Remember, kids:
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@lritter @swoonie @juergen_hubert
I should be clear that much of my post is in jest. I don't actually believe it could be true, just to highlight the fact that we can never know for sure.@MadCowKastor @swoonie @juergen_hubert jürgen explained it really well, so you should have gotten it.
otherwise, ask the clanker; even they understand it:
> what is the difference between colloquial "theory" and scientific "theory"?
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Remember, kids:
In proper scientific terms, an attempt to explain observable phenomena is called a "hypothesis".
It is called a "theory" when it fits all the observable facts, and there is no observable evidence to the contrary. We don't call it a "truth" because there's always a chance that it might be overturned by later evidence - but as far as science is concerned, a "theory" is as hard as it gets.
This is often confusing to people who dismiss science they don't like as "it's just a theory". But this distinction should be kept in mind when discussing things like the "Theory of Evolution", "Theory of Relativity", "Global Warming Theory", and "Dead Internet Theory".
#PSA #Evolution #GlobalWarming #DeadInternetTheory #Science #Theory
@juergen_hubert teacher here offering unsolicited advice.
This is great info, however, starting it off with “remember kids” can come across as patronizing and so people may get their backs up and check out before they get to the great points you make.
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Remember, kids:
In proper scientific terms, an attempt to explain observable phenomena is called a "hypothesis".
It is called a "theory" when it fits all the observable facts, and there is no observable evidence to the contrary. We don't call it a "truth" because there's always a chance that it might be overturned by later evidence - but as far as science is concerned, a "theory" is as hard as it gets.
This is often confusing to people who dismiss science they don't like as "it's just a theory". But this distinction should be kept in mind when discussing things like the "Theory of Evolution", "Theory of Relativity", "Global Warming Theory", and "Dead Internet Theory".
#PSA #Evolution #GlobalWarming #DeadInternetTheory #Science #Theory
@juergen_hubert didn't help that you put "dead internet theory" in there, since wikipedia says it's just a concept. probably your pet hypothesis.
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@juergen_hubert The people who try to discount evolution for being "just a theory" should also feel free to discount gravity for being "just a theory."
@ljwrites @juergen_hubert
Aren't there people who are actually doing that? -
@ljwrites @juergen_hubert
Aren't there people who are actually doing that?@t_robinart @juergen_hubert Yeah that's what I was referring to.
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Sorry to be a pedant, a Law is the hardest it gets. You can't fuck around with the Laws of Gravity.
Theories come and go and many are a work in progress: some withstand the test of experiment and observation better than others as the theory gets better and better at explaining all the facets of a phenomenon. However, as far as lay people are concerned, science as a constantly moving feast goes against the absolutism promoted by many non-scientists to justify the shit they come out with.@tribactam @juergen_hubert relevant natural law for Global warming (theory?)
https://en.wikipedia.org/wiki/Black-body_radiation#Planck's_law_of_black-body_radiation
https://en.wikipedia.org/wiki/Black-body_radiation#Effective_temperature_of_EarthAnd this law may (or may not) save us:
https://en.wikipedia.org/wiki/Stefan%E2%80%93Boltzmann_law -
@Virginicus @malte @juergen_hubert In the context here: Is Newton's theory still a (scientific) theory or just a formula good enough for many/most practical purposes?
@goedelchen @malte @juergen_hubert For me, it’s a perfectly good theory. Except that Newton thought of it as the “law of universal gravitation”, and it’s not quite universal. Now we know that a theory has to have a domain of validity attached.
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Remember, kids:
In proper scientific terms, an attempt to explain observable phenomena is called a "hypothesis".
It is called a "theory" when it fits all the observable facts, and there is no observable evidence to the contrary. We don't call it a "truth" because there's always a chance that it might be overturned by later evidence - but as far as science is concerned, a "theory" is as hard as it gets.
This is often confusing to people who dismiss science they don't like as "it's just a theory". But this distinction should be kept in mind when discussing things like the "Theory of Evolution", "Theory of Relativity", "Global Warming Theory", and "Dead Internet Theory".
#PSA #Evolution #GlobalWarming #DeadInternetTheory #Science #Theory
@juergen_hubert
Ask yourself, "How can I find out more about the 'Dead Internet Theory'"?
Then do it.
Bong hits 4 Jesus.
#DeadInternetTheory -
@juergen_hubert The people who try to discount evolution for being "just a theory" should also feel free to discount gravity for being "just a theory."
@ljwrites @juergen_hubert people who try to discount evolution are typically unable to accurately re-state the claims of evolution, and people really ought to start quizzing them when they speak up.
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@MadCowKastor @swoonie @juergen_hubert jürgen explained it really well, so you should have gotten it.
otherwise, ask the clanker; even they understand it:
> what is the difference between colloquial "theory" and scientific "theory"?
