5 ms·

Three Thousand Years of Algorithmic Rituals

76 points by chobeat 7y ago

schapin23 7y ago
"Even at the end of the twentieth century, no one would have ever thought to call a truck driver a “cognitive worker,” an intellectual. At the beginning of the twenty-first century, the use of machine learning in the development of self-driving vehicles has led to a new understanding of manual skills such as driving, revealing how the most valuable component of work, generally speaking, has never been merely manual, but also social and cognitive" This is the best quote from the article.
ArtWomb 7y ago
Nice to see e-flux, one of the oldest netart sites on the internet, still publishing. For a deeper dive into fascinating origins of materialism in Ancient Indian philosophy, the following provides a decent intro. "However, in importing these labels from Western philosophy to the classical Indian philosophical systems, one needs to exercise caution because the concepts of nature, science, scientific method, etc. do not smoothly converge in the two theoretical traditions." Naturalism in Classical Indian Philosophy https://plato.stanford.edu/entries/naturalism-india/ https://plato.stanford.edu/entries/naturalism-india/
xaedes 7y ago
Despite the way it is often framed and critiqued, artificial intelligence is not really “artificial” or “alien”: in the usual mystification process of ideology, it appears to be a deus ex machina that descends to the world like in ancient theater. But this hides the fact that it actually emerges from the intelligence of this world. What people call “AI” is actually a long historical process of crystallizing collective behavior, personal data, and individual labor into privatized algorithms that are used for the automation of complex tasks: from driving to translation, from object recognition to music composition. Just as much as the machines of the industrial age grew out of experimentation, know-how, and the labor of skilled workers, engineers, and craftsmen, the statistical models of AI grow out of the data produced by collective intelligence. I can totally resonate with that part
- ralphstodomingo 7y ago
  Quite a nice excerpt, will be reading the article now. We almost always discount the work done by our predecessors: NIH-syndrome/"reinventing the wheel" vs "standing in the shoulders of giants", and this was a humble reminder for me.
  - gumby 7y ago
    > We almost always discount the work done by our predecessors: NIH-syndrome/"reinventing the wheel" vs "standing in the shoulders of giants", and this was a humble reminder for me. "We" being computer scientists (or computing) which for some reason has this disease, perhaps due to the field's newness? When I worked in the life sciences (pharmaceutical chemistry) the literature was the first place we looked. Whereas when working at a research lab in my 20s: I would often go down to our library and read CACM, IEEE journal et al and would sometimes implement things I read there. Even though I would brandish a photocopy of the journal article and reference it in the source code my boss and colleagues would praise me for "thinking up" a solution to a given problem. Ironically the Internet changed things dramatically in the physical sciences (in Physics especially* but in other physical sciences by making it much easier to both search and read the literature) whereas in non-academic computing it's been the small conferences and, to my surprise, Youtube. * Physics has long been an innovator in information dissemination; when journal publishing got too slow and letters too point-to-point it gave rise to Physics Letters, which itself became a pair of journals....
- carapace 7y ago
  Turing machines are essentially automation of Turing's thought processes, so, in a way, computers have always been AI.
voidhorse 7y ago
Great to see this on hacker news. E-flux publishes a lot of voices (artists, continental philosophers, and others) that have sound, intellectual criticisms about te ways we incorporate technology into our lives—and I think it’s important for tehnologists to hear them. It’s not common for these voices to reach traditional comp-sci/mega tech spheres. They put out a nice series of readers based on their journals and other material. I recently read a great one that collected some of the works of Hito Steyerl.
- chobeat 7y ago
  I'm trying to work in that direction on many fronts. Hackernews is not really one of them but this post was really in Hackernews style so I decided to post it here.
  - voidhorse 7y ago
    That’s great. This is something I’m interested in as well. I found your critical essays repo on github. I have committed time to studying the philosophy of technology and am particularly familiar with the works of the Frankfurt school, some of Paul Virilio’s work, and the work of Lewis Mumford. I’d be happy to contribute if you’re looking for contributors for any critical projects.
    - chobeat 7y ago
      Well, if you want to suggest some proposal for the reading list, I would love to include your contributions. My projects are very local: Tech Worker Coalition in Berlin e Gambe.ro in Italy, so I don't think there's any room in those.
YeGoblynQueenne 7y ago
