DEATH-DEFYING NERDS
We hear a lot these days about the job threat from automation and robotics. The predicted peril: that there will be millions of unemployed, left stranded financially and socially. The predicted promise: that millions will be freed up to pursue more rewarding careers after a great social transformation.
“At present machinery competes against man. Under proper conditions machinery will serve man,” wrote Oscar Wilde in The Soul of Man Under Socialism (1891):
There is no doubt at all that this is the future of machinery, and just as trees grow while the country gentleman is asleep, so while Humanity will be amusing itself, or enjoying cultivated leisure which, and not labour, is the aim of man — or making beautiful things, or reading beautiful things, or simply contemplating the world with admiration and delight, machinery will be doing all the necessary and unpleasant work.
A century later, Bill Joy, the co-founder and Chief Scientist of Sun Microsystems, penned an influential article for Wired magazine. In Why The Future Doesn’t Need Us, he listed his fears involving engineering, biotechnology, nanotechnology and computing. He feared that one day only the wealthy would have the power to control robots, allowing them the ability to determine how and where the underclass could populate and reproduce.
Joy’s colleagues in computing circles, such as Hans Moravec, George Gilder and the inventor/futurist Ray Kurzweil, had sunnier expectations for Artificial Intelligence, hewing closer to Wilde’s musings.
In 2005, Kurzweil released The Singularity is Here: When Humans Transcend Biology, a popular book which predicted the merger of humans and computational systems. Extrapolating from Moore’s Law (computer processing power doubling approximately every two years), the age-defying thinker believes the singularity will arrive in his lifetime.
“If you go back 500 years, not much happened in a century. Now, a lot happens in six months. Technology feeds on itself and it gets faster and faster,” he notes in the 2009 biopic,“Transcendent Man.” A great fan of life extension practices, the 73 year-old Kurzweil eats well, exercises regularly and pops vitamins like Tic Tacs in the fervent hope he will live long enough to upload his consciousness into the Cloud and still retain his personal identity. The guy’s a big thinker with big ambitions: he plans to survive death.
In the documentary, the inventor muses on the existential event horizon presented by death. “It’s such a profoundly sad, lonely feeling that I really can’t bear it," he confesses. “So I go back to thinking about how I’m not going to die,“ he adds brightly.
Kurzweil seems both single-minded and self-absorbed in his goal of personal immortality. What complicates matters is his relationship with his father, a composer who died at 58 from heart disease. His “genius was thwarted by life,” Kurzweil observes. Old family film strips of the young boy and his doting dad underscore the deep love between them and a loss from which the son never recovered.
The son archived his father’s personal papers, including his musical scores. He compiled recollections from those who knew him. He even recovered DNA from his father’s grave. With all these elements, Kurzweil believes the technology of the post-singularity world will allow the digital resurrection of his beloved father.
He’s serious. Dead serious.
Resurrection may be a tough call, but there’s no denying the exponential growth of computing systems and their capability is putting us on the cusp of a world predicted by either Wilde or Joy. A number of high-profile scientists fear that self-improving AI systems will scale up to a point where not only have they vastly exceeded human intelligence, but even our own ability to understand their ‘thought’ processes or decision paths.
In fact, by 2017 machine learning had reached a stage where the field’s researchers found themselves unable to account for how their algorithms performed across neural nets. Artificial Intelligence succeeds not by thinking like human beings, but reaching the same end point in performance through inscrutable means. (In fact, one of the newer employment opportunities in Silicon Valley involves “teaching” AI to explain their decisions in comprehensible terms. )
One amusing example of this played out when Facebook ran an unintentionally bizarre 2017 experiment with two chatbots tasked to negotiate over trades. Items like hats, balls and books were assigned a certain value, and the chatbots communicated back and forth in human-like ways, including ‘faking’ interest until the deadline for a trade. The bartering bots communicated in English, but the text began to drift ; in essence, they were starting to use the language in a completely idiosyncratic way.
Bob: i can i i everything else . . . . . . . . . . . . . .
