adding page while reading Lisa Margonelli @LisaMargonelli’s underbug
what makes stigmergy spectacular as a concept is that is doesn’t just describe how termites build; it also makes it *possible to predict what will be built..t
*how so..? i don’t see stigmergy as predictable
i asked him about superorganisms.. is the mound a body?.. t
i’m thinking only if we don’t define/predict/mechanize the mound.. just like the city.. once we plan/strategize it.. it’s no longer alive.. so can no longer be organism as fractal
he said he thought the link between the organization of bodies and of termite mounds was homeostasis: cells build bones and termites build mounds that create an environ suitable for their survival. ‘there are tough questions a scientist has to confront. why do we say the termite is alive but not the mound?.. the mound does things the termite can’t do.. you need to think about the organism extending outside itself thru the mound. *it’s impossible to be alive w/o changing the environ you live in’..t
and i’d say… *it’s impossible to be alive and predictable..
and while reading this from Steven Johnson:
Aditya Bapat (@adityasbapat) tweeted at 7:52 AM on Tue, Nov 20, 2018:
This has to be the best article I have read this year. It’s on the brain, it’s capacity to wander, and the implication of machines that do it for us and better than us. https://t.co/macUOAecPf
“Apparently, when the brain/mind thinks in a free and unencumbered fashion,” she wrote, “it uses its most human and complex parts.”
In 2001, Randy Buckner’s adviser at Washington University, Marcus Raichle, coined a new term for the phenomenon: the “default-mode network,” or just “the default network.” The phrase stuck. Today, Google Scholar lists thousands of academic studies that have investigated the default network. “It looks to me like this is the most important discovery of cognitive neuroscience,” says the University of Pennsylvania psychologist Martin Seligman. The seemingly trivial activity of mind-wandering is now believed to play a central role in the brain’s “deep learning,” the mind’s sifting through past experiences, imagining future prospects and assessing them with emotional judgments: that flash of shame or pride or anxiety that each scenario elicits.
“What best distinguishes our species,” Seligman wrote in a Times Op-Ed with John Tierney, “is an ability that scientists are just beginning to appreciate: We contemplate the future.” He went on: “A more apt name for our species would be Homo prospectus, because we thrive by considering our prospects. The power of prospection is what makes us wise.”
? – i don’t know
If the Homo prospectus theory is correct, those limited time-traveling skills explain an important piece of the technological gap that separates humans from all other species on the planet. It’s a lot easier to invent a new tool if you can imagine a future where that tool might be useful. What gave flight to the human mind and all its inventiveness may not have been the usual culprits of our opposable thumbs or our gift for language. It may, instead, have been freeing our minds from the tyranny of the present.
ugh.. i don’t think that’s a good thing
this poem by Nic Askew resonates w my ‘ugh’
in the dreams you so
spoke his soul.‘When you were a boy
you had no time
for such dreams.The electricity of the world
under your feet was enough.’
Agriculture itself would have been unimaginable without a working model of the future: predicting seasonal changes, visualizing the long-term improvements possible from domesticating crops.
yeah.. i don’t see agri as benefitting an undisturbed ecosystem
Banking and credit systems require minds capable of sacrificing present-tense value for the possibility of greater gains in the future. For vaccines to work, we needed patients willing to introduce a potential pathogen into their bodies for a lifetime of protection against disease.
wow.. i see those of symptoms of disturbing an undisturbed ecosystem.. not benefits
We are born with a singular gift for imagining the future, but we have been enhancing those gifts since the dawn of civilization. Today, new enhancements are on the horizon, in the form of machine-learning algorithms that already outperform humans at certain kinds of forecasts. As A.I. stands poised to augment our *most essential human talent, we are faced with a curious question: How will the future be different if we get much better at **predicting it?
i see **predict\able ness as a disturbance/symptom of an undisturbed ecosystem
so what’s the diff between imagining (because i see that as good) and predicting..? (i asked myself).. i’m thinking it’s the assumption of particulars (see below ‘a specified thing) that comes w predicting..
ie: a nother way.. is imagining an undisturbed ecosystem.. but key to it is that the particulars emerge.. they have to be emergent.. or it’s not an alive system.. not organism as fractal
We have long heard promises of “smart drugs” on the horizon that will enhance our memory, but if the Homo prospectus argument is correct, we should probably be looking for breakthroughs that will enhance our predictive powers as well.
disturbance/symptom of a disturbed ecosystem
Accurate weather forecasting is merely one early triumph of software-based time travel: algorithms that allow us to peer into the future in ways that were impossible just a few decades ago, what a new book by a trio of University of Toronto economists calls “prediction machines.” In machine-learning systems, algorithms can be trained to generate remarkably accurate predictions of future events by combing through vast repositories of data from past events. An algorithm might be trained to predict future mortgage defaults by analyzing thousands of home purchases and the financial profiles of the buyers, testing its hypotheses by tracking which of those buyers ultimately defaulted.
all i can think of now is..we’re not being careful and we are missing it..
ie mufleh humanity law: we have seen advances in every aspect of our lives except our humanity – Luma Mufleh
ginorm small zoom dance
his ie’s are so manufactured: getting a job; buying a house; market; school;..
