I think centralization played a big role in this, at least for software. When messaging meant IRC, AIM, Yahoo, MSN, Xfire, Ventrilo, TeamSpeak, or any number of PHP forums, you had to be able to pick up new software quickly and conceptualized the thing it’s doing separate from the application it’s accomplished with. When they all needed to be installed from different places in different ways you conceptualize the file system and what an executable is to an extent. When every game needs a bit of debugging to get working and a bit of savvy to know when certain computer parts are incompatible, you need a bit of knowledge to do the thing you want to do.

That said, fewer people did it. I was in highschool when Facebook took off, and the number of people who went from never online to perpetually online skyrocketed.

I teach computer science, I know it isn’t wholly generational, but I’ve watched the decline over the past decade for the basics. Highschool students were raised on Chromebooks and tablets/phones and a homogenous software scene. Concepts like files, installations, computer components, local storage, compression, settings, keyboard proficiency, toolbars, context menus - these are all barriers for incoming students.

The big difference, I think, is that way more people (nearly everyone) has some technical proficiency, whereas before it was considered a popular enough hobby but most people were completely inept, but most of students nowadays are not proficient with things past a cursory level. That said, the ones who are technically inclined are extremely technically inclined compared to my era, in larger numbers at least.

Higher minimum and maximum thresholds, but maybe lower on average.

Yeah, that’s definitely the way to see it, and as that I think it’s great. I think it might overload the term dark patterns a bit too much, and would have liked to have seen a different name used (as a game design academic), but I absolutely agree with and appreciate the approach otherwise.

Edit to include, I guess why I have that hesitation with an example - I couldn’t link this in a class I’m teaching without loads of caveats because suddenly 80% of the curriculum gets seen as abusive when it’s really just experience design and explain the grey (which we do, so this is quite helpful for that particular purpose), and I would need to caveat that when they see the term out in the wild it will be used differently.

Interesting. I was chatting with a lot of big name AAA designers and indie designers discussing dark patterns, and they’ve got a very different opinion on what constitutes a dark pattern. To them, largely, it needs to be more technical deception - like having a fake “X” button, or immediately popping up an ad over where a button was to trick you into clicking it, or bait-and-switching pricing before the user notices.

I tried to raise these kinds of patterns as problematic, and it was a mixed bag. The general vibe from them was that they’d only call it a dark pattern if it deceives the player to get more money than they were prepared to spend (or similar for ads). If the player knows what they’re getting into, and they are presented with a choice to stop or continue, it’s on them.

And I’ll admit, while I don’t go that far (and there were designers in both camps), I can at least understand how all game design is manipulation, in the same way that teaching and storytelling is manipulation, and drawing the lines can be very hard. Your job is to convince the player that they are having fun and want to keep playing. Resources in a game have no real value, only valued by the scarcity and utility of them, which the designer intentionally assigns to convince the player it’s more or less valuable.

Curiously, the examples listed in the OP were exactly the patterns I see designers discuss, but don’t seem to be the patterns on the website (like “illusion of control”, artificial scarcity, which is like, game designs while thing).

Either way, nice to have this as a resource because honestly a lot of these elements are what I’d put in the “bad / abusive design” category rather than purely dark patterns, but still great to highlight, but I can agree that we should probably be careful blanket calling these dark patterns; examples: It mentions illusion of control being separating you into shards of leader boards so that you can be in the top 500 of a shard rather than top 200,000 world ranking or whatever, or claw machines choosing whether you successfully grab an item rather than relying on skill. How does this compare to Uncharted not letting enemies successfully shoot you in the first few seconds of an action sequence to give you time to ground yourself, or Resident Evil spawning different loot and enemies based on how good/bad you play?

I’d say, is it to extract money from you in the short term, but it’s more grey than a non-designer might read into from lists like these.

I love that friend group A is a gradient.

I’m Canadian, but the point they are making is that there won’t be another election; VP is the backup for a dead president. Not to tinfoil too hard, but placing an obvious puppet in as VP with a clearly declining candidate who is popular seems like a strategy straight out of House of Cards.

Geode colouring matched Ace Flag colouring.

Insane compute wasn’t everything. Hinton helped develop the technique which allowed more data to be processed in more layers of a network without totally losing coherence. It was more of a toy before then because it capped out at how much data could be used, how many layers of a network could be trained, and I believe even that GPUs could be used efficiently for ANNs, but I could be wrong on that one.

