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On anthropomorphism in science (1985)

cs.utexas.edu

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Re: On anthropomorphism in science (1985)

#21

Post by bitwize »

skybrian wrote: post #20

Apparently Dijkstra thought that if we could somehow think more abstractly and mathematically then we'd avoid making mistakes. But in practice, it seems to be the opposite: most people have a hard time thinking abstractly. We need analogies to make sense of things. For example, there was an experiment [1] showing that even basic logic is easier to handle if it's thought of as "detecting cheating" than as a pure logic…

Dijkstra wanted us to think on paper, use abstractions that accurately describe real-world systems, and arrive at answers methodically with a trail of checkable work. If our data and methods are sound our answers will always be correct.

Using just-so stories does nothing to aid in the methodical derivation of conclusions from premises; and can serve to obfuscate and confuse the issues.

Re: On anthropomorphism in science (1985)

#22

Post by Jtsummers »

Houshalter wrote: post #19
chickenfries wrote: post #17

Earlier quoted context omitted.

I think your language metaphor works here, but I won't try to extend it for fear of misleading you with anthropomorphism :) Anthropomorphized code reads like someone reading off a gigantic checklist that keeps getting longer and longer. Each time a new problem comes up, we solve it by adding another "If A then B" except it's something like this if foo.bar.baz[0][1]['value'] if (foo.bar.baz[0][1]['value'] == 'undocume…

My favorite examples of overreliance on conditionals: https://cdn.discordapp.com/attachments/285492834444771328/28... https://i.redd.it/6fh5xb20ttly.png http://i.imgur.com/GqcvMhp.png

Dear god, I think this would be what would drive coders mad if some Lovecraftian old one were a coder. I have a colleague that writes code like that last one. I know he won't change, but I wish he'd at least use a damned switch statement.

Re: On anthropomorphism in science (1985)

#23

Post by jamesrcole »

SomeStupidPoint wrote: post #6
FullMtlAlcoholc wrote: post #5

This issue is pernicious in the biological sciences. Evolution is often depicted as having a will and is referred to as a marvelous creator which completely misses the point of evolution, a system driven by simple instructions that over time create emergent complexity (like a cellular automata). People assume that their is some mechanism for adaptation exercised. Adaptation happens at the species level and the only t…

Does a baby have a will? How about a cat? Bacterium? I'm actually curious why people believe one emergent system does (eg, people) but another doesn't (eg, evolution/biosphere). What lets you determine when a composite object or pattern in an automata has crossed that threshold?

You're assuming it's a matter of some threshold (presumably of something like "complexity").

We have good reason to think that anything like "will" (leaving aside "free will" here, and just taking about things like the ability to achieve ends by developing plans and utilising information about the state of the environment) requires specific information processing capabilities. Capabilities that a process like natural selection does not have.

Re: On anthropomorphism in science (1985)

#24

Post by SomeStupidPoint »

jamesrcole wrote: post #23
SomeStupidPoint wrote: post #6

Earlier quoted context omitted.

Does a baby have a will? How about a cat? Bacterium? I'm actually curious why people believe one emergent system does (eg, people) but another doesn't (eg, evolution/biosphere). What lets you determine when a composite object or pattern in an automata has crossed that threshold?

You're assuming it's a matter of some threshold (presumably of something like "complexity"). We have good reason to think that anything like "will" (leaving aside "free will" here, and just taking about things like the ability to achieve ends by developing plans and utilising information about the state of the environment) requires specific information processing capabilities. Capabilities that a process like natural…

Or a threshold in information processing capabilities, yes. But could you describe these information processing capabilities?

Since evolution does process information about iterative states, it's not the mere existence of feedback, so there must be some threshold in capabilities that requires crossing.

Please describe them in a manner that includes or excludes as you see fit babies, cats, and bacteria but doesn't leave it a continuum (ie, there must be a cutoff where on one side you have some and the other none).

Re: On anthropomorphism in science (1985)

#25

Post by jamesrcole »

SomeStupidPoint wrote: post #24
jamesrcole wrote: post #23

Earlier quoted context omitted.

You're assuming it's a matter of some threshold (presumably of something like "complexity"). We have good reason to think that anything like "will" (leaving aside "free will" here, and just taking about things like the ability to achieve ends by developing plans and utilising information about the state of the environment) requires specific information processing capabilities. Capabilities that a process like natural…

Or a threshold in information processing capabilities, yes. But could you describe these information processing capabilities? Since evolution does process information about iterative states, it's not the mere existence of feedback, so there must be some threshold in capabilities that requires crossing. Please describe them in a manner that includes or excludes as you see fit babies, cats, and bacteria but doesn't lea…

Describing how evolution works, and why it is completely blind, is not something for the size constraints of a HN comment. I'd recommend books like Dawkin's "The Blind Watchmaker" or "Climbing Mount Improbable", or Dennett's "Darwin's Dangerous Idea" for good, readable descriptions.

Re: On anthropomorphism in science (1985)

#27

Post by goatlover »

SomeStupidPoint wrote: post #24
jamesrcole wrote: post #23

Earlier quoted context omitted.

You're assuming it's a matter of some threshold (presumably of something like "complexity"). We have good reason to think that anything like "will" (leaving aside "free will" here, and just taking about things like the ability to achieve ends by developing plans and utilising information about the state of the environment) requires specific information processing capabilities. Capabilities that a process like natural…

Or a threshold in information processing capabilities, yes. But could you describe these information processing capabilities? Since evolution does process information about iterative states, it's not the mere existence of feedback, so there must be some threshold in capabilities that requires crossing. Please describe them in a manner that includes or excludes as you see fit babies, cats, and bacteria but doesn't lea…

> Since evolution does process information about iterative states

Evolution is a computer?

> Please describe them in a manner that includes or excludes as you see fit babies, cats, and bacteria but doesn't leave it a continuum

What's the cutoff between a heap of and non-heap?

Re: On anthropomorphism in science (1985)

#28

Post by GuB-42 »

Our brain is for hunting and gathering.

We somehow managed to repurpose it for mathematics in a very short amount of time on the evolution timescale.

So while we are capable of abstraction, our brains work better when we rethink the problem in terms of throwing rocks. Anthropomorphism help us make our primitive mind and higher functions cooperate.

Re: On anthropomorphism in science (1985)

#30

Post by pdonis »

bitwize wrote: post #21
skybrian wrote: post #20

Apparently Dijkstra thought that if we could somehow think more abstractly and mathematically then we'd avoid making mistakes. But in practice, it seems to be the opposite: most people have a hard time thinking abstractly. We need analogies to make sense of things. For example, there was an experiment [1] showing that even basic logic is easier to handle if it's thought of as "detecting cheating" than as a pure logic…

Dijkstra wanted us to think on paper, use abstractions that accurately describe real-world systems, and arrive at answers methodically with a trail of checkable work. If our data and methods are sound our answers will always be correct. Using just-so stories does nothing to aid in the methodical derivation of conclusions from premises; and can serve to obfuscate and confuse the issues.

> Dijkstra wanted us to think on paper, use abstractions that accurately describe real-world systems, and arrive at answers methodically with a trail of checkable work. If our data and methods are sound our answers will always be correct.

I understand the aspiration, but I always think of the counterpoint implicit in Knuth's famous statement: "Beware of bugs in the above code; I have only proved it correct, not tried it."

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