Oh absolutely, I’m pretty sure I’m on the same page with this. I only pose that to someone who believes they’ve found people who respect them, and particularly those who have felt for a long time that their voice didn’t matter, it is counterproductive to approach them and their group with outward hostility.

Telling them the people who took them in and listened to them are vile, abusive, disgusting people and are exactly the problem they say everyone says you are, is just reinforcing of their views.

Consider the comment originally replied to; paraphrase because mobile is hard, “those loudest about being victimized are the most eager to take their pound of flesh”. This can easily sound like:

1. (Man) I’ve been victimized and nobody lets me voice this except for this gang/cult/militia. Cult says they should be allowed to “get support” and they know the way (it’s bad).
2. (Outsider) Claiming to be a victim usually means you are a terrible person.
3. (Man) So according to outsiders, if I seek help, I’m a bad person. According to my (cult etc) if I tell them, they will offer a form of support. I can stay with these people and get something of support, or I can leave them, be ostracized, and any attempts to voice my feelings will lead me to being labeled someone eager to take a pound of flesh.

They need to be shown that those on the outside understand them and are better people than those who took them in. They are with people whose form of empathy and respect is so distorted and toxic, but it’s the only model of that experience they know.

Your comment, upon my read, felt like anyone in that position would feel justified in their gang telling them that everyone on the outside is out to get them. If they already think everyone else is a predator, what is attacking their friends, their family, and their opinions, going to do?

They will only leave when they know they will arrive somewhere with the respect they craved without those toxic feelings they repressed during their time with a hateful group.

So I guess it’s less about the content of the comment, more of the way it represented the ideas, the timing, and the perceived intention.

I agree that much of the problem is men on men and this patriarchy - men who do not want to uphold patriarchal values can often be ostracized and demonized by those who do - but I believe OP was specifically noting that then those men who get abused and ostracized cannot speak out of seek help because many people will simply snap back at them saying that they are part of the problem and resources need to be given elsewhere. They cannot endure the abuse, and their own cohort becomes abusive, and the only way to avoid the abuse from all sides (in their view) becomes joining the “social excrement” they wanted to escape in the first place.

Angry screams tend to mask sad and lonely tears. Hatred does not end hatred; hatred ends through non-hate alone. Non-hate is not inaction, though. If we do not look at them, and ourself, with empathy and kindness and understanding and patience, they will continue living in a world devoid of and therefore ignorant to empathy and kindness and understanding and patience.

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.

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.

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.

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.

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.

I really want to see if worker owned cooperatives plus AI could do help democratize running companies (where appropriate). Not just LLMs, but a mix of techniques for different purposes (e.g., hierarchial task networks to help with operations and pipelining, LLM for assembling/disseminating information to workers).

C could just be a blank and you have to bit blit the arrow on yourself.

I don’t know why, but I still can’t open a core file without going I’m in. I don’t do QA, though, and so tinkering with final breath of my program frozen in time maintains some novelty.

My two cents, after years of Markdown (and md to PDF solutions) and LaTeX and a full two years of trying to commit to bashing my head against Word for work purposes, I’m really enjoying Typst. It didn’t take long to convert my themes, having docs I can import which are basically just variables to share across documents in a folder has been really helpful. Haven’t gone too deep into it but I’m excited to give it a deeper test run over the next little bit.

Lots of immediate hate for AI, but I’m all for local AI if they keep that direction. Small models are getting really impressive, and if they have smaller, fine-tuned, specific-purpose AI over the “general purpose” LLMs, they’d be much more efficient at their jobs. I’ve been rocking local LLMs for a while and they’ve been great as a small compliment to language processing tasks in my coding.

Good text-to-speech, page summarization, contextual content blocking, translation, bias/sentiment detection, click bait detection, article re-titling, I’m sure there’s many great use cases. And purely speculation,but many traditional non-llm techniques might be able to included here that were overlooked because nobody cared about AI features, that could be super lightweight and still helpful.

If it goes fully remote AI, it loses a lot of privacy cred, and positions itself really similarly to where everyone else is. From a financial perspective, bandwagoning on AI in the browser but “we won’t send your data anywhere” seems like a trendy, but potentially helpful and effective way to bring in a demographic interested in it without sacrificing principles.

But there’s a lot of speculation in this comment. Mozilla’s done a lot for FOSS, and I get they need monetization outside of Google, but hopefully it doesn’t lead things astray too hard.

That too, and I can really efficiently manage the items going into bags given I backpack my groceries and want pretty specific configurations…

Totally agree. I forgot about those, as I’ve only encountered the weighing ones once in the past very long time and it was a mess, I can totally get hate if weighing ones are the only experience with them.

I almost exclusivity self-checkout for groceries, and it had drastically sped up my checkout time as most people in my area opt to use traditional checkout and the stores are still keeping lots of lanes open (just closing the express lanes). The last 3 times I’ve used a non-self checkout, each time I was double charged for items or didn’t have reduced prices applied and didn’t notice because I was bagging.

Yeah, this is the approach people are trying to take more now, the problem is generally amount of that data needed and verifying it’s high quality in the first place, but these systems are positive feedback loops both in training and in use. If you train on higher quality code, it will write higher quality code, but be less able to handle edge cases or potentially complete code in a salient way that wasn’t at the same quality bar or style as the training code.

On the use side, if you provide higher quality code as input when prompting, it is more likely to predict higher quality code because it’s continuing what was written. Using standard approaches, documenting, just generally following good practice with code before sending it to the LLM will majorly improve results.