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    Society & Culture

    Long Now

    The Long Now Foundation is a non-profit dedicated to fostering long-term thinking and responsibility. Explore hundreds of lectures and conversations from scientists, historians, artists, entrepreneurs, and more through The Long Now Foundation’s award-winning Long Now Talks, started in 02003 by Long Now co-founder Stewart Brand (creator of the Whole Earth Catalog). Past speakers include Brian Eno, Neal Stephenson, Jenny Odell, Daniel Kahneman, Suzanne Simard, Jennifer Pahlka, Kim Stanley Robinson, and many more. Watch video of these talks at https://longnow.org/talks

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    Latest Episodes:
    Jonathan Rose: The Well Tempered City Sep 20, 2016
    Show notes

    ### Coherent cities What holds a city together? Rose noted that the earliest cities were built around a temple and the spirituality it embodied. As the early communities became larger and more diverse and complex, their economic activity intensified. To be effective in trade they had to specialize, monetizing their regional opportunities. One city became known for shipping, another for serving caravans. One as a source of metal, another as a source of grain. To cope with their growing complexity the cities had to develop varying control systems for everything—irrigation, food storage, accounting, building codes. The Code of Hammurabi was written in 1754 BCE explicitly “to further the well-being of mankind.” (One of its building-code provisions declared, “If your building falls down and kills somebody, we kill you.”) Modern cities need to create their own “circular economy,” Rose stressed, not just of services and goods, but of greener waste treatment, of water recycling, of food creation (such as“vertical gardens”,) and especially of what he called "communities of opportunity”—where low-income groups such as immigrants get a chance to create prosperity for themselves and the city. In his own many real-estate projects, Rose focusses on increasing urban density with low-income housing in combination with improved mass transit, local parks, better schools, and the greenest of building standards. But for such innovations to be copied, he pointed out, they have to be profitable. Cities are systems, Rose concluded: “When a system is optimized, then all of its components do well. Cities that focus on the optimization of the whole for everybody are the ones that thrive the best.”


    Seth Lloyd: Quantum Computer Reality Aug 09, 2016
    Show notes

    ### Quantum Computer Reality The 15th-century Renaissance was triggered, Lloyd began, by a flood of new information which changed how people thought about everything, and the same thing is happening now. All of us have had to shift, just in the last couple decades, from hungry hunters and gatherers of information to overwhelmed information filter-feeders. Information is physical. A bit can be represented by an electron _here_ to signify 0, and _there_ to signify 1. Information processing is moving electrons from here to there. But for a “qubit" in a quantum computer, an electron is both _here_ and _there_ at the same time, thanks to "wave-particle duality.” Thus with “quantum parallelism” you can do massively more computation than in classical computers. It’s like the difference between the simple notes of plainsong and all that a symphony can do—a huge multitude of instruments interacting simultaneously, playing arrays of sharps and flats and complex chords. Quantum computers can solve important problems like enormous equations and factoring--cracking formerly uncrackable public-key cryptography, the basis of all online commerce. With their ability to do “oodles of things at once," quantum computers can also simulate the behavior of larger quantum systems, opening new frontiers of science, as Richard Feynman pointed out in the 1980s. Simple quantum computers have been built since 1995, by Lloyd and ever more others. Mechanisms tried so far include: electrons within electric fields; nuclear spin (clockwise and counter); atoms in ground state and excited state simultaneously; photons polarized both horizontally and vertically; and super-conducting loops going clockwise and counter-clockwise at the same time; and many more. To get the qubits to perform operations—to compute—you can use an optical lattice or atoms in whole molecules or integrated circuits, and more to come. The more qubits, the more interesting the computation. Starting with 2 qubits back in 1996, some systems are now up to several dozen qubits. Over the next 5-10 years we should go from 50 qubits to 5,000 qubits, first in special-purpose systems but eventually in general-purpose computers. Lloyd added, “And there’s also the fascinating field of using funky quantum effects such as coherence and entanglement to make much more accurate sensors, imagers, and detectors.” Like, a hundred thousand to a million times more accurate. GPS could locate things to the nearest micron instead of the nearest meter. Even with small quantum computers we will be able to expand the capability of machine learning by sifting vast collections of data to detect patterns and move on from supervised-learning (“That squiggle is a 7”) toward unsupervised-learning—systems that learn to learn. The universe is a quantum computer, Lloyd concluded. Biological life is all about extracting meaningful information from a sea of bits. For instance, photosynthesis uses quantum mechanics in a very sophisticated way to increase its efficiency. Human life is expanding on what life has always been—an exercise in machine learning.