Whether you find the idea of augmenting the default network thrilling or terrifying, one thing should be clear: These tools are headed our way. In the coming decade, many of us will draw on the forecasts of machine learning to help us muddle through all kinds of life decisions: career changes, financial planning, hiring choices. These enhancements could well turn out to be the next leap forward in the evolution of Homo prospectus, allowing us to see into the future with more acuity — and with a more nuanced sense of probability — than we can do on our own.
termite\ing us.. getting us to sync up to an algo/repetition – Lisa Margonelli
The Homo prospectus theory suggests that, if anything, we need to carve out time in our schedule — and perhaps even in our schools — to let minds drift.
yeah.. but not for the purpose of predicting.. for the purpose of being alive.. what we need most.. the energy of 7bn alive people
“The brain’s default-mode network appears to preserve the capacity for plasticity into adulthood,” he told me.
antifragile.. entropy.. all that.. makes/keeps us alive.. but specific predicting.. killer
begs we let go and free art ists (from bot ism).. in the city.. as the day..
John Hagel (@jhagel) tweeted at 7:09 AM – 21 Nov 2018 :
Exploring some of the early investigators of chaos theory – embarking on a quest to extract ordered structures from a sea of chaos. Surprised it does not mention the Santa Fe Institute where much of this work is done today https://t.co/5fFPSmILdD(http://twitter.com/jhagel/status/1065245789809713154?s=17)
Poincaré identified the unpredictability of the system and wrote: “It may happen that small differences in the initial conditions produce very great ones in the final phenomena. A small error in the former will produce an enormous error in the latter. Prediction becomes impossible.”
Chaos theory became the perfect mathematical tool to extract ordered structures from a sea of chaos. It is based on two main ideas: 1) even complex systems contain an underlying order, and 2) in these systems, small differences in initial conditions (e.g. small temperature variations) produce very divergent results, which means that, in general, the prediction of their long-term behaviour is impossible (mathematically, we say that the system has a strong dependence on the initial conditions).
This happens even though the behaviour of these phenomena is completely determined by their initial conditions, without involving any type of random elements. In other words, the deterministic nature of these systems does not make them predictable, although, at the very least, thanks to chaos theory it is possible to analyse their unpredictability from a strategic point of view.
Matt Ballantine (@ballantine70) tweeted at 2:59 PM on Thu, Nov 22, 2018:
Blimey. We’re only 13 months away from the point at which a huge bucket load of corporate “2020 Visions” will expire as people don’t even realise they haven’t been realised…
in Hannah Arendt‘s on violence
since the end of human action, as distinct from the end products of fabrication, can never be reliably predicted, the means used to achieve political goals are more often than not of greater relevance to the future world than the intended goals..
predictions of the future are never anything but projection of present automatic processes and procedures that is, of occurrences that are likely to come to pass if men do not act and if nothing unexpected happens; ..
cory on predict\able ness
un1crom (@un1crom) tweeted at 2:52 AM – 30 Dec 2019 :
“I make no claim to predicting the future. I make up stories. Stories are better than predictions: predictions tell us that the future is inevitable. Stories tell us that the future is up for grabs.” -@doctorow is wise. https://t.co/1TR5X3jDI0(http://twitter.com/un1crom/status/1211585769976012801?s=17)
from Jim Al-Khalili in secret life of chaos (doc):
the idea that a math eq gave you the power to predict how a system will behave was dead..t
predict able ness
32 min – it seemed unpredictability was hard wired into every aspect of the world we live in.. the global climate.. the stock market.. could change in course of few short years.. without warning.. could be wiped from face of planet overnight (nuclear) and there was nothing anyone could do about it
unfortunately i have to tell you.. that all of this is true.. and yet..
to be scared of chaos is pointless..t
it’s woven into the basic laws of physics… and we really all have to accept it as a fact of life..
probably first place i started feeling more boldly about predict\able ness being a huge red flag.. david graeber‘s theory of value ie:
p. 50 – if objects are in constant flux, even precise spatial measures are impossible..tone can take an object’s measure at a particular moment and then treat that as representative, but even this is something of an imaginary construct, because such “moments” (in the sense of points in time, of no duration, infinitely small) do not really exist – they, too, are imaginary constructs. it has been precisely such imaginary constructs (“models”) that have made modern science possible…
again.. if legit alive can’t be static.. so can’t be compared.. ie: graeber values law
we need to let go of any form of m\a\p
p. 51 – something ironic: what ricoeur is suggesting is that we have been able to create a technology capable of giving us hitherto unimaginable power to transform the world, largely because we were first able to imagine a world without powers or transformations. it may well be true. the crucial thing, though, is that in doing so, we have also lost something. because once one is accustomed to a basic apparatus for looking at the world that starts from an imaginary, static, parmenidean world outside of it, connecting the two becomes an overwhelming problem. ….bhaskar has been arguing for some years now that since parmenides, western philosophy has been suffering from what he calls an ‘epistemic fallacy’: a tendency to confuse the question of how we can know things with the question of whether those things exist.
