A quoi sert la connaissance ? What is knowledge for?
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How can non-scientists influence the course of scientific research?

How can non-scientists influence the course of scientific research? | A quoi sert la connaissance ? What is knowledge for? | Scoop.it

Science communication should be more than the dissemination of results to the public; it should also flow in the other direction, with members of the public able to communicate their priorities to scientists and those who fund them. But how? (...) - by Cath Ennis, The Guardian, 23 October 2013

 

 


Via Collectif PAPERA, Julien Hering, PhD
La Life's insight:

Indeed - science communication should only secondarily be about results. It should be about engagement in the question of knowledge creation and knowledge validation.

 

Engagement through the question of selection of knowledge discovery, which questions we want answers to. That is very interesting.

 

I haven't read the article yet :)

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Biocentrism vs. Multiverse and backwards time

Biocentrism vs. Multiverse and backwards time | A quoi sert la connaissance ? What is knowledge for? | Scoop.it

Jerry Coyne summons Sean Carrol to take on biocentrism. It’s a fair fight.

La Life's insight:

The kind of claptrap that Lanza portrays in the Independent is what you reap when you sow unreal science.

 

Lanza’s unreal statements are legitimized in the public perception at least, by countless other bullshit that scientists peddle all the time as empirical truth to the public.

Three examples :

 the constant reference to the notion of "observer" in mainstream accounts of QM. Quantum indeterminacy and the collapse of the wave function/decoherence are not functions of "conscious observation", whether of Schrödinger’s cat or the photon going through the second slit. They are functions of whether there is some other thing there that interacts with the quantum system and reduces it. It has nothing to do with "observation". Keep talking about "conscious observers", and you’ll legitimize Lanza’s bunk.

 Multiverse theories : as long as cosmologists get credit for coming up with any bunk they feel like provided they show some half-consistent set of complex mathematical expressions that rely on the purely abstract concept of probability 1 at infinity, you will be legitimizing any crap that claims crazy stuff that we can’t observe can still be scientific. 


 Universe from nothing : yet another cosmological theory gleaming pseudo-data, removed from any real observations by several layers of maths and probabilities, relying on barely plausible interpretations, once again relying on probability 1 at infinity and making empirical truth claims about stuff that is ontologically outside of our experimental reach.

 

Sean talks of "mapping maths to observable things". Well, as long as you keep confusing the map with the territory, and end up believing that the maths IS the reality, this is what you get, and you have very little to oppose the crazies because, ultimately, you yourself give no credit to empirical validation to make truth claims.

 

That’s what I don’t understand about self-proclaimed "naturalists". It seems that, counterintuitively, these are the most egregiously platonician about their worldview, that the maths is indeed the real world, rather than an imperfect approximation.

 

Do we still have to remind ourselves that we can’t account for gravity, EM and nuclear forces out of the same consistent mathematical theory? Shouldn’t that give us a strong clue that we can’t claim our maths to actually BE reality, or even consistently map to it?

 

It’s only if you apply the same standards of self-criticism to yourself as you do to others, and most importantly not criticize them using arguments that could just as well be applied to yourself, and accept the fact that our current theories do not explain how nature is set up that you can then oppose rational empirical standards to crazy claims. Otherwise you don’t really have much standing.

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How can non-scientists influence the course of scientific research?

How can non-scientists influence the course of scientific research? | A quoi sert la connaissance ? What is knowledge for? | Scoop.it

Science communication should be more than the dissemination of results to the public; it should also flow in the other direction, with members of the public able to communicate their priorities to scientists and those who fund them. But how? (...) - by Cath Ennis, The Guardian, 23 October 2013

 

 


Via Collectif PAPERA, Julien Hering, PhD
La Life's insight:

Indeed - science communication should only secondarily be about results. It should be about engagement in the question of knowledge creation and knowledge validation.

 

Engagement through the question of selection of knowledge discovery, which questions we want answers to. That is very interesting.