    Kevin Kelly: The Next 30 Digital Years Jul 14, 2016
    Show notes

    ## Digital is just getting started In Kevin Kelly’s view, a dozen “inevitable” trends will drive the next 30 years of digital progress. Artificial smartnesses, for example, will be added to everything, all quite different from human intelligence and from each other. We will tap into them like we do into electricity to become cyber-centaurs -- co-dependent humans and AIs. All of us will need to perpetually upgrade just to stay in the game. Every possible display surface will become a display, and study its watchers. Everything we encounter, “if it cannot interact, it is broken.” Virtual and augmented reality (VR and AR) will become the next platform after smartphones, conveying a profound sense of experience (and shared experience), transforming education (“it burns different circuits in your brain”), and making us intimately trackable. “Everything that can be tracked will be tracked,” and people will go along with it because “vanity trumps privacy,” as already proved on Facebook. “Wherever attention flows, money will follow.” Access replaces ownership for suppliers as well as consumers. Uber owns no cars; AirBnB owns no real estate. On-demand rules. Sharing rules. Unbundling rules. Makers multiply. “In thirty years the city will look like it does now. We will have rearranged the flows, not the atoms. We will have a different idea of what a city is, and who we are, and how we relate to other people.” In the Q&A;, Kelly was asked what worried him. “Cyberwar,” he said. “We have no rules. Is it okay to take out an adversary’s banking system? Disasters may have to occur before we get rules. We’re at the point that any other civilization in the galaxy would have a world government. I have no idea how to do that.” Kelly concluded: “We are at the beginning of the beginning—the first hour of day one. There have never been more opportunities. The greatest products of the next 25 years have not been invented yet.” “You are not late.”


    Brian Christian: Algorithms to Live By Jun 20, 2016
    Show notes

    ### Solving hard decisions Deciding when to stop your quest for the ideal apartment, or ideal spouse, depends entirely on how long you expect to be looking, says Brian Christian. The first one you check will be the best you’ve seen, but it’s unlikely to be the best you’ll ever see. So you keep looking and keep finding new bests, though ever less frequently, and you start to wonder if maybe you refused the very best you’ll ever find. And the search is wearing you down. When should you take the leap and look no further? The answer from computer science is precise: 37% of the way through your search period. If you’re spending a month looking for an apartment, you should calibrate (and be sorely tempted) for 11 days, and then you should grab the next best-of-all you find. Likewise with the search for a mate. If you’re looking from, say, age 18 to 40, the time to shift from browsing and having fun to getting serious and proposing is at age 26.1. (However, if you’re getting lots of refusals, “propose early and often” from age 23.5. Or, if you can always go back to an earlier prospect, you could carry on exploring to age 34.4.) This “Optimal Stopping” is one of twelve subjects examined in Christian’s (and co-author Tom Griffiths’) book, _Algorithms to Live By_. (The other subjects are: Explore/Exploit; Sorting; Caching; Scheduling; Bayes’ Rule; Overfitting; Relaxation; Randomness; Networking; Game Theory; and Computational Kindness. An instance of Bayes’ Rule, called the Copernican Principle, lets you predict how long something of unknown lifespan will last into the future by assuming you’re looking at the middle of its duration—hence the USA, now 241 years old, might be expected to last through 2257.) Christian went into detail on the Explore/Exploit problem. Optimism minimizes regret. You’ve found some restaurants you really like. How often should you exploit that knowledge for a guaranteed good meal, and how often should you optimistically take a chance and explore new places to eat? The answer, again, depends partly on the interval of time involved. When you’re new in town, explore like mad. If you’re about to leave a city, stick with the known favorites. Infants with 80 years ahead are pure exploration— they try tasting everything. Old people, drawing on 70 years of experience, have every reason to pare the friends they want to spend time with down to a favored few. The joy of the young is discovering. The joy of the old is relishing.


