Posts Tagged ‘complexity’
“The brain has corridors surpassing / Material place…”*
Our brains, Luiz Pessoa suggests, are much less like machines than they are like the murmurations of a flock of starlings or an orchestral symphony…
When thousands of starlings swoop and swirl in the evening sky, creating patterns called murmurations, no single bird is choreographing this aerial ballet. Each bird follows simple rules of interaction with its closest neighbours, yet out of these local interactions emerges a complex, coordinated dance that can respond swiftly to predators and environmental changes. This same principle of emergence – where sophisticated behaviours arise not from central control but from the interactions themselves – appears across nature and human society.
Consider how market prices emerge from countless individual trading decisions, none of which alone contains the ‘right’ price. Each trader acts on partial information and personal strategies, yet their collective interaction produces a dynamic system that integrates information from across the globe. Human language evolves through a similar process of emergence. No individual or committee decides that ‘LOL’ should enter common usage or that the meaning of ‘cool’ should expand beyond temperature (even in French-speaking countries). Instead, these changes result from millions of daily linguistic interactions, with new patterns of speech bubbling up from the collective behaviour of speakers.
These examples highlight a key characteristic of highly interconnected systems: the rich interplay of constituent parts generates properties that defy reductive analysis. This principle of emergence, evident across seemingly unrelated fields, provides a powerful lens for examining one of our era’s most elusive mysteries: how the brain works.
The core idea of emergence inspired me to develop the concept I call the entangled brain: the need to understand the brain as an interactionally complex system where functions emerge from distributed, overlapping networks of regions rather than being localised to specific areas. Though the framework described here is still a minority view in neuroscience, we’re witnessing a gradual paradigm transition (rather than a revolution), with increasing numbers of researchers acknowledging the limitations of more traditional ways of thinking…
Complexity, emergence, and consciousness: “The entangled brain” from @aeon.co. Read on for the provocative details.
* Emily Dickinson
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As we think about thinking, we might send amibivalent birthday greetings to Robert Yerkes; he was born on this date in 1876. A psychologist, ethnologist, and primatologist, he is best remembered as a principal developer of comparative (animal) psychology in the U.S. (his book The Dancing Mouse (1908), helped established the use of mice and rats as standard subjects for experiments in psychology) and for his work in intelligence testing.
But in his later life, Yerkes began to broadcast his support for eugenics. These views are broadly considered specious– based on outmoded/incorrect racialist theories— by modern academics.
“I think the next century will be the century of complexity”*…
… and as Philip Ball reports, a team of scientists at Carnegie Science agrees…
In 1950 the Italian physicist Enrico Fermi was discussing the possibility of intelligent alien life with his colleagues. If alien civilizations exist, he said, some should surely have had enough time to expand throughout the cosmos. So where are they?
Many answers to Fermi’s “paradox” have been proposed: Maybe alien civilizations burn out or destroy themselves before they can become interstellar wanderers. But perhaps the simplest answer is that such civilizations don’t appear in the first place: Intelligent life is extremely unlikely, and we pose the question only because we are the supremely rare exception.
A new proposal by an interdisciplinary team of researchers challenges that bleak conclusion. They have proposed nothing less than a new law of nature, according to which the complexity of entities in the universe increases over time with an inexorability comparable to the second law of thermodynamics — the law that dictates an inevitable rise in entropy, a measure of disorder. If they’re right, complex and intelligent life should be widespread.
In this new view, biological evolution appears not as a unique process that gave rise to a qualitatively distinct form of matter — living organisms. Instead, evolution is a special (and perhaps inevitable) case of a more general principle that governs the universe. According to this principle, entities are selected because they are richer in a kind of information that enables them to perform some kind of function.
This hypothesis, formulated by the mineralogist Robert Hazen [here] and the astrobiologist Michael Wong [here] of the Carnegie Institution in Washington, D.C., along with a team of others, has provoked intense debate. Some researchers have welcomed the idea as part of a grand narrative about fundamental laws of nature. They argue that the basic laws of physics are not “complete” in the sense of supplying all we need to comprehend natural phenomena; rather, evolution — biological or otherwise — introduces functions and novelties that could not even in principle be predicted from physics alone. “I’m so glad they’ve done what they’ve done,” said Stuart Kauffman, an emeritus complexity theorist at the University of Pennsylvania. “They’ve made these questions legitimate.”…
[Ball explains the origin and outline of Hazen’s and Wong’s conjecture, explores the critiques– among them, that it’s not clear how to test the hypothesis– and examines the resonant work on Assembly Theory being done by Lee Cronin and Sara Walker…]
… Wong said there is more work still to be done on mineral evolution, and they hope to look at nucleosynthesis and computational “artificial life.” Hazen also sees possible applications in oncology, soil science and language evolution. For example, the evolutionary biologist Frédéric Thomas of the University of Montpellier in France and colleagues have argued that the selective principles governing the way cancer cells change over time in tumors are not like those of Darwinian evolution, in which the selection criterion is fitness, but more closely resemble the idea of selection for function from Hazen and colleagues.
