Posts Tagged ‘Steven Johnson’
“O brave new world, that has such people in ‘t!”*…
The estimable Steven Johnson suggests that the creation of Disney’s masterpiece, Snow White, gives us a preview of what may be coming with AI algorithms sophisticated enough to pass for sentient beings…
… You can make the argument that the single most dramatic acceleration point in the history of illusion occurred between the years of 1928 and 1937, the years between the release of Steamboat Willie [here], Disney’s breakthrough sound cartoon introducing Mickey Mouse, and the completion of his masterpiece, Snow White, the first long-form animated film in history [here— actually the first full-length animated feature produced in the U.S; the first produced anywhere in color]. It is hard to think of another stretch where the formal possibilities of an artistic medium expanded in such a dramatic fashion, in such a short amount of time.
[There follows an fascinating history of the Disney Studios technical innovations that made Snow White possible, and an account of the film;’s remarkable premiere…]
In just nine years, Disney and his team had transformed a quaint illusion—the dancing mouse is whistling!—into an expressive form so vivid and realistic that it could bring people to tears. Disney and his team had created the ultimate illusion: fictional characters created by hand, etched onto celluloid, and projected at twenty-four frames per second, that were somehow so believably human that it was almost impossible not to feel empathy for them.
Those weeping spectators at the Snow White premiere signaled a fundamental change in the relationship between human beings and the illusions concocted to amuse them. Complexity theorists have a term for this kind of change in physical systems: phase transitions. Alter one property of a system—lowering the temperature of a cloud of steam, for instance—and for a while the changes are linear: the steam gets steadily cooler. But then, at a certain threshold point, a fundamental shift happens: below 212 degrees Fahrenheit, the gas becomes liquid water. That moment marks the phase transition: not just cooler steam, but something altogether different.
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It is possible—maybe even likely—that a further twist awaits us. When Charles Babbage encountered an automaton of a ballerina as a child in the early 1800s, the “irresistible eyes” of the mechanism convinced him that there was something lifelike in the machine. Those robotic facial expressions would seem laughable to a modern viewer, but animatronics has made a great deal of progress since then. There may well be a comparable threshold in simulated emotion—via robotics or digital animation, or even the text chat of an AI like LaMDA—that makes it near impossible for humans not to form emotional bonds with a simulated being. We knew the dwarfs in Snow White were not real, but we couldn’t keep ourselves from weeping for their lost princess in sympathy with them. Imagine a world populated by machines or digital simulations that fill our lives with comparable illusion, only this time the virtual beings are not following a storyboard sketched out in Disney’s studios, but instead responding to the twists and turns and unmet emotional needs of our own lives. (The brilliant Spike Jonze film Her imagined this scenario using only a voice.) There is likely to be the equivalent of a Turing Test for artificial emotional intelligence: a machine real enough to elicit an emotional attachment. It may well be that the first simulated intelligence to trigger that connection will be some kind of voice-only assistant, a descendant of software like Alexa or Siri—only these assistants will have such fluid conversational skills and growing knowledge of our own individual needs and habits that we will find ourselves compelled to think of them as more than machines, just as we were compelled to think of those first movie stars as more than just flickering lights on a fabric screen. Once we pass that threshold, a bizarre new world may open up, a world where our lives are accompanied by simulated friends…
Are we in for a phase-shift in our understanding of companionship? “Natural Magic,” from @stevenbjohnson, adapted from his book Wonderland: How Play Made The Modern World.
And for a different, but aposite perspective, from the ever-illuminating L. M. Sacasas (@LMSacasas), see “LaMDA, Lemoine, and the Allures of Digital Re-enchantment.”
* Shakespeare, The Tempest
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As we rethink relationships, we might recall that it was on this date in 2007 that the original iPhone was introduced. Generally downplayed by traditional technology pundits after its announcement six months earlier, the iPhone was greeted by long lines of buyers around the country on that first day. Quickly becoming a phenomenon, one million iPhones were sold in only 74 days. Since those early days, the ensuing iPhone models have continued to set sales records and have radically changed not only the smartphone and technology industries, but the world in which they operate as well.
