10 ms·

Richard Stallman Talks Red Hat, AI and Ethical Software Licenses at GNU Birthday

124 points by mmphosis 3y ago

haolez 3y ago
I don't agree with his take on LLMs. There is something about them that feels very similar to the way my own brain works. Like, for example, when I perceive a smell that, somehow, activates a very old and almost forgotten visual memory. Sometimes, when talking to a LLM, it feels like one or two words in my prompt is having a similar effect on it.
- visarga 3y ago
  Maybe his perspective on AI is colored by the fact that he's not going to get to see it fully developed so he has nothing to gain.
  - baz00 3y ago
    Maybe he's looking at now, which he is on the mark on, and not some hypothetical destination that is being hyped that we may never get to.
  - benterix 3y ago
    There are so many assumptions in your statement.
  - crabbone 3y ago
    I doubt that. As someone who was enthusiastic about AI before neural networks rose to prominence, I only shake my head when I hear people ascribe all sorts of properties of intelligence to the particular trend in AI that is in vogue today. The ultimate quest of AI was to understand how to make good decisions. The idea was that maybe if we emulate human activity that humans call "intelligence", but remove all the randomness, unintended errors etc, then we can understand what it means to be intelligent and subsequently will be able to attack hard problems where humans fail due to things like the size of the problem, or the lack of intuition for a particular domain etc. The neural-net AI abandoned all hopes of understanding of how intelligence works and concentrated its efforts on mimicking a typical human response by asking a lot of people the same question, and then averaging the answers. It inspires no confidence that it will be able to apply to domains where humans themselves struggle (eg. multidimensional geometry) or that it will ever become an authoritative source for any kind of answers (i.e. would produce a proof why its answers are correct). To anyone who wanted to know how intelligence works neural-net AI is worthless. That's not to say that such AI is worthless in general, clearly, it does very well predicting complex patterned behavior, or can sift through a lot of data with difficult to deterministically determine patterns, but it isn't even going in the direction anyone who wanted intelligence would be interested in. I think that as with many historically vague terminology, we'll have to redefine what "intelligence" means. Split this concept into multiple concepts, and, maybe the neural-net group will win the right to call themselves "AI", while those who I describe above will switch to a different term, or maybe it will be the other way around. It's clear though that the modern in-vogue approach is simply a waste of time for a lot of people interested in AI.
    - ta988 3y ago
      You don't seem to understand how thise systems are trained if you believe it is by asking a lot of people and averaging answers. Plus there is a ton of work to now combine LLMs with their excellent language abilities to more formal systems based on rules, ontologies and (fuzzy) logic. LLMs showed that this type of networks can likely solve one aspect if intelligence, the ability to handle language, that previous approaches were all extremely bad at. Doesn't mean that this approach is good for all other aspects of intelligence, but it turns out it is not too bad at information retrieval as well and a few other things. And other kind of networks also showed excellent abilities in other aspects like vision.
      - crabbone 3y ago
        I work in HPC infra, so I know some stuff about how these network are trained, but more from a technical perspective, i.e. stuff like "how to set up MPI for a cluster of X nodes" or how to configure GPU drivers. I know basic stuff about how models are trained from another perspective too -- since I work with researchers, and my wife being an RSE who usually works with healthcare related research I'm also exposed to a lot of side effects of using neural network styled AI in practice. I don't claim to have a good knowledge of the ins and outs of the particular trend of the day though. I wouldn't be able to tell what the difference is between "deep learning" and "reinforcement