Hazen’s team has been fielding queries from researchers ranging from economists to neuroscientists, who are keen to see if the approach can help. “People are approaching us because they are desperate to find a model to explain their system,” Hazen said.
But whether or not functional information turns out to be the right tool for thinking about these questions, many researchers seem to be converging on similar questions about complexity, information, evolution (both biological and cosmic), function and purpose, and the directionality of time. It’s hard not to suspect that something big is afoot. There are echoes of the early days of thermodynamics, which began with humble questions about how machines work and ended up speaking to the arrow of time, the peculiarities of living matter, and the fate of the universe…
A new suggestion that complexity increases over time, not just in living organisms but in the nonliving world, promises to rewrite notions of time and evolution: “Why Everything in the Universe Turns More Complex,” from @philipcball.bsky.social and @quantamagazine.bsky.social.
See also: Benjamin Bratton‘s explantion of the work he and his collegues are doing at a new institute at UCSD: “Antikythera.” See his recent Long Now Foundation talk on this same subject here.
* Stephen Hawking
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As we celebrate complication, we might spare a thought for G. N. Ramachandran (Gopalasamudram Narayanan Ramachandran); he died on this date in 2001. A biophysicist, he discovered the triple helical “coiled coil” structure of the collagen molecule, among other remarkable contributions to structural biology.
Ramachandran was a master of X-ray crystallography, and with his colleagues, constructed space filling models of protein molecules. He devised the Ramachandran Plot, a method to diagram the conformation of polypeptides, polysaccharides and polynucleotides– which remains the international standard to describe protein structures.
Ramachandran, inspired by the ancient Syaad Nyaaya (doctrine of “may be”), also explored artificial intelligence. He developed the Boolean Vector Matrix Formulation which has important application in writing software for AI.
“Tennyson said that if we could understand a single flower we would know who we are and what the world is”*…
Reality feels “stable” enough to talk about it– though all logic seems to point away from that possibility. Marco Giancotti unpacks what he suggests is the only line of reasoning that resolves that paradox…
What is the source of what we call order? Why do many things look too complex, too perfectly organized to arise unintentionally from chaos? How can something as special as a star or a flower even happen? And, for that matter, why do some natural phenomena seem designed for a purpose?
We live in a universe of forces eternally straining to crush things together or tear them apart. There is no physical law for “forming shapes”, no law for being separated from other things, no law for staying still.
Boundaries are in the eye of the beholder, not in the world out there. Out there is only tumult, clashing, and shuffling of everything with everything else.
And yet, our familiar world is filled with things stable and consistent enough for us to give them names—and to live our whole lives with.
In this essay we’ll tackle these questions at the very root. We need good questions to get good answers, so we’ll begin by clarifying the problem. It has to do with probabilities—we’ll see why those natural objects seem so utterly unlikely to happen by chance, and we’ll find the fundamental process that solves the dilemma.
This will take us most of the way, but we’ll have one final obstacle to overcome, a cognitive Last Boss: living things still feel a little magical in some way, imbued with a mysterious substance called “purpose” that feels qualitatively different from how inanimate things work. This kind of confusion runs very deep in our culture. To remove it, I’ll give a name to something that, as far as I know, hasn’t been named before: phenomena that I’ll be calling—enigmatically, for now—“Water Lilies.”…
Applying systems dynamics, complexity, and emergence to understanding reality itself: “Recursion, Tidy Stars, and Water Lilies,” from @marco_giancotti (the second in a trilogy of essays: part one here; subscribe to his newsletter for Part Three when it drops).
* Jorge Luis Borges, “The Zahir“
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As we explore existence, we might spare a thought for Francis Simpson; he died on this date in 2003. An English naturalist, conservationist, and chronicler of the countryside and wild flowers of his native Suffolk, he became a botanist at Ipswich Museum, where he worked until his retirement in 1977.
He published one of the most highly regarded county floras, simply entitled Simpson’s Flora of Suffolk, and in 1938 saved a small meadow, famous for its snakeshead fritillaries, from being drained and ploughed into farmland. Using donations amounting to £75, he was able to purchase the field, Mickfield Meadow, for the Society for the Promotion of Nature Reserves. Today, it is one of the oldest nature reserves in the country, protecting the meadow flowers now surrounded by farmland.
“For every complex problem, there’s a solution that is simple, neat, and wrong”*…
Last year, in explaining the Biden Administration’s emerging new economic policy, National Security Advisor Jake Sullivan talked of a “small yard, high fence” approach to its trade with China. The idea: to place strict restrictions on a small number of technologies with significant military potential while maintaining normal economic exchange in other areas.
The estimable Henry Farrell argues that this approach to technology and China is working poorly (though, he suggests, it will work much worse if Trump wins and takes office in January). Self-reinforcing political feedback loops and self-reinforcing expectations are leading to breakdown.