“When the graphs were finished, the relations were obvious at once”*…
We can only understand what we can “see”…
… this long-forgotten, hand-drawn infographic from the 1840s… known as a “life table,” was created by William Farr, a doctor and statistician who, for most of the Victorian era, oversaw the collection of public health statistics in England and Wales… it’s a triptych documenting the death rates by age in three key population groups: metropolitan London, industrial Liverpool, and rural Surrey.
With these visualizations, Farr was making a definitive contribution to an urgent debate from the period: were these new industrial cities causing people to die at a higher rate? In some ways, with hindsight, you can think of this as one of the most crucial questions for the entire world at that moment. The Victorians didn’t realize it at the time, but the globe was about to go from less than five percent of its population living in cities to more than fifty percent in just about a century and a half. If these new cities were going to be killing machines, we probably needed to figure that out.
It’s hard to imagine just how confusing it was to live through the transition to industrial urbanism as it was happening for the first time. Nobody really had a full handle on the magnitude of the shift and its vast unintended consequences. This was particularly true of public health. There was an intuitive feeling that people were dying at higher rates than they had in the countryside, but it was very hard even for the experts to determine the magnitude of the threat. Everyone was living under the spell of anecdote and availability bias. Seeing the situation from the birds-eye view of public health data was almost impossible…
The images Farr created told a terrifying and unequivocal story: density kills. In Surrey, the increase of mortality after birth is a gentle slope upward, a dune rising out of the waterline. The spike in Liverpool, by comparison, looks more like the cliffs of Dover. That steep ascent condensed thousands of individual tragedies into one vivid and scandalous image: in industrial Liverpool, more than half of all children born were dead before their fifteenth birthday.
The mean age of death was just as shocking: the countryfolk were enjoying life expectancies close to fifty, likely making them some of the longest-lived people on the planet in 1840. The national average was forty-one. London was thirty-five. But Liverpool—a city that had undergone staggering explosions in population density, thanks to industrialization—was the true shocker. The average Liverpudlian died at the age of twenty-five, one of the lowest life expectancies ever recorded in that large a human population.
There’s a natural inclination to think about innovation in human health as a procession of material objects: vaccines, antibiotics, pacemakers. But Farr’s life tables are a reminder that new ways of perceiving the problems we face, new ways of seeing the underlying data, are the foundations on which we build those other, more tangible interventions. Today cities reliably see life expectancies higher than rural areas—a development that would have seemed miraculous to William Farr, tabulating the data in the early 1840s. In a real sense, Farr laid the groundwork for that historic reversal: you couldn’t start to tackle the problem of how to make industrial cities safer until you had first determined that the threat was real.
Why the most important health innovations sometimes come from new ways of seeing: “The Obscure Hand-Drawn Infographic That Changed The Way We Think About Cities,” from Steven Johnson (@stevenbjohnson). More in his book, Extra Life, and in episode 3 of the PBS series based on it.
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As we investigate infographics, we might send carefully calculated birthday greetings to Lewis Fry Richardson; he was born on this date in 1881. A mathematician, physicist, and psychologist, he is best remembered for pioneering the modern mathematical techniques of weather forecasting. Richardson’s interest in weather led him to propose a scheme for forecasting using differential equations, the method used today, though when he published Weather Prediction by Numerical Process in 1922, suitably fast computing was unavailable. Indeed, his proof-of-concept– a retrospective “forecast” of the weather on May 20, 1910– took three months to complete by hand. (in fairness, Richardson did the analysis in his free time while serving as an ambulance driver in World War I.) With the advent of modern computing in the 1950’s, his ideas took hold. Still the ENIAC (the first real modern computer) took 24 hours to compute a daily forecast. But as computing got speedier, forecasting became more practical.
Richardson also yoked his forecasting techniques to his pacifist principles, developing a method of “predicting” war. He is considered (with folks like Quincy Wright and Kenneth Boulding) a father of the scientific analysis of conflict.
And Richardson helped lay the foundations for other fields and innovations: his work on coastlines and borders was influential on Mandelbrot’s development of fractal geometry; and his method for the detection of icebergs anticipated the development of sonar.
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