    Walter Mischel: The Marshmallow Test: Mastering Self-Control May 02, 2016
    Show notes

    ### Thinking hot and cool **In the 1960s, Mischel** and colleagues at Stanford launched a series of delayed-gratification experiments with young children using a method that later came to be known as “the marshmallow test.” A researcher whom the child knew and trusted, after playing some fun games together, suggested playing a “waiting game.” The researcher explained that the child could have either one or two of the highly attractive treats the child had chosen and was facing (marshmallows, cookies, pretzels)--depending on how long the child waited for them after the researcher left the room. The game was: at any time the child could ring a bell, and the researcher would come back immediately and the child could have _one_ treat. To practice, the researcher left the room, the child rang the bell and the researcher came right back, saying, “You see, you brought me back. Now if you wait for me to come back by myself without ringing the bell or starting to eat a treat you can have _both_ of them!!” The wait might be as long as 15 or 20 minutes. (About one third made it that far.) The kids varied widely in how long they could stand it before ringing the bell. Mischel emphasizes that the focus of the research was to identify the specific cognitive strategies and mental mechanisms, as well as the developmental changes, that make delay of gratification possible--not to “test” or pigeonhole children. Between the ages of 4 and 6 years, for example, the older kids could delay their gratification longer, apparently as the impulse-overriding “executive function” of their maturing brains kicked in. And in some conditions it was easy for the children to wait, while under other conditions it was very difficult. The research sought to identify the cognitive skills that underlie willpower and long-term thinking and how they can be enhanced. Longitudinal studies of the tested children suggested that something profound was going on. By the time they were adolescents, the kids who had been able to hold out longer for the bigger reward in some conditions were also likelier to have higher SAT scores, to function better socially, and to manage temptation and stress better. On into their adulthood, they were less likely to show extreme aggression, less likely to over-react if they became anxious about social rejection, and less likely to become obese. For the kids who did not hold out well and took the quick reward, Mischel said the findings suggested that “the inability to delay gratification can have quite serious potential negative effects.” (Mischel cautions that the longitudinal results are only correlations that describe group findings and do not allow accurate predictions for individual children.) Can “delay ability” be trained? Mischel thinks it can, if we understand how our mind works. He and colleagues postulated a “Hot System” and a “Cool System” in the brain. (They are similar to Daniel Kahneman’s “System 1” and “System 2” in his book _Thinking Fast and Slow_.) The Hot System (Go!) is: emotional, simple, reflexive, fast, and centered in the amygdala. It develops early in the child and is exacerbated by stress. The Cool System (Know), on the other hand, is: cognitive rather than emotional, complex, reflective, slow, and centered in the frontal lobes and hippocampus. It develops later in the child and is made weaker by stress. In the Hot System the stimulus controls us; in the Cool System we control the stimulus. You can chill a hot object of desire by representing it to yourself in Cool, abstract terms. Don’t think of the marshmallow as _yummy and chewy_ ; imagine it as _round and white_ like a cotton ball. One little girl became patient by pretending she was looking at a picture of a marshmallow and “put a frame around it” in her head. “You can’t eat a picture,” she explained. (Girls were better handling temptation than boys.) While coolly defusing a temptation, you can also make Hot the delayed consequences of yielding to it. Mischel was a three-pack-a-day smoker ignoring all warnings about cancer until one day he saw a man on a gurney in Stanford Hospital. “His head was shaved, with little green X’s, and his chest was bare, with little green X’s.” A nurse told him the X’s were for where the radiation would be targeted. “I couldn’t shake the image. It made hot the delayed consequences of my smoking.” Mischel kept that image alive in his mind while reframing his cigarettes as sources of poison instead of relief, and he quit. “If you don’t know how to delay gratification,” he said, “you don’t have a choice. If you do know how, you have a choice.”