The fundamental problem of managing geopolitics through manipulating technological trajectories is not readily solvable given existing means, Farrell suggests. We live in a much more complex world than existing state institutions are capable of handling. Therefore, he argues, we need to remake the state…
… Making the right choices in a complex policy environment requires an approach that is a world away from the application of brute force at scale. Your maps of the environment are going to be all wrong when you go in, and brute force is likely to have unexpected consequences. It isn’t just that you are going to make mistakes (you are), but your map of the actual problem you are trying to solve is likely to be utterly out of whack. As you try to catch up with China on EV, you discover that you don’t understand the market right. As you try to impose controls on military use of semiconductors, you find out that you don’t have the information you need to really actually understand how the semiconductor market works.
The problem – as Jen Pahlka’s book Recoding America explains at length – is that addressing such complex problems does not fit well with the way that the U.S. government works. When you are trying to impose order a vast sprawling bureaucracy, which is its own mid-sized global economy, and when your people don’t trust government much, you rely on rigid contracting systems, which define the problem in advance down to its finest details, even if that definition is out of whack with reality. You don’t build connections between the bureaucracy and outside actors, unless they run through cumbersome and rigidly pre-defined channels because it takes months or years to get approval for such connections. And you certainly don’t try to remake policy in realtime as your understanding of the situation changes. Pahlka’s book is cunningly disguised as an account of US software outsourcing practices. If it mentions either ‘national security’ or ‘economic security’ once, I don’t remember it. But it is arguably (along with Dan Davies’ similarly motivated The Unaccountability Machine) the most important book on these topics of the last twenty years. [Your correspondent heartily agrees.]…
… what do you do – is this. You start to think… about how to build economic security institutions that are designed from the ground up to manage complexity. If you want to take ‘small yard, high fence’ seriously as a policy approach, you need to build the apparatus to discover what lies inside, what lies outside, and what the barriers ought be. That apparatus – and its prescriptions – need to change over time both to match a better understanding of the policy environment, and changes in the environment itself.
And we don’t have the apparatus to actually implement small yard, high fence properly. Nor do we have it for pretty well every other plausible economic security policy you might imagine, short of a brute force decoupling of the U.S. and Chinese economies. And if you did that, you would need enormous capacity to manage the horrifically complex aftermath, if that aftermath could even be managed at all.
Clearly, it is far easier to make these arguments in the general than the particular. Saying that you need reforms is straightforward, but figuring out what they ought to be, let alone how to implement them in current political circumstances, is an altogether more difficult challenge. But it is where the debate needs to be going – and there is a role for technology in it. We are in a situation that rhymes in weird ways with the situation discovered by Vannevar Bush after World War II – recognizing that the needs of government had changed, that vastly better information and feedback systems were required to meet those needs, and that even if we didn’t exactly know what those systems were, we needed to start figuring them out, and quickly. That world had its pathologies. This one does too. But to prevent them becoming worse, we need better ways to manage them, and to ensure that the solutions are better than the problems that they are supposed to mitigate.
This is – obviously – a radical set of claims. But it’s one that is entailed by the diagnosis of the problem that I’ve presented. If we need to manage complex challenges – of which the U.S. China relationship is only one – we need a state that is capable of managing complexities. We don’t have one. And that remains a first order problem, regardless of however hawkish or dovish you are…
We need a new kind of state for the new geopolitics: “‘Small Yard, High Fence’: these four words conceal a mess,” from @himself.bsky.social (and @pahlkadot.bsky.social). Eminently worth reading in full.
* H.L. Mencken
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As we ruminate on restructuring, we might recall that it was on this date in 1954 (7 years after the transistor was developed at Bell Labs) that Texas Instruments introduced the Regency TR-1, the first commercially-manufactured transistor radio. Its performance was mediocre, but its small size and portability drove sales of over 150,000 units.
Further to Farrell’s and Pahlka’s points, it’s instructive to ponder what became of the transistor radio as a product category (and of the competitors in it) over the next few decades– and the altogether-unanticipated plethora of small, convenient, hand-held product categories it spawned: calculators, mobile phones, tablets… and whatever comes next…
“The function of economic forecasting is to make astrology look respectable.”*…
For as long as there have been markets, there have been those who forecast them. Bob Seawright explains why, for all of that “practice,” forecasting is never– and never can be– a precise nor “perfect” pursuit…
… On our best days, wearing the right sort of spectacles, squinting and tilting our heads just so, we can be observant, efficient, loyal, assertive truth-tellers. However, on most days, all too much of the time, we’re delusional, lazy, partisan, arrogant confabulators. It’s an unfortunate reality, but reality nonetheless.
But that’s hardly the whole story.
We are our own worst enemy, but there are other enemies, too. Despite our best efforts to make it predicable and manageable, and even if we were great forecasters, the world is too immensely complex, chaotic, and chance-ridden for us to do it well…
Eminently worth reading in full for Seawright’s accounts of human nature, complexity, chaos, and chance– and of the ways in which they make confident predictions of the future a “Fool’s Errand.”
As Niels Bohr once said (paraphrasing a Danish proverb), “it is difficult to make predictions, especially about the future.”
(Image above: source)
* John Kenneth Galbraith
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As we seek clarity, not certainty, we might recall that it was on this date in 1983 that Thomas Dolby’s “She Blinded Me with Science” reached #5 on the Billboard Hot 100 chart.
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