learning", not with any authority or confidence. I did take two courses on AI though, long before the neural-network approach was a thing. I.e. my AI learning experience was focused on search algorithms, building knowledge bases etc. So, here, based on my experience of practical applications of LLMs, I can comment on things you wrote: > Plus there is a ton of work to now combine LLMs with their excellent language abilities to more formal systems based on rules Tons of publications doesn't mean this is a solved problem. As it stands now, there's a serious doubt this is a problem that can be solved. I have not seen any real system working in the world of medicine which would use LLMs for anything that can be encoded as rules. If anything, I've heard a lot about failures to implement anything remotely similar to this (which happened outside of academic medicine, or somehow slept through the cracks). I.e. chatbots suggesting suicide to people in distress, or suggesting to cut on carbs to young women struggling with anorexia and so on. > the ability to handle language, that previous approaches were all extremely bad at Well, now it's my turn to point fingers. You probably don't know much about previous approaches, and don't understand the problem well. It's true that since the term AI was coined substantial efforts went into understanding natural languages. But what came out of this work is a disillusionment, the understanding that natural languages suck at encoding knowledge and as such are a bad tool for building ontologies, or call them knowledge bases. So, it wasn't because older methods failed to parse language well. It was because we realized that there's no point in being good at it. It's a cute gimmick, if you can do it, and can be useful in harmless situations, like enabling rich interactions between NPCs and PCs in video games. But, if your goal is to understand how to make good decisions, it's more of an obstacle really. Like I said previously, but you seem to have ignored: yes, neural networks are useful, but not in the way a lot of people understand intelligence, or, at least, they fail to address the central and the critical questions about intelligence. Compounded by dishonest advertisement of their abilities and armies of low-quality practitioners this approach has a tendency to alienate people who are interested in more fundamental questions about the nature of intelligence.
  - sph 3y ago
    You got it the wrong way round. The perspective of people that stand to gain from AI is colored, rather than the one on the sidelines being biased.
- thesuperbigfrog 3y ago
  >> I don't agree with his take on LLMs. His take may be a bit jaded from his own experience. He worked as a Lisp hacker at the MIT Artificial Intelligence lab when AI research was peaking in the 1970s. The commercialization of Lisp and early AI effectively destroyed the hacker paradise he worked in and the following "AI Winter" devastated the research and its funding. These experiences lead him to start the GNU project, so the net result was good for software, but definitely colored his perspective. See https://en.wikipedia.org/wiki/Richard_Stallman#Harvard_University_and_MIT https://en.wikipedia.org/wiki/Richard_Stallman#Harvard_Unive... for more details.
serioussecurity 3y ago
[flagged]
visarga 3y ago
> “As I see it, ‘intelligence’ needs something like the ability to know or understand some area,” he said. “If something can’t actually understand things we shouldn’t say it’s intelligent, not even a little intelligent, but people are using the term artificial intelligence for bullshit generators.” I wouldn't go as far in blaming AI. It is certainly error prone and has very short autonomy. It's not better than subject matter experts in any field. But it can solve multi-step problems even when they don't look very close to anything in the training set. I thought that as a pioneer in the free software movement, he would fully support LLMs that democratize skills and make them universally applicable. LLMs benefit from the knowledge of some and extend that help to others, much like the principles of free software. In fact AI is much more radical in making skills free than software ever was.
- varelse 3y ago
  [dead]
- vidarh 3y ago