Either way, after Hinton’s research in ~2010-2012, problems that seemed extremely difficult to solve (e.g., classifying images and identifying objects in images) became borderline trivial and in under a decade ANNs went from being almost fringe technology that many researches saw as being a toy and useful for a few problems to basically dominating all AI research and CS funding. In almost no time, every university suddenly needed machine learning specialists on payroll, and now at about 10 years later, every year we are pumping out papers and tech that seemed many decades away… Every year… In a very broad range of problems.

The 580 and CUDA made a big impact, but Hinton’s work was absolutely pivotal in being able to utilize that and to even make ANNs seem feasible at all, and it was an overnight thing. Research very rarely explodes this fast.

Edit: I guess also worth clarifying, Hinton was also one of the few researching these techniques in the 80s and has continued being a force in the field, so these big leaps are the culmination of a lot of old, but also very recent work.

Lots of good comments here. I think there’s many reasons, but AI in general is being quite hated on. It’s sad to me - pre-GPT I literally researched how AI can be used to help people be more creative and support human workflows, but our pipelines around the AI are lacking right now. As for the hate, here’s a few perspectives:

• Training data is questionable/debatable ethics,
• Amateur programmers don’t build up the same “code muscle memory”,
• It’s being treated as a sole author (generate all of this code for me) instead of like a ping-pong pair programmer,
• The time saved writing code isn’t being used to review and test the code more carefully than it was before,
• The AI is being used for problem solving, where it’s not ideal, as opposed to code-from-spec where it’s much better,
• Non-Local AI is scraping your (often confidential) data,
• Environmental impact of the use of massive remote LLMs,
• Can be used (according to execs, anyways) to replace entry level developers,
• Devs can have too much faith in the output because they have weak code review skills compared to their code writing skills,
• New programmers can bypass their learning and get an unrealistic perspective of their understanding; this one is most egregious to me as a CS professor, where students and new programmers often think the final answer is what’s important and don’t see the skills they strengthen along the way to the answer.

I like coding with local LLMs and asking occasional questions to larger ones, but the code on larger code bases (with these small, local models) is often pretty non-sensical, but improves with the right approach. Provide it documented functions, examples of a strong and consistent code style, write your test cases in advance so you can verify the outputs, use it as an extension of IDE capabilities (like generating repetitive lines) rather than replacing your problem solving.

I think there is a lot of reasons to hate on it, but I think it’s because the reasons to use it effectively are still being figured out.

Some of my academic colleagues still hate IDEs because tab completion, fast compilers, in-line documentation, and automated code linting (to them) means you don’t really need to know anything or follow any good practices, your editor will do it all for you, so you should just use vim or notepad. It’ll take time to adopt and adapt.

Everything changed when I found the most understanding teachers at the end of my school. I switched schools and had a teacher recognize I was smart and bored and distracted, and she tested me out of the classes and let me spend my time on other random things that were tangentially related and still work with the other students. Game changer compared to where I was where I’d get deductions for doing problems early or reading ahead.

The point on the way to many interests and things, and loving yourself beyond the meds, very important! I found o was regulating myself too much for the first while after diagnosing, and the most relaxation wasn’t what people might typically find relaxing, it was letting the (healthy enough) chaos flow in a safer environment than I was previously prepared to setup.

100%. Great way of putting it. I bounce back forth on occasion, but the trend line is always toward accepting that old part of me, and realizing it’s okay to move on because it’s a very closed chapter that’s been outstaying its welcome. Like any death, you still have those same neural patterns, and they’re slowly getting overwritten, and it’s confusing and disorienting when your muscle memory reaches for something and it’s not there.

It’s extra confusing when what’s reached for is that feeling of not grabbing anything, but you do. When you’ve been falling for decades the ground feels weird for a while when you land.

I definitely feel like a big part of what I’ve grieved is the childhood that I never had, moreso than the future I won’t. It was a big relief, and I felt like I could do well and cut myself slack. I’m just trying to do the same with past me; cut myself that slack, give my past self that love and understanding now that I didn’t get then, accept it was a brutal time, and that it was unfair, but that I’ve grown and learned and stopped rejecting that person was me, and we’re doing all right.

Absolutely! Important to recognize you’re not “weird” for not going through this, sometimes it just aligns so well you’re already prepped for it.

