For me, it tracks, but the caveat is a high increase in burnout accumulation. No self regulation needed? No problem. Except when you can’t self regulate healthy work amounts / dealing with demands.

I can appreciate that. Arguably these folks might be more likely to vote because they aren’t stuck in the mud of nuance, answers they see are more clear and obvious and the other ones may as well not exist. Not contemplation of what they don’t know, in a way.

But - on the other hand, as mentioned we can’t really pick who votes without opening Pandora’s Box - and the best thing we can do is not to punish, but to rehabilitate. To model stronger behaviours, to identify why they behave in this way, and to try to help them build stronger critical thinking skills. Punishment is polarizing.

Fun, maybe related note: I’ve researched some more classical AI approaches and took classes with some greats in the field whom are now my colleagues. One of which has many children who are absurdly successful globally, every one of them. He mathematically proved that (at least this form of AI) when you reward good behaviour and punish bad behaviour (correct responses, incorrect responses), the AI takes much longer to learn and spends a long time stuck on certain correct points and fails to, or takes a long time to, develop a varied strategy. If you just reward correct responses and don’t punish incorrect responses, the AI builds a much stronger model for answering a variety of questions. He said he applied that thinking to his kids, too, to what he considered a great success.

I think there’s something to that, and I’ve seen it in my own teaching, but the difficulty now has been getting students with this mindset to even try to get something correct or incorrect in the first place, so they just… Give up, or only kick into action after it’s too late and they don’t know how to handle it at that stage because they didn’t learn. Inaction is often the worst action, as it kills any hope of learning or building the skills of learning.

Yeah, this point about really needing time is pretty real. I recently came to the conclusion that some folks really just need to retake the core courses multiple times (and seeing if we can change this pattern) because it just takes them a long time to unlearn helplessness in the field and adapt.

And absolutely, as you’ve said, I find those who do adapt go from someone taking our most basic course three times to becoming a top student. Those who don’t adapt fall to cheating and/or dropping out. I usually have about 500-800 students per term, and with about 20-30% falling into this category with more each year, one-on-one interventions are rare and you usually only catch them on their second time around once they finally heed our requests to come talk to us.

I’d be curious what other fields work with this so I could go read some papers or other materials on these mindsets, it sounds like there is quite an overlap to what we’ve been experiencing, I appreciate these insights!

Edit: Oh, and adding that I’ve spoken to some researchers in trauma informed education and I imagine the overlap here is high in terms of approach - recognizing how different behaviours can be linked to trauma and considering the approaches that can be taken to ease them back into stronger academic habits. It’s been a while since my talks, but this could spark some more, as I hadn’t quite connected the rote memorizes to this. Seems quite feasible for at least a subset.

Yeah, you can feel it pretty quickly in an interaction. I like how the other comment put it, where it seems like they are stuck in rote memory mode. Having a list of facts in their head but no connections between them, no big picture capability. I recently had a student who seemingly refused to read the six bullet points describing a problem, and couldn’t comprehend that they described requirements, not step-by-step instructions. Without step-by-step instructions, this group flounders, and what should be insignificant details stand out as blockades they can’t get past because they can’t distinguish the roles of the details.

Reasoning blindness is an interesting term for it. Bloom’s taxonomy of learning, which has its controversies, stands out to me here; it’s like they are stuck at recall problems, maybe moving up to understanding a little bit but unable to get into using knowledge in new circumstances, connecting them, or being able to argue points. It works well for certain testing, it’s a great skill to be particularly astute in for many lines of work, but it really is a critical thinking nightmare.

Really great point - purely rote learning is definitely a major piece of this category, if not the category in itself. Basically an inability to move up Bloom’s taxonomy from the first level or two. I very recently spent hours with a student who had this exact issue - they tested well, but couldn’t even begin to do the applied work unless they were walked through it, precisely, step by step. Zero capability of generalizing, but fully capable of absorbing and recollecting facts… just no understanding associated with it. No connections.

That gave me something to think about, thank you!

I was once teaching a student introductory programming when I was in my undergrad.

The problem was to draw two circles on the screen of different colours and detect when the mouse is inside of one.

I said, “So our goal is simple: Let’s draw a circle somewhere on the screen. Consider what you’d tell me as a human - I’ve got the pencil, and you want to tell me to draw a circle of a certain size somewhere on this paper. We have three functions. Calling a function will draw a shape. Each function draws a different shape. We have rect(), circle(), and line(). Which of these sounds like the one we want to use? Which would get me to draw the correct shape?”

“… Rect?” “Why?” “It draws a shape.” “What shape would rect draw?” “I don’t know.” “Guess.” “A circle?” “Why do you think that?” “We need to draw a circle.” “If I said that rect draws a rectangle, which of the three functions would we want to use then, to draw our picture?” “Rect?”

I’ve now been teaching for many years, and those situations still come up a lot. When I put up a poll in class, with the answer still written on the board, about 25% of people in a 100+ student class will get it wrong - of people who were not only admitted to a competitive university program, but have passed multiple prerequisite courses to be here.

Not only is it unknown gaps in knowledge, there is just a thought process I haven’t been able to crack through that some people really can’t see what is immediately before them.

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.

All I’m commenting on, as a game design researched and professor, is that it’s an established term in a discipline which means something else to those actually within the discipline. These are still patterns, and they can absolutely be harmful patterns, but the terminology is being overloaded and there is some interesting nuance within it.

Also, just to comment on the last quip there, and yes - to those I’ve spoken to, they are okay with those because they (being actively involved in the industry) know more than most people to educate and supervise and ensure that playing games with these patterns doesn’t turn into harmful behaviours. They also call them out for what they are - often, very bad design.

I guess that’s really the line they drew - these patterns are more gray than the examples they presented. Most are good sometimes and terrible other times depending on how it is used. The term “dark patterns” as used professionally refers to always bad, always deceptive, always harmful. I do like having that line, even if it means the dark side is a much smaller subset of the greater space, then you can easily say, “If this uses a single dark pattern, it’s out. If it uses a lot of ‘grey’ patterns, be cautious. If it’s nothing but grey patterns, it’s purely abusive trash.”

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.

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.

Hah, yeah, I’m sure I could have taken time to phrase it better.

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.

I do think stigma is a part, both your expectations of others and the expectations on yourself. I had a psychiatrist tell me years before my diagnosis that I was “too successful” for ADHD and that pretty much derailed the acceptance for a long time, heh.

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.