  His thinking here leans on assuming that there's a qualitative difference between LLM's "understanding" and our "understanding" that justifies using the term for us, but not for LLMs. Maybe there is, but their reasoning ability is sufficient that I don't think is at all a given, and at a minimum an assertion that should make you ask someone how they define "understanding", because defining that in a way that is focused on reasoning-ability that will exclude LLMs but not exclude some people seems tricky.
  - ad404b8a372f2b9 3y ago
    I don't know that his argument is based on essentialism since he goes on to describe algorithms which he considers artificially intelligent: "There are programs that can look at a photo of some magnified cells and tell you, with greater likelihood of being right than any human doctor, whether it’s cancerous or not,”. And he puts it in contrast to his previous statement about LLMs not being artifically intelligent. It seems to me he wants people to look past the impressive facade of correct grammar and see that a lot of the LLMs often spew out bullshit. Personally I've seen them perform intelligence tasks, generate correct code and so forth. But I think many people ascribe to them a general intelligence that they don't have, which is why you see them quoted increasingly often online as if they were knowledgeable or correct-by-default.
deleted 3y ago
[deleted]
munchler 3y ago
[flagged]
- mik1998 3y ago
  A statistical model cannot understand anything since it does not think in the first place.
  - steve1977 3y ago
    That implies that thinking is not based on some kind of biological statistical system.
    - oddevan 3y ago
      Counterpoint: person hears 15 arguments. 14 say one thing, 1 says another. Person agrees with the 1 argument because it resonates with them more. I'm not saying the 14 are right and the 1 is wrong. I'm saying that the decision was not based on a statistical model.
      - steve1977 3y ago
        Not so simple. Why did the argument of that one person resonate more? Likely because of some other „experience“ or data that is not necessarily expressed or codified in either of the arguments. That experience or intuition or whatever you want to call it can itself be based on some statistical „model“.
      - macksd 3y ago
        No, it's based on a statistical model that incorporates biases, like many statistical models.
- steve1977 3y ago
  Not so quick with disqualifications… Stallman was working at the MIT Artificial Intelligence Lab, long before most of us have first heard the term AI or were even born. Also, for example: „While working (starting in 1975) as a research assistant at MIT under Gerry Sussman, Stallman published a paper (with Sussman) in 1977 on an AI truth maintenance system, called dependency-directed backtracking.“ Source: https://en.m.wikipedia.org/wiki/Richard_Stallman https://en.m.wikipedia.org/wiki/Richard_Stallman
Boogie_Man 3y ago
Very sad to hear that a crucial, visionary figure in FOSS has cancer. The loss of his "Lion's Mane" is shocking to see in an image in the article. Prayers and best wishes to Stallman.
- dehrmann 3y ago
  For a sec I was like "Is that Knuth?"
sph 3y ago
It is really jarring to see RMS without his iconic beard. I hope he recovers soon from his cancer, we need GNU and free software proselytism more than ever today.
- spicymaki 3y ago
  It is great that his prognosis is good, but who is stepping up to bring the movement into the next generation?
  - justinclift 3y ago
    Why would anyone want to paint that kind of target on their own back?
  - tmpX7dMeXU 3y ago
    The FSF and its leagues of fanboys should be thought about that decades ago instead of painting themselves into a corner by being utterly unapproachable by anyone that wasn’t using computers in 2004.
- microtherion 3y ago
  He was really unrecognizable to me. I would have thought I'd recognize his face even without the hair, but apparently not.
thorin 3y ago
Is the free software not being cool / peer pressure thing directed at Apple? I don't think people are buying Windows because it's cool.
simiones 3y ago
Interesting to see he is very clearly against what IBM Red Hat is doing. Not surprising, since it was the obvious thing to say about it (they are trying to prevent you from using the full rights given to you by the license). Still, nice to see no ifs, ands or buts: what they are doing is ethically wrong and should stop. It may or may not be illegal as well, but it's certainly not a good thing.