    Priyamvada Natarajan: Solving Dark Matter and Dark Energy Apr 11, 2016
    Show notes

    ## The darkness of dark matter and dark energy ALL THAT WE KNOW of the universe we get from observing photons, Natarajan pointed out. But dark matter, which makes up 90 percent of the total mass in the universe, is called dark because it neither emits nor reflects photons — and because of our ignorance of what it is. It is conjectured to be made up of still-unidentified exotic _collisionless_ particles which might weigh about six times more than an electron. Though some challenge whether dark matter even exists, Natarajan is persuaded that it does because of her research on “the heaviest objects in the universe“ — galaxy clusters of more than 1,000 galaxies. First of all, the rotation of stars within galaxies does not look Keplerian — the outermost stars move far too quickly, as discovered in the 1970s. Their rapid rate of motion only makes sense if there is a vast “halo” of dark matter enclosing each galaxy. And galaxy clusters have so much mass (90 percent of it dark) that their gravitation bends light, “lenses” it. A galaxy perfectly aligned on the far side of a galaxy cluster appears to us — via the Hubble Space Telescope — as a set of multiple arc-shaped (distorted) galaxy images. Studying the precise geometry of those images can reveal some of the nature of dark matter, such as that it appears to be “clumpy.” With the next generation of space telescopes — the James Webb Space Telescope that comes online in 2018 and the Wide-Field Infrared Survey Telescope a few years afterward — much more will be learned. There are also instruments on Earth trying to detect dark-matter particles directly, so far without success. As for dark energy — the _accelerating_ expansion of the universe — its shocking discovery came from two independent teams in 1998–99. Dark energy is now understood to constitute 72 percent of the entire contents of the universe. (Of the remainder, dark matter is 23 percent, and atoms — the part that we know — makes up just 4.6 percent.) When the universe was 380,000 years old (13.7 billion years ago), there was no dark energy. But now “the universe is expanding at a pretty fast clip.” Natarajan hopes to use galaxy-cluster lensing as a tool “to trace the geometry of space-time which encodes dark energy.” These days, she said, data is coming in from the universe faster than theory can keep up with it.” We are in a golden age of cosmology.”


    Jane Langdale: Radical Ag: C4 Rice and Beyond Mar 14, 2016
    Show notes

    ## Revolutionary rice Feeding the world (and saving nature) in this populous century, Jane Langdale began, depends entirely on agricultural efficiency—the ability to turn a given amount of land and sunlight into ever more food. And that depends on three forms of efficiency in each crop plant: 1) interception efficiency (collecting sunlight); 2) conversion efficiency (turning sunlight into sugars and starch); and 3) partitioning efficiency (maximizing the edible part). Of these, after centuries of plant breeding, only conversion efficiency is far short of the theoretical maximum. Most photosynthesis (called “C3“) is low-grade, poisoning its own process by reacting with oxygen instead of carbon dioxide when environmental conditions are hot and dry. But some plants, such as corn and sugar cane, have a brilliant workaround. They separate the photosynthetic process into two adjoining cells. The outer cell creates a special four-carbon compound (hence “C4“) that is delivered to the oxygen-protected inner cell. In the inner cell, carbon dioxide is released from the C4 compound, enabling drastically more efficient photosynthesis to take place because carbon dioxide is at a much higher concentration than oxygen. Rice is a C3 plant--which happens to be the staple food for half the world. If it can be converted to C4 photosynthesis, its yield would increase by _50%_ while using _half_ the water. It would also be drought-resistant and need far less fertilizer. Langdale noted that C4 plants have evolved naturally 60 times in a variety of plant families, all of which provide models of the transition. “How difficult could it be?” she deadpanned. The engineering begins with reverse-engineering. For instance, the main leaves in corn are C4, but the husk leaves are C3-like, so the genes that affect the two forms of development can be studied. Langdale’s research suggests that the needed structural change in rice can be managed with about 12 engineered genes, and previous research by others indicates that the biochemical changes can be achieved with perhaps 10 genes. How much is needed for the eventual fine tuning will emerge later. When is later? The C4 Rice project began in 2006 at the International Rice Research Institute in the Philippines, funded by the Bill & Melinda Gates Foundation. The research is on schedule, and engineering should begin in 2019, with the expectation that breeding of delicious, fiercely efficient C4 rice could be complete by 2039. It is the kind of thing that highly focussed multi-generation science can accomplish.