@lritter @MadCowKastor @swoonie @juergen_hubert "Clankers" understand nothing. They are not capable of engaging in dialectic and are algorithmic constructs which enumerate a Hilbert-space-like embedding via a net-of-neural-nets.
If straw man detection were a thing, that would be a killer app. But for the unreliable imitative narrators, which statistically approximate the outputs at the mercy of the system prompts and RLHF, reason is not possible.
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@ljwrites @juergen_hubert people who try to discount evolution are typically unable to accurately re-state the claims of evolution, and people really ought to start quizzing them when they speak up.
@ljwrites @juergen_hubert (e.g. if you hear someone say shit like, "i can't believe that the formation of life is all just random", that's when it's quiz time. remember, we're not looking for _agreement_; we're only looking for signs of _basic reading comprehension_.)
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@juergen_hubert Good reminder! One thing I'm missing from your description: Can you have competing scientific theories in your definition? I'm reminded of Kuhn's concept of paradigms which entails that there is always some conflicting evidence that any paradigm tends to dismiss (as noise, mistakes etc). Paradigms tend to shift when the conflicting evidence becomes overwhelming and a new theory manages to account for those previous exceptions.
Can you have competing scientific theories in your definition?
You can. You rarely have two theories that make exactly the same predictions. You often find that the differences are in things that are really hard to build experiments for (a lot of recent decades of physics has been about that: all of the things where the experiments are easy to do are fairly settled). It's fairly common to find that there are a few different models that all have the same behaviour in the common cases and make different predictions in outlying cases.
There is one special case, which Occam's Razor covers. If two theories provide the same set of predictions but one requires a superset of the things of the other, you should disregard the additional elements. This is because you can take any theory that provides useful predictions and add other irrelevant factors and create an infinite number of theories that make the same predictions. This doesn't mean that the more complex theories are wrong, it means that the additional factors are not providing useful information. If, at some point in the future, you come up with an experiment that would give different outcomes for the variants, you can add them back.
Newton's Laws are not a good example here because they are known to be wrong, they're kept around because they're useful. For anything much bigger than an atom or smaller than a moon (and slower than a satellite), the measurement errors that you get are likely to be much bigger than the errors from Newton's formulae. But the way in which they are wrong is very different for big things and small things. You can't predict the behaviour of electrons with general relativity and you can't predict the behaviour of gas giants with quantum mechanics. So there are a lot of attempts to build theories that work at both scales and then run experiments to attempt to falsify them.
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@ljwrites @juergen_hubert (e.g. if you hear someone say shit like, "i can't believe that the formation of life is all just random", that's when it's quiz time. remember, we're not looking for _agreement_; we're only looking for signs of _basic reading comprehension_.)
@ljwrites @juergen_hubert (i mean, if someone says, "i can't believe it's all just random", that's a pretty clear sign of reading comprehension failure, but it's important to drill down to the specific point of that particular person's failure.)
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Sorry to be a pedant, a Law is the hardest it gets. You can't fuck around with the Laws of Gravity.
Theories come and go and many are a work in progress: some withstand the test of experiment and observation better than others as the theory gets better and better at explaining all the facets of a phenomenon. However, as far as lay people are concerned, science as a constantly moving feast goes against the absolutism promoted by many non-scientists to justify the shit they come out with.You can't fuck around with the Laws of Gravity.
You absolutely can, Einstein did and this is why no one has the hubris of Newton when it comes to naming their theories anymore.
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@androcat @lritter @swoonie @juergen_hubert
One additional confusing (for lay people’s understanding of the word) issue is that theory also means “the entirety of human thought” on a given subject.
When we say music theory, we don’t mean that we’re speculating if music actually exists. We mean the entirety of what we think regarding how it works. Same for evolution. The theory of evolution is not a speculation on the existence of the phenomenon, it’s the totality of what we know about how it works. Well, technically it’s “what we think we know”.
On one hand I understand why this word is confusing and prone to misuse, on the other can’t get over the frustration that it is.
If only the average person wasn’t so insecure about uncertainty.
@CynAq @androcat @lritter @swoonie @juergen_hubert Having danced the dance of hypothesis across multiple chapters, I can tell you: an LLM couldn't actually do my job. And "the entirety of human thought" of which you write here is what compels me to respond, for the people who "boost" such things seem to fundamentally misunderstand that the sum total of human knowledge cannot truly be known, nor is it even VERBAL to begin with! To claim that the sum total of human knowledge is accessible to LLMs is the epitome of ignorance.