I agree to an extent, but also that the parents need to take time to understand how to “gas them up” appropriately. It’s not everyone’s case, but it became very apparent to me when I was young that my parents would cheer me on over anything, and never take any time to learn about the things they were cheering me on over, and that led to disbelieving pretty much any positive feedback from anyone long-term. The only feedback of substance growing up was the very rare negative feedback, because they would only pull it out when they understood it enough to know it needed improving. That, and emphasizing their efforts as the thing to cheer on, not just the end results.

I’ve learned to work through that, and maybe it goes without saying for most people, but being a genuine and substantive cheerleader is important.

I know this is in response to a post saying your ADHD is not other people’s ADHD, but I’m pretty sure your ADHD is my ADHD.

As someone who researched AI pre-GPT to enhance human creativity and aid in creative workflows, it’s sad for me to see the direction it’s been marketed, but not surprised. I’m personally excited by the tech because I personally see a really positive place for it where the data usage is arguably justified, but we either need to break through the current applications of it which seems more aimed at stock prices and wow-factoring the public instead of using them for what they’re best at.

The whole exciting part of these was that it could convert unstructured inputs into natural language and structured outputs. Translation tasks (broad definition of translation), extracting key data points in unstructured data, language tasks. It’s outstanding for the NLP tasks we struggled with previously, and these tasks are highly transformative or any inputs, it purely relies on structural patterns. I think few people would argue NLP tasks are infringing on the copyright owner.

But I can at least see how moving the direction toward (particularly with MoE approaches) using Q&A data to support generating Q&A outputs, media data to support generating media outputs, using code data to support generating code, this moves toward the territory of affecting sales and using someone’s IP to compete against them. From a technical perspective, I understand how LLMs are not really copying, but the way they are marketed and tuned seems to be more and more intended to use people’s data to compete against them, which is dubious at best.

Not to fully argue against your point, but I do want to push back on the citations bit. Given the way an LLM is trained, it’s not really close to equivalent to me citing papers researched for a paper. That would be more akin to asking me to cite every piece of written or verbal media I’ve ever encountered as they all contributed in some small way to way that the words were formulated here.

Now, if specific data were injected into the prompt, or maybe if it was fine-tuned on a small subset of highly specific data, I would agree those should be cited as they are being accessed more verbatim. The whole “magic” of LLMs was that it needed to cross a threshold of data, combined with the attentional mechanism, and then the network was pretty suddenly able to maintain coherent sentences structure. It was only with loads of varied data from many different sources that this really emerged.

Mainly learning that I did, in fact, have ADHD, Then: medication (Vyvanse); drastically reducing or cutting weed, alcohol, and caffeine; therapy to help deal with childhood issues (which exacerbate symptoms); taking time away from work to start recovering from ADHD-driven burnout and building some structures to support my ADHD in the workplace.

Systems to externalize things. I’ve accepted that if I don’t see something, it isn’t happening, so I try to arrange and organize things in a way that it’s physically out in the world for me. Digital doesn’t work extremely well for me for the most part, except for some work things where it’s all in one place, because digital disappears from existence when the screen turns off.

I hate it, but regular exercise, eating more healthy, and the nights where I can actually sleep are probably the biggest factors in whether I have a good day or not. Not that knowing that is enough, of course.

Oh, and just generally learning what my weaknesses are. I’m still hugely struggling with ADHD overall, but knowing the big weaknesses helps. It’s not about doing what’s easy, it’s about facing what’s hard head-on and accepting it sucks, but you have to go on.

• I struggle with transitioning, so random text messages or having to sporadically decide to move from Task A to Task B is hard/impossible, so I have scheduled socializing and build in transition “rituals” like going for a walk, having lights and TV automatically turn off at set times,
• I get stuck on tasks, so hard rules like “Under no circumstances can you do this after X time” are vital to live by, when you can,
• I don’t notice bodily needs, so practicing meditation and having regular reminders to check-in on myself help to make sure I’ve eaten / drank water / walked around and generally am not hurting my body with whatever weird way I’m sitting,
• I’m terrible with detail-oriented work, so I have workflows specifically designed to reduce the amount of detail-oriented work I need to do,
• I binge a ton of work in short periods and rest for periods, so I moved my career toward flexible scheduling to allow for this, with enough accountability to have deadlines I can’t violate.