jekude 3y ago
Recommend watching the video[1], there are some classic moments where the crowd can’t hear rms because of how he is holding the microphone and we get a classic stallman rant about microphones. [1] https://m.youtube.com/watch?v=vUwQLsWjA-g&pp=ygUQcmljaGFyZCBzdGFsbG1hbg%3D%3D https://m.youtube.com/watch?v=vUwQLsWjA-g&pp=ygUQcmljaGFyZCB...
0atman 3y ago
I went to a small talk rms gave in London in around 2009. The talk was unmemorable (my fault, likely, not his) but the Q&A afterwards was remarkable: He screamed at people for using 'open source' instead of 'free software' in their questions, raved about the Amazon "Swindle" like a 12-year-old, and talked over and down to everyone. He was often accurate in the core of what he was trying to say, but his attitude was unhinged, and discouraged most people from interacting. The 100 or so developers all left the talk in silence, mourning the loss of the hero we had imagined him to be. To those who say we need him for GNU outreach: we absolutely don't. ANYONE would be better for the job. I thank him for his many incredible contributions to our world, and wish him a speedy recovery, but we don't need these talented assholes to represent our community.
- rmstruth 3y ago
  [dead]
- dayvid 3y ago
  I read the infamous article that tried to cancel Stallman and agreed with most of it. She was wrong at the end when she tried to destroy his legacy and image. Stallman has done a lot, but he's doing more harm than good nowadays. It's mature to know when to step down and give the next generation space to grow.
  - 0atman 3y ago
    I read just today that there's no such thing as 'cancel culture', what it is, is 'consequence culture': The observation that it's becoming less accepted that we must protect the rich/famous/powerful just because they're rich/famous/powerful.
    - digging 3y ago
      This is the reality and thanks for saying it. Bullies and harassers get so used to having their way that they think they're being victimized when others call them out for bullying and harassment.
    - 3y ago
2devnull 3y ago
“It’s not really expression of anything. It’s freedom of manipulation; freedom of engineering people’s brains to be ideal victims. Maybe that’s something society needs to prohibit.” I think governments were first in this space of “engineering people’s brains to be ideal victims” and will remain active in that long after any regulation is crafted to limit individuals and corporations from doing the same. Engagement optimization seems like a thing that can be regulated, but it’s just the same thing tv stations have been doing forever, basically marketing. I think really the problem is a different one. People need better education especially when it comes to ethics. Psychological experiments (a/b testing for example) should be governed by boards that oversee the ethics of experimenting on human subjects. Stallman identifies the problem as “popularity” but what if popularity required behaving ethically and not doing what is incontrovertibly unethical human subject research for personal greed.
apienx 3y ago
> It was pretty much a classic RMS talk, with a focus on Red Hat, artificial intelligence, and why kids don’t think free software is cool (hint: it has to do with wanting to be popular, which evidently was never an issue for Stallman). I chuckled ;-)
xcrunner529 3y ago
Why are we giving this accused sex pest attention still?
tmarsden 3y ago
You’re never going to get children interested in free software. They barely know what software is let alone the distinction between free and proprietary software. On the other hand you will be able to get adults interested, there are likely plenty of us out there that are completely jaded from using proprietary software most of their lives. The ideals of freedom, privacy and openness are still valued by some and they should be the core of the recruitment message.
- cxr 3y ago
  Children understand the feeling of being told they can't do something for no good reason, the sense of unfairness it evokes, and the desire to vocalize it (rather than suppressing it knowing it will be met with responses in the form of the thought-terminating cliche that "life's not fair").

