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> I wish ML researchers stopped using anthropomorphizing language. ML researchers don't write articles, journalists do. Actual language used by the ML researc

> I wish ML researchers stopped using anthropomorphizing language. ML researchers don't write articles, journalists do. Actual language used by the ML researchers: "Intuitive physics learning in a deep-learning model inspired by developmental psychology" [1] [1]: https://www.nature.com/articles/s41562-022-01394-8 https://www.nature.com/articles/s41562-022-01394-8

mikolajw 4y ago
You're right that journalists use anthropomorphization much more. But AI researchers also have a long history of choosing terms that are anthropomorphizing or animating. Here the name PLATO -- which evokes an image of an ancient philosopher, a human, who is by cultural tradition considered smart -- is used in the original journal article. Terms like "neural network" and "artificial intelligence" are frequently used by AI engineers and researchers despite the obvious image they evoke. Sometimes they even call their creations "brains". Also note the name DeepMind. It's definitely not just the journalists.
bluetwo 4y ago
To add to that, often EDITORS are the ones who come up with the titles, for reasons beyond being clear, like using words that draw attention and to fit in a specific space.
_gabe_ 4y ago
> Actual language used by the ML researchers: "Intuitive physics learning in a deep-learning model inspired by developmental psychology" In my opinion, this is still anthropomorphizing the algorithms. The term deep-learning is a poor representation of what actually goes on. Someone please correct me if I'm wrong, but all ML does is statistical regressions (in essence). It doesn't "learn" like a person learns. Neural networks are not actually like brains (as far as we understand how the brain works). I feel like the whole industry is inundated with aphorisms that are kind of true, but not wholly true. Evolutionary algorithms, neural networks, deep learning, deep mind, this stuff all reeks of anthropomorphizing fundamentally mathematical processes. I get it, it's a lot easier to get the gist of "the computer is learning/training" than "the computer is refining the weights and biases to try to optimize the output".
- kupopuffs 4y ago
  it's metaphors all the way down. deep learning isn't a bad name imo. it is learning, but nothing in the name suggests it's like a human brain.
- FeepingCreature 4y ago
  Seems anthropocentric. Humans don't have a monopoly on learning.
- mdp2021 4y ago
  > It doesn't "learn" like a person learns Who cares? Why should you hold the idea that it would? They are systems moulded after data, 'learn' seemed to be a decent label. If it is not, it is because "learning" is _active_, by philological analysis, and happily consistently with an aim of AGI (intelligent entities learn actively). A computer does not compute like a human would. Yet, no problem. For that matter, you are using 'person' in a very individual way - not even "personal" (a "person" learns according to individual nature, while you are using it as a collective term). As already expressed - nearby I wrote 'biomimicry' -, what you are calling "anthropomorphizing" is a wrong direction: "evolutionary algorithms" were born out of keys after the observation of the natural world, and the terms express that - it is not that you saw the algorithm and went "It looks like my uncle Oscar"¹ (this side is active - it "learns"). (¹Those anthropomorphizing Hollywood cultists and all that sculpture...)
  - _gabe_ 4y ago
    > Who cares? > a "person" learns according to individual nature, while you are using it as a collective term There's a very specific definition for learn: >> to gain knowledge or understanding of or skill in by study, instruction, or experience[0] There's a few more, but none of the definitions treat learn in a non-collective way. I guess meriam Websters dictionary doesn't like treating people as individuals or something lol. Additionally, all the definitions there are speaking in human contexts. They talk about learning in the sense of being taught, or gaining experience, or gaining knowledge. Sure a computer kind of does this stuff, but it doesn't really. And that falls into the category of attributing human characteristics to an inanimate object. I probably shouldn't have said that everything in the short list I wrote reeked of anthropomorphizing processes. But the evolutionary algorithm was more in line with what I mentioned immediately before. My whole comment read: > I feel like the whole industry is inundated with aphorisms that are kind of true, but not wholly true. Evolutionary algorithms, neural networks, deep learning, deep mind, this stuff all reeks of anthropomorphizing fundamentally mathematical processes. An evolutionary algorithm definitely falls into the category of kind of true but not wholly true. But it's not anthropomorphic. > intelligent entities learn actively Also, this is a very loaded statement. What is an intelligent entity? If you Google "is a computer intelligent" there are various papers, articles, and other pieces of media all claiming that we can't call a computer intelligent, and some claiming that we can consider certain algorithms somewhat intelligent. This is anything but an accepted standard today. [0]: https://www.merriam-webster.com/dictionary/learn https://www.merriam-webster.com/dictionary/learn