Alice: balls have zero to me to me to me to me to me to me to me to me to
Bob: you i everything else . . . . . . . . . . . . . .
Alice: balls have a ball to me to me to me to me to me to me to me
Bob: i i can i i i everything else . . . . . . . . . . . . . .
Alice: balls have a ball to me to me to me to me to me to me to me
Bob: i . . . . . . . . . . . . . . . . . . .
Alice: balls have zero to me to me to me to me to me to me to me to me to
Bob: you i i i i i everything else . . . . . . . . . . . . . .
Alice: balls have 0 to me to me to me to me to me to me to me to me to
Bob: you i i i everything else . . . . . . . . . . . . . .
Alice: balls have zero to me to me to me to me to me to me to me to me to
The strings of repeated words contained an algorithmic meaning the bots had ‘agreed upon,’ without human direction. Given no rule to stick to comprehensible English language , the chatbots became autonomously creative with it.
Alarmist news stories at the time suggested that Facebook researchers pulled the plug after witnessing bots speaking something weirder than Vulcan, but the internal story was more mundane: the experiment was concluded as unsuccessful. That said, computer scientists appear to be on the brink of encountering rather alien forms of intelligence, entirely of their own making.
BRANDS WITH BRAINS
Former Wired magazine editor Kevin Kelly put a question in 2000 to Google co-founder Larry Page. Why, with so many web search companies out there, were Page and colleague Sergey Brin getting into the game by offering search for free? "Oh, we’re really making an AI,” Page responded.
"Rather than use AI to make its search better, Google is using search to make its AI better,” Kelly explained. In other words, each query instructs the company’s networked machine intelligence to sharpen its inventory of concepts. For example, image searches for “dog” teaches the AI to refine its visual recognition of the word, independent of the breed, angle of view or lighting.
“Our AI future is likely to be ruled by an oligarchy of two or three large, general-purpose cloud-based commercial intelligences,” Kelly wrote in his Panglossian 2017 book, The Inevitable: Understanding the 12 Technological Forces That Will Shape Our Future. Brands with brains, in other words. Monopolies with minds.
Deep learning — the capacity of computing systems to algorithmically improve their own accuracy, processing, and general intelligence — is penetrating areas once believed outside the domain of robots. In 2016, the Alphabet-owned DeepMind Technologies achieved a new benchmark with a computer that beat out the reigning human Go player. A year later, their AlphaGoZero climbed to new heights by playing 4.9 million games against itself in quick succession. Within three days, it had far exceeded any human capacity to touch it in competition. In fact, it has since come up with original opening moves that professional human Go players had never seen before, which they’ve actually learned from.
In 2019, a former Go champion retired from professional play after declaring AI invincible. “Even if I become the number one, there is an entity that cannot be defeated,” said Lee Se-dol, who was defeated by DeepMind’s AlphaGo in 2016.
None of this high-level gamesmanship is likely to trouble the average Joe or Jane all that much. It’s another matter when it’s blue collar and white collar jobs threatened with extinction through automation. To cite just one example, in 40 of the 50 U.S. states the most common occupation is “truck driver.” That entire area of employment is set to be eliminated by driverless vehicles — and that’s a pre-COVID estimate. By some estimates, approximately half of all current jobs, both blue-collar and white collar, will be rendered redundant by automation.
After a messy period of capitalistic “creative destruction,” will full employment will be necessary or even missed if machines can attend to all our needs? Whose future seems more likely at this stage, Oscar Wilde’s or Bill Joy’s? More in Part 3.
The next Carrington event will send us back to a very dark age. Imagine, a world with no electricity, hence no electronics.
Sure, we'll tool up again, since some of the larger transformers are protected now, but it'll still take a while. In the meantime, just try to buy anything or get the bank to open its doors so you can get some cash out of your account ... or safety deposit box, for that matter.
Why do we live like electricity is a given and will go on forever?
That said ? At which day was that the end of ? Going forward and all that haha ( that said: 0 )