124 points by mmphosis 3y ago

I don't agree with his take on LLMs. There is something about them that feels very similar to the way my own brain works. Like, for example, when I perceive a smell that, somehow, activates a very old and almost forgotten visual memory. Sometimes, when talking to a LLM, it feels like one or two words in my prompt is having a similar effect on it.

visarga 3y ago
Maybe his perspective on AI is colored by the fact that he's not going to get to see it fully developed so he has nothing to gain.
- baz00 3y ago
  Maybe he's looking at now, which he is on the mark on, and not some hypothetical destination that is being hyped that we may never get to.
- benterix 3y ago
  There are so many assumptions in your statement.
- crabbone 3y ago
  I doubt that. As someone who was enthusiastic about AI before neural networks rose to prominence, I only shake my head when I hear people ascribe all sorts of properties of intelligence to the particular trend in AI that is in vogue today. The ultimate quest of AI was to understand how to make good decisions. The idea was that maybe if we emulate human activity that humans call "intelligence", but remove all the randomness, unintended errors etc, then we can understand what it means to be intelligent and subsequently will be able to attack hard problems where humans fail due to things like the size of the problem, or the lack of intuition for a particular domain etc. The neural-net AI abandoned all hopes of understanding of how intelligence works and concentrated its efforts on mimicking a typical human response by asking a lot of people the same question, and then averaging the answers. It inspires no confidence that it will be able to apply to domains where humans themselves struggle (eg. multidimensional geometry) or that it will ever become an authoritative source for any kind of answers (i.e. would produce a proof why its answers are correct). To anyone who wanted to know how intelligence works neural-net AI is worthless. That's not to say that such AI is worthless in general, clearly, it does very well predicting complex patterned behavior, or can sift through a lot of data with difficult to deterministically determine patterns, but it isn't even going in the direction anyone who wanted intelligence would be interested in. I think that as with many historically vague terminology, we'll have to redefine what "intelligence" means. Split this concept into multiple concepts, and, maybe the neural-net group will win the right to call themselves "AI", while those who I describe above will switch to a different term, or maybe it will be the other way around. It's clear though that the modern in-vogue approach is simply a waste of time for a lot of people interested in AI.
  - ta988 3y ago
    You don't seem to understand how thise systems are trained if you believe it is by asking a lot of people and averaging answers. Plus there is a ton of work to now combine LLMs with their excellent language abilities to more formal systems based on rules, ontologies and (fuzzy) logic. LLMs showed that this type of networks can likely solve one aspect if intelligence, the ability to handle language, that previous approaches were all extremely bad at. Doesn't mean that this approach is good for all other aspects of intelligence, but it turns out it is not too bad at information retrieval as well and a few other things. And other kind of networks also showed excellent abilities in other aspects like vision.
    - crabbone 3y ago
      I work in HPC infra, so I know some stuff about how these network are trained, but more from a technical perspective, i.e. stuff like "how to set up MPI for a cluster of X nodes" or how to configure GPU drivers. I know basic stuff about how models are trained from another perspective too -- since I work with researchers, and my wife being an RSE who usually works with healthcare related research I'm also exposed to a lot of side effects of using neural network styled AI in practice. I don't claim to have a good knowledge of the ins and outs of the particular trend of the day though. I wouldn't be able to tell what the difference is between "deep learning" and "reinforcement learning", not with any authority or confidence. I did take two courses on AI though, long before the neural-network approach was a thing. I.e. my AI learning experience was focused on search algorithms, building knowledge bases etc. So, here, based on my experience of practical applications of LLMs, I can comment on things you wrote: > Plus there is a ton of work to now combine LLMs with their excellent language abilities to more formal systems based on rules Tons of publications doesn't mean this is a solved problem. As it stands now, there's a serious doubt this is a problem that can be solved. I have not seen any real system working in the world of medicine which would use LLMs for anything that can be encoded as rules. If anything, I've heard a lot about failures to implement anything remotely similar to this (which happened outside of academic medicine, or somehow slept through the cracks). I.e. chatbots suggesting suicide to people in distress, or suggesting to cut on carbs to young women struggling with anorexia and so on. > the ability to handle language, that previous approaches were all extremely bad at Well, now it's my turn to point fingers. You probably don't know much about previous approaches, and don't understand the problem well. It's true that since the term AI was coined substantial efforts went into understanding natural languages. But what came out of this work is a disillusionment, the understanding that natural languages suck at encoding knowledge and as such are a bad tool for building ontologies, or call them knowledge bases. So, it wasn't because older methods failed to parse language well. It was because we realized that there's no point in being good at it. It's a cute gimmick, if you can do it, and can be useful in harmless situations, like enabling rich interactions between NPCs and PCs in video games. But, if your goal is to understand how to make good decisions, it's more of an obstacle really. Like I said previously, but you seem to have ignored: yes, neural networks are useful, but not in the way a lot of people understand intelligence, or, at least, they fail to address the central and the critical questions about intelligence. Compounded by dishonest advertisement of their abilities and armies of low-quality practitioners this approach has a tendency to alienate people who are interested in more fundamental questions about the nature of intelligence.
- sph 3y ago
  You got it the wrong way round. The perspective of people that stand to gain from AI is colored, rather than the one on the sidelines being biased.
thesuperbigfrog 3y ago
>> I don't agree with his take on LLMs. His take may be a bit jaded from his own experience. He worked as a Lisp hacker at the MIT Artificial Intelligence lab when AI research was peaking in the 1970s. The commercialization of Lisp and early AI effectively destroyed the hacker paradise he worked in and the following "AI Winter" devastated the research and its funding. These experiences lead him to start the GNU project, so the net result was good for software, but definitely colored his perspective. See https://en.wikipedia.org/wiki/Richard_Stallman#Harvard_University_and_MIT https://en.wikipedia.org/wiki/Richard_Stallman#Harvard_Unive... for more details.