At the risk of sounding like a broken record I must point out that AI, neural networks, machine learning, Perceptrons, algorithms and deep learning are not interchangeable terms, any more than "maths" is interchangeable with "calculus", "trigonometry", "geometry", "algebra" and "arithmetic". Unfortunately this article is typically using such terms as synonyms and, while it's probably meant to help the lay reader understand a technical subject, will only manage to confuse the issue further. It's clear that there is intense interest in deep learning and machine learning in the last 7 years or so, but, especially when talking of "AI", it is important to remember that the majority of work in AI has _not_ been on machine learning, but on inference and reasoning, and using symbolic, logic-based techniques (including Bayesian reasoning, as in Solomonoff's Inductive Inference) rather than "statistical" methods (in the sense that the term is used in AI to mean everything from probabilities to calculus). Finally, there are historcial inaccuracies in this article. For example, Rosenblatt's Perceptron was not "the first machine-learning algorithm' as the article says: Arthur Samuel's self-playing checkers agents and Minsky's SNARC are two systems predating the Perceptron by a few years and research on machine learning techniques like Markov chains goes back to the 1910's.
- chobeat 7y ago
  While agree with you on the need to straighten the narrative and usage of these terms, the author is a philosopher and uses AI not in the common sense nor in the Computer Science sense. It is indeed confusing but he's very very rigorous in the way he writes (this is extremely simple writing for his usual style) so don't believe he's using the terms intercheangeably
  - whatshisface 7y ago
    Most of these philosophical thinkpiece authors are charlatans. Charlatan philosophers can get along very well, even in professional circles, because there's almost no way to tell the difference between a true belief and a false belief in some areas of philosophy. However, they meet their downfall in articles like these, when they make the mistake of talking about something that is relatively easy to verify - revealing that they are sloppy thinkers with great English skills.
vertline3 7y ago
Algorithms aren't rituals, they are more concrete.
odomojuli 7y ago
I vaguely recall reading a paper about oracle bones and hunter-gatherers, with the central theme being a study of generating randomness by the means of an "algorithm". I recall it was on arxiv but that doesn't seem to be the case anymore. Algorithm being defined as: take a bunch of animal bones, burn them until they are essentially cremated, and then interpret the ashes somehow to point you in a random direction away from your village. The idea was that this is such a noisy and chaotic system that you get decent enough randomization to distribute your hunter-gatherers into wilderness. The reason this is economical is it allows you to distribute away from concentrating too much effort into just one particular zone. A key idea here is that while maybe a certain river or patch of grass might have been historically lucrative, eventually the population will be exhausted. Without doing ample surveys of the wilderness all the time, hunter-gatherers have scarcely a clue that they are exhausting its resources. So a simple strategy is to randomly distribute your collection of resources to allow areas to recover. At the same time, the model of relying on an oracle bone also makes it simpler than doing an exhaustive search of your "food-space" and if anything goes awry, it's because you've misinterpreted the divine spirits or you've done something wrong or bad. It's easy to cooperate if you all blame the same thing. I think the article's tone is a bit on what I would wholeheartedly dismiss as outlandish numerology mysticism - were I to read this when I was just beginning to study mathematics. Now that I've read a bit more history, I have a better appreciation that humans by nature have always tried to impose order, symmetry and harmony upon the universe and have codified that language of understanding as poetry in all forms. I think the article is ambitious towards grasping at the scale and scope of mathematics not merely as a tool of human will, or a language science, or philosophy of philosophies, but something that is very palpably and tangibly human in form. There is a decent treatment towards the ambiguity of what an "algorithm" even is. My overall impression of the article is that it is trying to describe something beautiful about how the process of mathematics has acted upon itself. Models such as cellular automata or recursive processes show how complexity arises from simple rules - order from chaos, chaos from order. At the end of the day, I love to nitpick the treatment of technical subjects and their sort of phenomenal attributes in society - but it's posts like these on HackerNews that make me happy that anyone even bothers to write about this topic at all.
- keypusher 7y ago

76 points by chobeat 7y ago

"Even at the end of the twentieth century, no one would have ever thought to call a truck driver a “cognitive worker,” an intellectual. At the beginning of the twenty-first century, the use of machine learning in the development of self-driving vehicles has led to a new understanding of manual skills such as driving, revealing how the most valuable component of work, generally speaking, has never been merely manual, but also social and cognitive" This is the best quote from the article.