intellect ness.. hubris ness.. et al.. making us all like whales
at its most extreme, this tendency opens into positivism: the assumption that give sufficient time and sufficiently accurate instruments, it should be possible to make models and reality correspond entirely.. predict precisely what would happen .. since *no one has been able to do anything of the sort, the position has tendency to generate its opposite.. a kind of aggressive nihilism .. saying.. if can’t come up w perfect descriptions.. impossible to talk about reality at all.. why most of us ordinary mortals find philosophical debates so pointless.. in contradiction w ordinary life experience..
*and won’t ever.. ie: what computers can’t do et al
graeber unpredictability/surprise law et al
.. most of us are accustomed to describe things as “realities” precisely because we can’t completely understand them, can’t completely control them, don’t know exactly how they are going to affect us, but nonetheless can’t just wish them away. it’s what we don’t know about them that brings home the fact that they are real.
grokking as ongoingly becoming rather than knowing in time/permanence/fragility et al.. which (to me) only happens when we let go of our focus obsession on intellect ness/understanding/meaning/defining/predicting.. any form of m\a\p
p. 52 – in alternative, heraclitean strain has always existed – one that sees objects as processes.. best-known .. via Hegel and Marx. but whatever form.. has been almost impossible to integrate with more conventional philosophy. it has tended to be seen as existing somewhat off to the side, as odd or somewhat mystical.
bhaskar – and those who have since taken up some version of his ‘critical realist’ approach: have been trying for some years to develop amore reasonable ontology.. some of his conclusions:
1\ realism – rather than limiting to what can be observed by senses.. ask ‘what would have to be the case’ in order to explain what we do experience.. ‘why are sci experiments possible/necessary’
2\ potentiality – reality not limited to what we can experience (empirical).. so even to sum total of events said to have taken place (actual).. rather third level (real).. that there’s no end to the pursuit does’t mean reality doesn’t exist; rather.. simply means one will never be able to understand it completely
3\ freedom – reality can be divided into emergent stratum: just as chem presupposed but cannot be entirely reduce to physics, so bio presupposes but cannot be reduced to chem.. diff sorts of mechs are operating on each.. each achieves a certain autonomy from those below.. it would be impossible even to talk about human freedom were this not the case, since our actions would simply be determine by chem/bio processes
4\ open systems – real world events occur in open systems.. there are always different sorts of mechanisms, derived from different emergent strata of reality, at play in any one of them. as a result, *one can never predict precisely how any real-world event will turn out. this is why scientific experiments are necessary: experiment are ways of creating temporary “closed systems” in which the effects of all other mechanisms are, as far as possible, nullified, so that one can actually examine a single mechanism in action.
5\ tendencies – so best to not refer to unbreakable scientific laws.. but rather tendencies..which interact in unpredictable ways. of course, the higher the emergent strata one is dealing with, *the less predictable things become, the involvement of human beings of course being the most unpredictable factor of all..t
*huge..and *huge .. thinking we have predict\able ness as huge red flag we’re doing it/life wrong.. because essentially we’re killing the alive ness of it/life/us
graeber unpredictability/surprise law
p. 53 – ..not a matter of abandoning science but is, rather, the only hope of giving science a solid ontological basis. but it also means that in order to do so, those who wish to make claims to science will have to abandon some of their most ambitious – one is tempted to say, totalitarian, paranoid – dreams of absolute or total knowledge, and accept a certain degree of humility about what it is possible to know. reality is what one can never know completely. if an object is real, any description we make of it will necessarily be partial and incomplete. that is indeed how we can tell it is real. the only things we can hope to know perfectly are ones that exist entirely in our imaginations..t
… bhaskar’s ultimate interest is social; he is trying to come up with the philosophical ground for a theory of human emancipation, a way of squaring scientific knowledge with the idea of human freedom. here, too, the ultimate message is one of humility: critical realists hold that it is possible to preserve the notion of a social reality and, therefore, of a science able to make true statements about it – but only if one abandons the sort of positivist number-crunching that passes for science among most current sociologists or economists, and gives up the idea that social science will ever be able to establish predictive laws.
dang.. graeber’s writings/findings are where all my deep thinking is found/ed.. where it’s resonated.. oh my
and so too.. bhaskar’s.. unpredictability ness.. et al.. can’t know ness
we say predict in order to be more ie: efficient.. or whatever.. but really all about control.. any form of m\a\p
graeber unpredictability/surprise law