    Stephen Pyne: Fire Slow, Fire Fast, Fire Deep Feb 09, 2016
    Show notes

    ### Ecological wildfire “We are uniquely fire creatures,” Pyne began, “on a uniquely fire planet.” Life itself is a form of slow metabolic combustion—which eventually created oxygen and burnable vegetation that allowed fast combustion, ignited by lightning. Humans came along and mastered fire for warmth, food preparation, and managing the landscape, and that made us a keystone species. Humanity’s ecological signature on the world is fire. Then we made fire the all-purpose catalyst for craft (clay, glass, metal) and eventually industry, shifting to the vast geological resource of fossil fuels. That “pyric transition” made humans dominant on the earth, even to the point of affecting climate. We used fire to clear much of the world’s forest for agriculture. Then came a century of misdirection about wildfire. The forests of Europe are mostly too wet to burn, but by the late 19th century the leading foresters in world came from there and taught their ignorance to foresters in North America and India, where the land depends on seasonal fire for ecological health. National governments set about suppressing all wildfire, with catastrophic success. In the absence of the usual occasional local fires, massive fuel loads built up, and destructive megafires became the norm. There was an alternative theory of a “restoration strategy” to manage wildfire in way that would emulate how lightning and native American burning kept the landscape ecologically healthy, but it has been applied haltingly and fractionally, and megafires still rule. “The real argument for fire is that it does ecological work that nothing else does,” Pyne concluded. “Charismatic megaflora” like redwoods need fire. An ecologically rich mosaic of forest, savannah, and meadows needs fire. Healthy prairie needs fire or it gets taken over by invasive woody plants. People trained only as foresters are blind to all that. Wildfire practice now works best when it is guided by wildlife biologists who insist that red cockaded woodpeckers need fire-dependent longleaf pines, that grizzly bears need the berries that grow in recent burns, that pheasants need grassland burned free of invasive eastern red cedar. The techniques for prescribed burns for a bioabundant natural landscape are now well honed. They need to be applied much more widely. When in doubt how to proceed, ask the ecologists, who will ask the animals.


    Eric Cline: 1177 B.C.: When Civilization Collapsed Jan 11, 2016
    Show notes

    ### When chaos overwhelmed civilization Archaeologist Cline began by declaring that the time he would most like to be transported to is the Late Bronze Age in the Mediterranean—the five centuries between 1700 and 1200 B.C. In those centuries eight advanced societies were densely connected—Egyptians, Assyrians, Babylonians, Canaanites, Hittites, Cypriots, Minoans, and Mycenaeans. They grew to power over two millennia, but they collapsed simultaneously almost overnight. What happened? The density of their connection can be learned from trade goods found in shipwrecks, from Egyptian hieroglyphs and wall paintings, and from countless well-preserved clay-tablet letters written between the states. The tin required for all that bronze (tin was the equivalent of oil today) came from Afghanistan 1,800 miles to the east. It was one of history’s most globalized times. In the 12th Century B.C. everything fell apart. For Cline the defining moment was the battle in 1177 B.C. (8th Year of Ramses III) when Egypt barely defeated a mysterious army of “Sea Peoples.” Who were they? Do they really explain the general collapse, as historians long assumed? Cline thinks the failure was systemic, made of a series of cascading calamities in a highly interdependent world. There were indeed invasions—they might have been soldiers, or refugees, or civil war, or all three. But the violence was probably set in motion by extensive drought and famine reported in tablet letters from the time. Voices in the letters: “There is famine in our house. We will all die of hunger.” “Our city is sacked. May you know it!” In some regions there were also devastating earthquakes. The interlinked collapses played out over a century as central administrations failed, elites disappeared, economies collapsed, and whole populations died back or moved elsewhere. In the dark centuries that followed the end of the Bronze Age, romantic myths grew of how wondrous the world had once been. Homer sang of Achilles, Troy, and Odysseus. Those myths inspired the Classical Age that eventually emerged. Cline wonders, could the equivalent of the Bronze Age collapse happen in our current Age?