 

I haven't read the article yet :)

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Determinism and finite states in algorithms

Determinism and finite states in algorithms | A quoi sert la connaissance ? What is knowledge for? | Scoop.it

In order to determine the complexity of an algorithm, you have to make the definitional assumption that the algorithm is determinisitic. .

La Life's insight:

The key insight is here, in the following couple of minutes, after the student attempts to answer the question:

http://www.youtube.com/watch?feature=player_detailpage&v=kqt-mfcm-FM#t=1614

 

In order to determine the complexity of an algorithm, which is the basis for all kinds of results about whether stuff is computable or not, you have to make the **definitional assumption** that the algorithm is determinisitic. More precisely, you have to assume that there exist things like:

- primitive operations

- states that are inputs or outputs that the primitive operations operate on

- that these are respectively deterministic and finite

 

Therefore, any attempt to justify deterministic processes of stuff by algorithmic theory is circular reasoning: algorithms are assumed to be determinisitic finite state machines.

 

Beyond that, even if that were abstractly true, the interaction of determinisitic processes whereby a particular process modifies the primitive operation while is is computing an input, or even modifies the input while it is being processed, creates the inability to pre-determine the outcome of the computation.

 

An argument that well, in that case all you have to do is to break down the algorithm and the inputs into smaller finite parts, so as to reach a point where all you have is a linear succession of steps, also relies on the assumption that this is possible in a consistent, reductionist manner that is not affected by limit conditions.

 

One of the keys here is the notion of what "deterministic" means, more specifically what kind of operational meaning we give it: does it mean that I can predict the outcome beforehand? Does it mean that "it couldn't have been otherwise", after the fact? There's a big, huge in fact, difference between the two, and I think that this is largely ignored in discussions about "determinisim".

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What is science for?

Can science still claim to the layman that it's working to empower them?

La Life's insight:

Very nice speech and discussion by Tyson. But beyond the ambition and the big projects, it's overlooked that science also has to project itself as being on the side of human empowerment. Modern scientific advoacy explaining that we are all zombies and/or mere computers, and maybe not even as good as computers to boot, is certainly not helping. This dire worldview is that of the major science advocates today. Worse: it is very likely wrong, certainly not established truth, yet these science advocates, while ostensibly advocating for evidence-based justified belief, cling to this non-truth as truth. I find it vile.

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Empathy: College students don't have as much as they used to

Today's college students are not as empathetic as college students of the 1980s and '90s, a University of Michigan study shows.

Via Ana Cristina Pratas
La Life's insight:

Empathy with things other than oneself may well be a key purpose of knowledge. In French, to "understand" is not etymologically to "support" or "provide a foundation" (under-stand), but to "take together", "take with" (com-prendre). It's a big difference. And knowledge is for understanding.

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Andrew McLaughin's curator insight, March 18, 2014 7:07 PM

This scoop sheds light on my topic because it introduces the "generation me" of college students that are neglecting their headphones. It also sheds light on why these students are so concerned with themselves and less with others. 

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Pleasure and emotion

Baroness Susan Greenfield CBE Hon FRCP, Member, House of Lords, United Kingdom, Professor of Synaptic Pharmacology, Lincoln College, Oxford University presen...
La Life's insight:

http://www.youtube.com/watch?v=WN5Fs6_O2mY&start=2646&end=2740

 

After what is a rather sane and semantically careful talk, Baronness Greenfield here lapses rather egregiously into self-serving biased interpretation.

 

From interesting remarks about neuron assemblies and how they get used by the brain, she ends up peddling a worldview of 'deep thought" and ' "meaning" ' (the term is actually between quotes - why?) being signs of clinical depression, whereas mindlessly seeking cognitive paucity through ecstasy and dance music would be, I don't know how to interpret otherwise what she's saying, a sign of mental health.