Dealing with uncertainty is the very apotheosis of abductive reasoning, the foundation of C.S. Peirce's philosophical school of Pragmatism. Humans do this all the time. 80s and 90s era GOFAI expert systems were capable of it to a degree, albeit with pre-coded heuristics. GPTs and DNN based systems and so forth use very computationally aggressive and energetically wasteful statistical approximation, with "inference" as a post-processing of the enumeration of said embedding. https://addxorrol.blogspot.com/2025/07/a-non-anthropomorphized-view-of-llms.html
There are definitely lessons to be learned from how the neural-net systems often approximate what would otherwise be a product of human reason badly, and that's the point: they cannot be said to be reasoning if one engages in functional decomposition of such systems, and leaves the "deus ex machina" interpretation to one side. The principle of logical parsimony at the heart of abduction (abductive reasoning) and the use of philosophical razors compel this; they require judgement and weighing-up of facts, which statistical systems do not do by definition. This is why I do not believe that these systems are capable of reason.
Knowing these things makes for stronger "human general intelligence" which, to be frank, is far more effective. Not infallible, but when LLMs go awry, they hit the bricks. -
@CynAq @androcat @lritter @swoonie @juergen_hubert Having danced the dance of hypothesis across multiple chapters, I can tell you: an LLM couldn't actually do my job. And "the entirety of human thought" of which you write here is what compels me to respond, for the people who "boost" such things seem to fundamentally misunderstand that the sum total of human knowledge cannot truly be known, nor is it even VERBAL to begin with! To claim that the sum total of human knowledge is accessible to LLMs is the epitome of ignorance.
Dealing with uncertainty is the very apotheosis of abductive reasoning, the foundation of C.S. Peirce's philosophical school of Pragmatism. Humans do this all the time. 80s and 90s era GOFAI expert systems were capable of it to a degree, albeit with pre-coded heuristics. GPTs and DNN based systems and so forth use very computationally aggressive and energetically wasteful statistical approximation, with "inference" as a post-processing of the enumeration of said embedding. https://addxorrol.blogspot.com/2025/07/a-non-anthropomorphized-view-of-llms.html
There are definitely lessons to be learned from how the neural-net systems often approximate what would otherwise be a product of human reason badly, and that's the point: they cannot be said to be reasoning if one engages in functional decomposition of such systems, and leaves the "deus ex machina" interpretation to one side. The principle of logical parsimony at the heart of abduction (abductive reasoning) and the use of philosophical razors compel this; they require judgement and weighing-up of facts, which statistical systems do not do by definition. This is why I do not believe that these systems are capable of reason.
Knowing these things makes for stronger "human general intelligence" which, to be frank, is far more effective. Not infallible, but when LLMs go awry, they hit the bricks. -
@deedo
Exactly. Although, in general using correlation to "prove" (and by extension "disprove") something is a very slippery slope at best. I always use this example when I'm explaining correlation:There is a perfect positive correlation between "being married" and "getting divorce", and even higher correlation between "being born" and "death", as you cannot have the latter without the former, and yet, neither means causality.
@Mehrad @deedo @juergen_hubert
Interestingly, the original meaning of 'prove' meant 'test'. Which is why you have sayings like 'the exception that proves the rule': it meant the exception that tested (and falsified) the rule.
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@androcat @bms @lritter @swoonie @juergen_hubert
was about to ask the same thing. Not that I disagree with the comment in a vacuum, but out of context here.
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@ljwrites @juergen_hubert (i mean, if someone says, "i can't believe it's all just random", that's a pretty clear sign of reading comprehension failure, but it's important to drill down to the specific point of that particular person's failure.)
@ljwrites @juergen_hubert also: for many topics, the "just a theory" nonsense may only be academic, but when it comes to evolution in particular, we actually have a civic responsibility to get more people to read about it, because it's impossible to understand public health issues without understanding evolution.
e.g.:
- everyone should have anticipated waves of variants of SARS-CoV-2.
- the fact that selective pressures apply to foodborne pathogens should feel obvious to everyone.
- etc
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@androcat @CynAq @lritter @swoonie @juergen_hubert I'm sure it crept into the thread somewhere, but the key point here is UNCERTAINTY. It's a lemma, a stepping stone. And I invoke the example of "what we're calling AI this week, depending on who you speak to" to illustrate the point. The GOFAI systems did handle it to some degree, the DNNs differ significantly in the technological approach used to emulating human cognitive capabilities and expression. When the "reasoning" of which one writes is actually a tie-break between an embedded token-based mapping, that surely does not resemble the weighing up of facts, at least to my mind, which leads back to the mistakes perhaps on the part of the lay person who cannot deal with uncertainty. But we do it all the time "under the hood" at a pre-conscious level. Just typing these words: uncertainty, in the neuro-chemical impulse of the fingers and their sense-feeling, not data, which can only ever be an approximation to what some might term qualia. There's something missing from the DNNs, that's obvious, but no one is putting their finger on it, hence the burden of proof arguments which arise on both "sides".