    Philip Tetlock: Superforecasting Nov 23, 2015
    Show notes

    ### All it takes to improve forecasting is KEEP SCORE Will Syria’s President Assad still be in power at the end of next year? Will Russia and China hold joint naval exercises in the Mediterranean in the next six months? Will the Oil Volatility Index fall below 25 in 2016? Will the Arctic sea ice mass be lower next summer than it was last summer? Five hundred such questions of geopolitical import were posed in tournament mode to thousands of amateur forecasters by IARPA—the Intelligence Advanced Research Projects Activity--between 2011 and 2015. (Tetlock mentioned that senior US intelligence officials opposed the project, but younger-generation staff were able to push it through.) Extremely careful score was kept, and before long the most adept amateur “superforecasters” were doing 30 percent better than professional intelligence officers with access to classified information. They were also better than prediction markets and drastically better than famous pundits and politicians, who Tetlock described as engaging in deliberately vague “ideological kabuki dance." What made the amateurs so powerful was Tetlock’s insistence that they score geopolitical predictions the way meteorologists score weather predictions and then learn how to improve their scores accordingly. Meteorologists predict in percentages—“there is a 70 percent chance of rain on Thursday.” It takes time and statistics to find out how good a particular meteorologist is. If 7 out of 10 such times it in fact rained, the meteorologist gets a high score for calibration (the right percentage) and for resolution (it mostly did rain). Superforecasters, remarkably, assigned probability estimates of 72-76 percent to things that happened and 24-28 percent to things that didn’t. How did they do that? They learned, Tetlock said, to avoid falling for the “gambler’s fallacy”—detecting nonexistent patterns. They learned objectivity—the aggressive open-mindedness it takes to set aside personal theories of public events. They learned to not overcompensate for previous mistakes—the way American intelligence professionals overcompensated for the false negative of 9/11 with the false positive of mass weapons in Saddam’s Iraq. They learned to analyze from the outside in—Assad is a dictator; most dictators stay in office a very long time; consider any current news out of Syria in that light. And they learned to balance between over-adjustment to new evidence (“This changes everything”) and under-adjustment (“This is just a blip”), and between overconfidence ("100 percent!”) and over-timidity (“Um, 50 percent”). “You only win a forecasting tournament,” Tetlock said, “by being decisive—justifiably decisive." Much of the best forecasting came from teams that learned to collaborate adroitly. Diversity on the teams helped. One important trick was to give extra weight to the best individual forecasters. Another was to “extremize” to compensate for the conservatism of aggregate forecasts—if everyone says the chances are around 66 percent, then the real chances are probably higher. In the Q & A following his talk Tetlock was asked if the US intelligence community would incorporate the lessons of its forecasting tournament. He said he is cautiously optimistic. Pressed for a number, he declared, “Ten years from now I would offer the probability of .7 that there will be ten times more numerical probability estimates in national intelligence estimates than there were in 2005.” Asked about long-term forecasting, he replied, “Here’s my long-term prediction for Long Now. When the Long Now audience of 2515 looks back on the audience of 2015, their level of contempt for how we go about judging political debate will be roughly comparable to the level of contempt we have for the 1692 Salem witch trials."


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