 

This is where these neuro-folks (but it's the case of most scientists, because they are human after all) have a real problem: they don't understand whence they are speaking from. They legitimately can (and maybe should?) have professional views about the nature of knowledge and truth and such, to frame and check their empirical work and conclusions. But to bring to their interpretation of empirical data their own biases, and smuggle them in unannounced, of what constitutes a good fun life vs. a bad depressed 'deep-thinking' life is pretty awful, albeit common...

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Meaningful answers in proofs

Meaningful answers in proofs | A quoi sert la connaissance ? What is knowledge for? | Scoop.it

It's a matter of judgement and experience to decide what you can discard from a formal expression yet retain a "meaningful answer".

La Life's insight:

Rather trivial insight here:

http://www.youtube.com/watch?feature=player_detailpage&v=yKp7dok7-Bg#t=1891

 

But worth noting that this type of thing comes up all the time in proofs or reasoning: it's a matter of judgement and experience to decide what you can discard from a formal expression yet retain a "meaningful answer".

 

To argue that "meaning" is in effect "meaningless", i.e. is in all cases just a causally ineffective epiphenomenon of underlying Shannon information, so to speak, doesn't hold up to scrutiny of how all this apparently purely formal scientific apparatus is actually designed: in many cases as soon as you start to try and formalize processes and causes, you will make some kind of decision to discard or simplify something, with **everybody agreeing** that the answer will remain meaningful.

 

It's not possible to argue that meaning is not operative in a context where people prove such statements and make judgement calls about what things mean.

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Meaningful Computational Complexity

Most of the problems that we're attempting to solve are computable, whereas mathematically most of the possible problems are uncomputable.

La Life's insight:

That's a truly interesting thing: most of the problems that we're attempting to solve are computable, whereas mathematically most of the possible problems are uncomputable.

 

The insight part is here: http://www.youtube.com/watch?v=moPtwq_cVH8&start=18:06&end=18:20

 

This says a lot to the effect that there are no answers without questions. Or, in other words, that the things we discover are the things that we conceivably are interested in discovering. The set of these problems are therefore those that, somehow, map to our cognitive interests, which have "evolved", or in any event represent thigns that matter to us, that can factor into outcomes that we care about. So, naturally, the questions we ask of the world are questions that actually have answers, whereas most of the actual answers (meaning things that actually come out of the universe's unfolding) are things that are beyond our cognition, including our computational and mathematical cognition. With some exceptions.

 

EDIT: Another key insight here, and in fact maybe more significant, is also that there are an infinite number of strings that an infinite roomful of monkeys can type, without all of these strings actually representing a question. To have a question and an answer requires semantics, not just binary information. It's wholly unclear what the ratio of meaningful strings over meaningless strings is in a random infinite set.

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NeuroLogica Blog » Extreme Dogmatism

NeuroLogica Blog » Extreme Dogmatism | A quoi sert la connaissance ? What is knowledge for? | Scoop.it
It is the standard skeptical narrative that people are biased in numerous ways. The 'default mode' of human behavior is to drift along with the currents of our...
La Life's insight:

The study is behind a paywall: can't check sources and data. Don't know what they really mean by "dogmatism" and "extremism".

 

The  definitions of terms, attitudes and "irrational" facts in this study are almost certainly wrong. I would like to check whether my suspicion that the authors of the study use trite, meaningless and/or unfalsifiable definitions of terms. but I can't without paying 35 bucks.

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La littérature, pour quoi faire ?

La littérature, pour quoi faire ? | A quoi sert la connaissance ? What is knowledge for? | Scoop.it
Auprès de la question théorique ou historique traditionnelle : « Qu'est-ce que la littérature ? », se pose avec plus d’urgence aujourd’hui une question critique et politique : « Que peut la littérature ?

Via reyser
La Life's insight:

La question de la fiction comme source de connaissance, qu'elle soit heuristique, d'intuition, factuelle, expositoire, de questionnement, de synthèse, de pertience, etc., est beaucoup trop souvent ignorée.

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