ArtWomb 7y ago

Nice to see e-flux, one of the oldest netart sites on the internet, still publishing. For a deeper dive into fascinating origins of materialism in Ancient Indian philosophy, the following provides a decent intro. "However, in importing these labels from Western philosophy to the classical Indian philosophical systems, one needs to exercise caution because the concepts of nature, science, scientific method, etc. do not smoothly converge in the two theoretical traditions." Naturalism in Classical Indian Philosophy https://plato.stanford.edu/entries/naturalism-india/ https://plato.stanford.edu/entries/naturalism-india/

xaedes 7y ago

Despite the way it is often framed and critiqued, artificial intelligence is not really “artificial” or “alien”: in the usual mystification process of ideology, it appears to be a deus ex machina that descends to the world like in ancient theater. But this hides the fact that it actually emerges from the intelligence of this world. What people call “AI” is actually a long historical process of crystallizing collective behavior, personal data, and individual labor into privatized algorithms that are used for the automation of complex tasks: from driving to translation, from object recognition to music composition. Just as much as the machines of the industrial age grew out of experimentation, know-how, and the labor of skilled workers, engineers, and craftsmen, the statistical models of AI grow out of the data produced by collective intelligence. I can totally resonate with that part

ralphstodomingo 7y ago
Quite a nice excerpt, will be reading the article now. We almost always discount the work done by our predecessors: NIH-syndrome/"reinventing the wheel" vs "standing in the shoulders of giants", and this was a humble reminder for me.
- gumby 7y ago
  > We almost always discount the work done by our predecessors: NIH-syndrome/"reinventing the wheel" vs "standing in the shoulders of giants", and this was a humble reminder for me. "We" being computer scientists (or computing) which for some reason has this disease, perhaps due to the field's newness? When I worked in the life sciences (pharmaceutical chemistry) the literature was the first place we looked. Whereas when working at a research lab in my 20s: I would often go down to our library and read CACM, IEEE journal et al and would sometimes implement things I read there. Even though I would brandish a photocopy of the journal article and reference it in the source code my boss and colleagues would praise me for "thinking up" a solution to a given problem. Ironically the Internet changed things dramatically in the physical sciences (in Physics especially* but in other physical sciences by making it much easier to both search and read the literature) whereas in non-academic computing it's been the small conferences and, to my surprise, Youtube. * Physics has long been an innovator in information dissemination; when journal publishing got too slow and letters too point-to-point it gave rise to Physics Letters, which itself became a pair of journals....
carapace 7y ago
Turing machines are essentially automation of Turing's thought processes, so, in a way, computers have always been AI.

voidhorse 7y ago

Great to see this on hacker news. E-flux publishes a lot of voices (artists, continental philosophers, and others) that have sound, intellectual criticisms about te ways we incorporate technology into our lives—and I think it’s important for tehnologists to hear them. It’s not common for these voices to reach traditional comp-sci/mega tech spheres. They put out a nice series of readers based on their journals and other material. I recently read a great one that collected some of the works of Hito Steyerl.

chobeat 7y ago
I'm trying to work in that direction on many fronts. Hackernews is not really one of them but this post was really in Hackernews style so I decided to post it here.
- voidhorse 7y ago
  That’s great. This is something I’m interested in as well. I found your critical essays repo on github. I have committed time to studying the philosophy of technology and am particularly familiar with the works of the Frankfurt school, some of Paul Virilio’s work, and the work of Lewis Mumford. I’d be happy to contribute if you’re looking for contributors for any critical projects.
  - chobeat 7y ago
    Well, if you want to suggest some proposal for the reading list, I would love to include your contributions. My projects are very local: Tech Worker Coalition in Berlin e Gambe.ro in Italy, so I don't think there's any room in those.