mikolajw 4y ago

You're right that journalists use anthropomorphization much more. But AI researchers also have a long history of choosing terms that are anthropomorphizing or animating. Here the name PLATO -- which evokes an image of an ancient philosopher, a human, who is by cultural tradition considered smart -- is used in the original journal article. Terms like "neural network" and "artificial intelligence" are frequently used by AI engineers and researchers despite the obvious image they evoke. Sometimes they even call their creations "brains". Also note the name DeepMind. It's definitely not just the journalists.

bluetwo 4y ago

To add to that, often EDITORS are the ones who come up with the titles, for reasons beyond being clear, like using words that draw attention and to fit in a specific space.

_gabe_ 4y ago

> Actual language used by the ML researchers: "Intuitive physics learning in a deep-learning model inspired by developmental psychology" In my opinion, this is still anthropomorphizing the algorithms. The term deep-learning is a poor representation of what actually goes on. Someone please correct me if I'm wrong, but all ML does is statistical regressions (in essence). It doesn't "learn" like a person learns. Neural networks are not actually like brains (as far as we understand how the brain works). I feel like the whole industry is inundated with aphorisms that are kind of true, but not wholly true. Evolutionary algorithms, neural networks, deep learning, deep mind, this stuff all reeks of anthropomorphizing fundamentally mathematical processes. I get it, it's a lot easier to get the gist of "the computer is learning/training" than "the computer is refining the weights and biases to try to optimize the output".

kupopuffs 4y ago
it's metaphors all the way down. deep learning isn't a bad name imo. it is learning, but nothing in the name suggests it's like a human brain.
FeepingCreature 4y ago
Seems anthropocentric. Humans don't have a monopoly on learning.
mdp2021 4y ago
> It doesn't "learn" like a person learns Who cares? Why should you hold the idea that it would? They are systems moulded after data, 'learn' seemed to be a decent label. If it is not, it is because "learning" is _active_, by philological analysis, and happily consistently with an aim of AGI (intelligent entities learn actively). A computer does not compute like a human would. Yet, no problem. For that matter, you are using 'person' in a very individual way - not even "personal" (a "person" learns according to individual nature, while you are using it as a collective term). As already expressed - nearby I wrote 'biomimicry' -, what you are calling "anthropomorphizing" is a wrong direction: "evolutionary algorithms" were born out of keys after the observation of the natural world, and the terms express that - it is not that you saw the algorithm and went "It looks like my uncle Oscar"¹ (this side is active - it "learns"). (¹Those anthropomorphizing Hollywood cultists and all that sculpture...)
- _gabe_ 4y ago
  > Who cares? > a "person" learns according to individual nature, while you are using it as a collective term There's a very specific definition for learn: >> to gain knowledge or understanding of or skill in by study, instruction, or experience[0] There's a few more, but none of the definitions treat learn in a non-collective way. I guess meriam Websters dictionary doesn't like treating people as individuals or something lol. Additionally, all the definitions there are speaking in human contexts. They talk about learning in the sense of being taught, or gaining experience, or gaining knowledge. Sure a computer kind of does this stuff, but it doesn't really. And that falls into the category of attributing human characteristics to an inanimate object. I probably shouldn't have said that everything in the short list I wrote reeked of anthropomorphizing processes. But the evolutionary algorithm was more in line with what I mentioned immediately before. My whole comment read: > I feel like the whole industry is inundated with aphorisms that are kind of true, but not wholly true. Evolutionary algorithms, neural networks, deep learning, deep mind, this stuff all reeks of anthropomorphizing fundamentally mathematical processes. An evolutionary algorithm definitely falls into the category of kind of true but not wholly true. But it's not anthropomorphic. > intelligent entities learn actively Also, this is a very loaded statement. What is an intelligent entity? If you Google "is a computer intelligent" there are various papers, articles, and other pieces of media all claiming that we can't call a computer intelligent, and some claiming that we can consider certain algorithms somewhat intelligent. This is anything but an accepted standard today. [0]: https://www.merriam-webster.com/dictionary/learn https://www.merriam-webster.com/dictionary/learn