serioussecurity 3y ago

[flagged]

visarga 3y ago

> “As I see it, ‘intelligence’ needs something like the ability to know or understand some area,” he said. “If something can’t actually understand things we shouldn’t say it’s intelligent, not even a little intelligent, but people are using the term artificial intelligence for bullshit generators.” I wouldn't go as far in blaming AI. It is certainly error prone and has very short autonomy. It's not better than subject matter experts in any field. But it can solve multi-step problems even when they don't look very close to anything in the training set. I thought that as a pioneer in the free software movement, he would fully support LLMs that democratize skills and make them universally applicable. LLMs benefit from the knowledge of some and extend that help to others, much like the principles of free software. In fact AI is much more radical in making skills free than software ever was.

varelse 3y ago
[dead]
vidarh 3y ago
His thinking here leans on assuming that there's a qualitative difference between LLM's "understanding" and our "understanding" that justifies using the term for us, but not for LLMs. Maybe there is, but their reasoning ability is sufficient that I don't think is at all a given, and at a minimum an assertion that should make you ask someone how they define "understanding", because defining that in a way that is focused on reasoning-ability that will exclude LLMs but not exclude some people seems tricky.
- ad404b8a372f2b9 3y ago
  I don't know that his argument is based on essentialism since he goes on to describe algorithms which he considers artificially intelligent: "There are programs that can look at a photo of some magnified cells and tell you, with greater likelihood of being right than any human doctor, whether it’s cancerous or not,”. And he puts it in contrast to his previous statement about LLMs not being artifically intelligent. It seems to me he wants people to look past the impressive facade of correct grammar and see that a lot of the LLMs often spew out bullshit. Personally I've seen them perform intelligence tasks, generate correct code and so forth. But I think many people ascribe to them a general intelligence that they don't have, which is why you see them quoted increasingly often online as if they were knowledgeable or correct-by-default.

deleted 3y ago

[deleted]

munchler 3y ago

[flagged]

mik1998 3y ago
A statistical model cannot understand anything since it does not think in the first place.
- steve1977 3y ago
  That implies that thinking is not based on some kind of biological statistical system.
  - oddevan 3y ago
    Counterpoint: person hears 15 arguments. 14 say one thing, 1 says another. Person agrees with the 1 argument because it resonates with them more. I'm not saying the 14 are right and the 1 is wrong. I'm saying that the decision was not based on a statistical model.
    - steve1977 3y ago
      Not so simple. Why did the argument of that one person resonate more? Likely because of some other „experience“ or data that is not necessarily expressed or codified in either of the arguments. That experience or intuition or whatever you want to call it can itself be based on some statistical „model“.
    - macksd 3y ago
      No, it's based on a statistical model that incorporates biases, like many statistical models.
steve1977 3y ago
Not so quick with disqualifications… Stallman was working at the MIT Artificial Intelligence Lab, long before most of us have first heard the term AI or were even born. Also, for example: „While working (starting in 1975) as a research assistant at MIT under Gerry Sussman, Stallman published a paper (with Sussman) in 1977 on an AI truth maintenance system, called dependency-directed backtracking.“ Source: https://en.m.wikipedia.org/wiki/Richard_Stallman https://en.m.wikipedia.org/wiki/Richard_Stallman

Boogie_Man 3y ago

Very sad to hear that a crucial, visionary figure in FOSS has cancer. The loss of his "Lion's Mane" is shocking to see in an image in the article. Prayers and best wishes to Stallman.

dehrmann 3y ago
For a sec I was like "Is that Knuth?"

sph 3y ago

It is really jarring to see RMS without his iconic beard. I hope he recovers soon from his cancer, we need GNU and free software proselytism more than ever today.

spicymaki 3y ago
It is great that his prognosis is good, but who is stepping up to bring the movement into the next generation?
- justinclift 3y ago
  Why would anyone want to paint that kind of target on their own back?
- tmpX7dMeXU 3y ago
  The FSF and its leagues of fanboys should be thought about that decades ago instead of painting themselves into a corner by being utterly unapproachable by anyone that wasn’t using computers in 2004.
microtherion 3y ago
He was really unrecognizable to me. I would have thought I'd recognize his face even without the hair, but apparently not.

