years.

    I find it tricky in fields where I am out of element, because I am the kind of person who likes to vet information. Your question about how to identify work as peer reviewed seems simple, but is deceptively complex. The trick is in the word “peer” — who counts as a peer is where the nuance comes in. Going to reputable journals can help, but even prestigious journals aren’t exempt from publishing bullshit (and there are so many junk journals that keeping up even within one field can be hard). There are multiple levels of “peer”, and each is context dependent. For example, the bullshit detector that I’ve developed as a biochemist is most accurate and efficient within my own field, somewhat useful within science more generally, slightly useful in completely unrelated academic fields. I find the trick is in situating myself relative to the thing I’m evaluating, so I can gauge how effective my bullshit detector will be. That’s probably more about reflecting on what I know (and think I know) than it is about the piece of material I’m evaluating.

    In most scenarios though, I’m not within a field where my background gives me much help, so that’s where I get lazy and have to rely on things like people’s credentials. One litmus test is to check whether the person actually has a background in what they’re talking about, e.g. if a physicist is chatting shit about biology, or a bioinformatician criticising anthropology, consider what they’re saying with extra caution. That doesn’t mean discount anyone who isn’t staying in their lane, just that it might be worthwhile looking into the topic further (and seeing who else is saying what they are, and what experts from the field are saying too).

    As I get deeper into my academic career, I’ve found I’m increasingly checking a person’s credentials to get a vibe check. Like, if they’re at a university, what department are they under? Because a biochemist who is under a physics department is going to have a different angle than one from the medical research side, for example. Seeing where they have worked helps a lot.

    But honestly a big part of it is that I have built up loose networks of trust. For example, I’m no statistician, but someone I respect irl referenced a blog of Andrew Gelman’s, which I now consider myself s fan of (https://statmodeling.stat.columbia.edu/). Then from that blog, I ended up becoming a fan of this blog, which tends to be about sociology. Trusting these places doesn’t mean I take them at face value for anything they say, but having that baseline of trust there acts as a sort of first pass filter in areas I’m less familiar with, a place to start if I want to learn about a perspective that I know the rough origin of.

    In the context of news, I might start to see a news outlet as trustworthy if I read something good of theirs, like this piece on 3M by ProPublica, which makes me trust other stuff they publish more.

    Ultimately though, all of these are just heuristics — imperfect shortcuts for a world that’s too complex for straightforward rules. I’m acutely aware of how little spare brain space I have to check most things, so I have to get lazy and rely on shortcuts like this. In some areas, I’m lucky to have friends I can ask for their opinion, but for most things, I have to accept that I can’t fact check things thoroughly enough to feel comfortable, which means having to try holding a lot of information at arms length and not taking it as fact. That too, takes effort.

    However, I got a hell of a lot smarter when I allowed myself to be more uncertain about things, which means sometimes saying “I don’t know what to make of that”, or “I think [thing] might be the case, but I don’t remember where I heard that, so I’m unsure”, or just straight up “I don’t know”. Be wary of simple and neat answers, and get used to sitting with uncertainty (especially in modern science research).





  • “Or, you could keep whining about how these people have no empathy for you.”

    When OP speaks of allies not being allies, it’s comments like yours that I think of. You use “we” like we’re on the same side here, but (ironically given you say this of OP) you have missed their entire point.

    We’re not going to survive (let alone make progress) if we tear each other down like this. This isn’t me saying “they go low, we go high” nonsense, because you’re quite right that relying Trump voters to show empathy doesn’t look like a good strategy. I don’t see that OP was actually saying anything of the sort though. This is about how we (people opposing Trump and co.) treat each other. It would be easier for us to become practiced and educated if we could rely on the people who are meant to be allies.

    I want to believe that you’re a decent person who wrote an assholish comment. It happens to the best of us. I hope that you’ll reread OP’s comment and your own and see how unproductive this approach is for everyone. But maybe I’m wasting my time here, in much the same way that expecting empathy from Trump voters is probably unwise. That’s up to you, I guess





  • I read somewhere that someone’s attitude to furries is a great litmus test for how tolerant that person actually is (assuming that person isn’t a furry, of course). I’ve always found myself mildly confused by furries (and I used to be somewhat weirded out because I mainly knew of furries because a friend bought a house from drawing furry porn). Hearing the litmus test thing helped me to chill out a bunch and recognise that seeing lots of furries in and adjacent to my community was a sign of a healthy social ecosystem, so to speak