YeGoblynQueenne 7y ago

At the risk of sounding like a broken record I must point out that AI, neural networks, machine learning, Perceptrons, algorithms and deep learning are not interchangeable terms, any more than "maths" is interchangeable with "calculus", "trigonometry", "geometry", "algebra" and "arithmetic". Unfortunately this article is typically using such terms as synonyms and, while it's probably meant to help the lay reader understand a technical subject, will only manage to confuse the issue further. It's clear that there is intense interest in deep learning and machine learning in the last 7 years or so, but, especially when talking of "AI", it is important to remember that the majority of work in AI has _not_ been on machine learning, but on inference and reasoning, and using symbolic, logic-based techniques (including Bayesian reasoning, as in Solomonoff's Inductive Inference) rather than "statistical" methods (in the sense that the term is used in AI to mean everything from probabilities to calculus). Finally, there are historcial inaccuracies in this article. For example, Rosenblatt's Perceptron was not "the first machine-learning algorithm' as the article says: Arthur Samuel's self-playing checkers agents and Minsky's SNARC are two systems predating the Perceptron by a few years and research on machine learning techniques like Markov chains goes back to the 1910's.

chobeat 7y ago
While agree with you on the need to straighten the narrative and usage of these terms, the author is a philosopher and uses AI not in the common sense nor in the Computer Science sense. It is indeed confusing but he's very very rigorous in the way he writes (this is extremely simple writing for his usual style) so don't believe he's using the terms intercheangeably
- whatshisface 7y ago
  Most of these philosophical thinkpiece authors are charlatans. Charlatan philosophers can get along very well, even in professional circles, because there's almost no way to tell the difference between a true belief and a false belief in some areas of philosophy. However, they meet their downfall in articles like these, when they make the mistake of talking about something that is relatively easy to verify - revealing that they are sloppy thinkers with great English skills.

vertline3 7y ago

Algorithms aren't rituals, they are more concrete.

odomojuli 7y ago

I vaguely recall reading a paper about oracle bones and hunter-gatherers, with the central theme being a study of generating randomness by the means of an "algorithm". I recall it was on arxiv but that doesn't seem to be the case anymore. Algorithm being defined as: take a bunch of animal bones, burn them until they are essentially cremated, and then interpret the ashes somehow to point you in a random direction away from your village. The idea was that this is such a noisy and chaotic system that you get decent enough randomization to distribute your hunter-gatherers into wilderness. The reason this is economical is it allows you to distribute away from concentrating too much effort into just one particular zone. A key idea here is that while maybe a certain river or patch of grass might have been historically lucrative, eventually the population will be exhausted. Without doing ample surveys of the wilderness all the time, hunter-gatherers have scarcely a clue that they are exhausting its resources. So a simple strategy is to randomly distribute your collection of resources to allow areas to recover. At the same time, the model of relying on an oracle bone also makes it simpler than doing an exhaustive search of your "food-space" and if anything goes awry, it's because you've misinterpreted the divine spirits or you've done something wrong or bad. It's easy to cooperate if you all blame the same thing. I think the article's tone is a bit on what I would wholeheartedly dismiss as outlandish numerology mysticism - were I to read this when I was just beginning to study mathematics. Now that I've read a bit more history, I have a better appreciation that humans by nature have always tried to impose order, symmetry and harmony upon the universe and have codified that language of understanding as poetry in all forms. I think the article is ambitious towards grasping at the scale and scope of mathematics not merely as a tool of human will, or a language science, or philosophy of philosophies, but something that is very palpably and tangibly human in form. There is a decent treatment towards the ambiguity of what an "algorithm" even is. My overall impression of the article is that it is trying to describe something beautiful about how the process of mathematics has acted upon itself. Models such as cellular automata or recursive processes show how complexity arises from simple rules - order from chaos, chaos from order. At the end of the day, I love to nitpick the treatment of technical subjects and their sort of phenomenal attributes in society - but it's posts like these on HackerNews that make me happy that anyone even bothers to write about this topic at all.

keypusher 7y ago