thorin 3y ago

Is the free software not being cool / peer pressure thing directed at Apple? I don't think people are buying Windows because it's cool.

simiones 3y ago

Interesting to see he is very clearly against what IBM Red Hat is doing. Not surprising, since it was the obvious thing to say about it (they are trying to prevent you from using the full rights given to you by the license). Still, nice to see no ifs, ands or buts: what they are doing is ethically wrong and should stop. It may or may not be illegal as well, but it's certainly not a good thing.

jekude 3y ago

Recommend watching the video[1], there are some classic moments where the crowd can’t hear rms because of how he is holding the microphone and we get a classic stallman rant about microphones. [1] https://m.youtube.com/watch?v=vUwQLsWjA-g&pp=ygUQcmljaGFyZCBzdGFsbG1hbg%3D%3D https://m.youtube.com/watch?v=vUwQLsWjA-g&pp=ygUQcmljaGFyZCB...

0atman 3y ago

I went to a small talk rms gave in London in around 2009. The talk was unmemorable (my fault, likely, not his) but the Q&A afterwards was remarkable: He screamed at people for using 'open source' instead of 'free software' in their questions, raved about the Amazon "Swindle" like a 12-year-old, and talked over and down to everyone. He was often accurate in the core of what he was trying to say, but his attitude was unhinged, and discouraged most people from interacting. The 100 or so developers all left the talk in silence, mourning the loss of the hero we had imagined him to be. To those who say we need him for GNU outreach: we absolutely don't. ANYONE would be better for the job. I thank him for his many incredible contributions to our world, and wish him a speedy recovery, but we don't need these talented assholes to represent our community.

rmstruth 3y ago
[dead]
dayvid 3y ago
I read the infamous article that tried to cancel Stallman and agreed with most of it. She was wrong at the end when she tried to destroy his legacy and image. Stallman has done a lot, but he's doing more harm than good nowadays. It's mature to know when to step down and give the next generation space to grow.
- 0atman 3y ago
  I read just today that there's no such thing as 'cancel culture', what it is, is 'consequence culture': The observation that it's becoming less accepted that we must protect the rich/famous/powerful just because they're rich/famous/powerful.
  - digging 3y ago
    This is the reality and thanks for saying it. Bullies and harassers get so used to having their way that they think they're being victimized when others call them out for bullying and harassment.
  - 3y ago

2devnull 3y ago

“It’s not really expression of anything. It’s freedom of manipulation; freedom of engineering people’s brains to be ideal victims. Maybe that’s something society needs to prohibit.” I think governments were first in this space of “engineering people’s brains to be ideal victims” and will remain active in that long after any regulation is crafted to limit individuals and corporations from doing the same. Engagement optimization seems like a thing that can be regulated, but it’s just the same thing tv stations have been doing forever, basically marketing. I think really the problem is a different one. People need better education especially when it comes to ethics. Psychological experiments (a/b testing for example) should be governed by boards that oversee the ethics of experimenting on human subjects. Stallman identifies the problem as “popularity” but what if popularity required behaving ethically and not doing what is incontrovertibly unethical human subject research for personal greed.

apienx 3y ago

> It was pretty much a classic RMS talk, with a focus on Red Hat, artificial intelligence, and why kids don’t think free software is cool (hint: it has to do with wanting to be popular, which evidently was never an issue for Stallman). I chuckled ;-)

xcrunner529 3y ago

Why are we giving this accused sex pest attention still?

tmarsden 3y ago

You’re never going to get children interested in free software. They barely know what software is let alone the distinction between free and proprietary software. On the other hand you will be able to get adults interested, there are likely plenty of us out there that are completely jaded from using proprietary software most of their lives. The ideals of freedom, privacy and openness are still valued by some and they should be the core of the recruitment message.

cxr 3y ago
Children understand the feeling of being told they can't do something for no good reason, the sense of unfairness it evokes, and the desire to vocalize it (rather than suppressing it knowing it will be met with responses in the form of the thought-terminating cliche that "life's not fair").