As the philosopher Michael Polanyi famously observed, "We know more than we can tell"
p21 - Siri
- Where is Elvis buried? Responded, "I cant answer that for you." It thought the person's name was Elvis Buried.
- When did the movie Cinderella come out? Responded, with a movie theatre search on Yelp.
- When is the next Halley's Comet? Responded, "You have no meetings matching Halley's."
- I want to go to Lake Superior. Responded with directions to the company Lake Superior X-Ray."
p28, 29 - ASIMO
"As the roboticist Hans Moravec has observed, "It is comparatively easy to make computers exhibit adult-level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility."
The situation has come to be known as Moravec's paradox, nicely summarized by Wikipedia as"the discovery by artificial intelligence and robotics researchers that, contrary to traditional assumptions, high-level reasoning requires very little computation, but low-level sensorimotor skills requires enormous computational resources"
Moravec's insight is broadly accurate, and important. As the cognitive scientist Steven Pinker puts it, "The main lesson of thirty-five years of AI research is that the hard problems are easy and the easy problems are hard...As the new generation of intelligent devices appears, it will be the stock analysts and petrochemical engineers and parole board members who are in danger of being replaced by machines. The gardeners, receptionists, and cooks are secure in their jobs for decades to come.
p 37- The digital progress we've seen recently is certainly impressive, but ti's just a small indication of what's to come. It's the dawn of the second machine age. To understand why it's unfolding now, we need to understand the nature of technological progress in the era of digital hardware, software,, and networks. In particular, we need to understand its three key characteristics: that is exponential, digital and combinatorial.
p42 - The (second) reason that Moore's Law has held up so well for so long is what we might call 'brilliant tinkering' - finding engineering detours around the roadblocks thrown up by physics, When it became difficult to cram integrated circuits more tightly together, for example chip makers instead layered them on top of one another, opening up a great deal of new real estate... As Intel executive Mike Marberry puts it, "If you're only using the same technology, then in principle you run into limits. the truth is we've been modifying the technology every five or seven years for 40 years, and there's no end in sight for being able to do that" This constant modification has made Moore's Law the central phenomenon of the computer age
p62 - Waze (google maps)
Waze exploits two of the well-understood and unique economic properties of digital information: such information is non-rival, and it has close to zero marginal coset of reproduction. In everyday language, we might say that digital information is not "used up" when it gets used, and it is extremely cheap to make another copy of a digitized resources.
p91 - Our digital machines have escaped their narrow confines and started to demonstrate broad abilities in pattern recognition, complex communication, and other domains that used to be exclusively human. (referencing to first paragraph)
p96 - Those of us who believe in the power of recombinant innovation believe that this development will boost human progress. We can't predict exactly what new insights, products, and solutions will arrive in the coming years, but we are fully confident that they'll be impressive. The second machine age will be characterized by countless instances of machine intelligence and billions of interconnected brains working together to better understand and improve our world.
p 107 - The Gross National Product does not include the beauty of our poetry or the intelligence of our public debate. It measures neither our wit nor our courage, neither our wisdom nor our learning, neither our compassion nor our devotion. It measures everything, in short, except that which makes life worthwhile" - Robert F. Kennedy
p115 - Research Erik Brynjolfsson and Joo Hee Oh "The Attention Economy: Measuring the Value of Free Goods on the Internet".
They started with the observation that even when people don't pay with money, they still give up something valuable whenever they use their Internet: their time. No matter how rich or poor we are, each of us gets twenty-four hours in a day. In order to consumer YouTube, Facebook, or e-mail, we must 'pay' attention... (they) estimated that the Internet created about $2600 of value per user each year. None of this showed up in GDP statistics but if it had, GDP growth - and thus productivity growth - would have been about 0.3 percent higher each year.
p138 - Companies with the biggest IT investments typically made the biggest organizational changes, usually with a lag of five to seven years before seeing the full performance benefits. These companies had the biggest increase is the demand for skilled work relative to unskilled work. The lags reflected the time that it takes for managers and workers to figure our new ways to use the technology... Creativity and organizational redesign are crucial to investments in digital technologies.
This means that the best way to use new technologies is usually not to make a literal substitution of a machine for each human worker, but to restructure the process... Compared to simply automating existing tasks, , this kind of organizational coinvention requires more creativity on the part of entrepreneurs, managers, and workers, and for that reason it tends to take time to implement the changes after the initial invention and introduction of new technologies. But once the changes are in place, they generate the lion's share of productivity improvements.
p178- technology replace workers
Eventually, the economy will find a new way equilibrium and full employment will be restored as entrepreneurs invent new businesses and the workforce adapts its human captial
BUT what if this process takes a decade? And what if, by then, technology has changed again?... Once one concedes that it takes time for workers and organizations to adjust to technical change, then it becomes apparent that accelerating technical change can lead to widening gaps and in creating possibilities for technological unemployment. Faster technological progress may ultimately bring greater wealth and longer lifespans, but it also requires fast er adjustments by both people are institutions
p 182- ... machines can have very different strengths and weaknesses than humans, When engineers work to amplify these differences, building on the areas where machines are strong and humans are weak, then the machines are more likely to complement humans rather than substitute for them. Effective productions is more likely to require both human and machine inputs, and the value of the human inputs will grow, not shrink, as the power of machines increases.
A second lesson of economics and business strategy is that it's great to be a complement to something that's increasingly plentiful mMoreover, this approach is more likely to create opportunities to produce goods and services that could never have been created by unaugmented humans, or machines that simply mimicked people, for that matter. These new goods and services provide a path for productivity growth based on increased output rather than reduced inputs.
This in a very real sense, as long as there are unmet needs and wants in the word, unemployment is a loud warning that we simply aren't thinking hard enough about what needs doing. We aren't being creative enough about solving the problems we have using the freed-up time and energy of the people whose old jobs were automated away. We can do more to invent technologies and business models that augment and amplify the unique capabilities of humans to create new sources of value, instead of automating the ones that already exist... this is the real challenge facing our policy makers, our entrepreneurs, and each of us individually.
p 188 - "I have a children in school. How should i be helping them prepare for the future you're describing?" Sometimes the kids are in college, sometimes they're in kindergerten, but the question is the same. And it's not just parents who are concerned about career opportunities in the second machine age. Students themselves, leaders of the organizations that might hire them, educators, polucy makers and elected officials, and many others also wonder which human skills and abilities, if any, will still be valued as technology continues to improve.
Frank Levy and Richard Murnane's excellent book The New Division of Labor was by far the best research and thinking on this topic... arguing that pattern recognition and complex communication were the two broad area where humans would continue to hold the high ground over digital labor... however, this has not always proved to be the case, so as technology races ahead, will it leave a generation behind in all areas, or at least most of them?
The answer is no. (cont)
p189 - Kasparov "the chess master and the computer"
Weak human + machine + better process was superior to a strong computer alone and, more remarkably, superior to a strong human + machine + inferior process
... we see that people still have a great deal to offer the game of chess at its highest levels once they're allowed to race with machines, instead of purely against them.
p 191 - We've never seen a truly creative machine, or an entrepreneurial one, or an innovative one. We've seen software that could create lines of English text that rhymed, but none that could write a true poem ("the spontaneous overflow of powerful feelings, recollected in tranquility" as Wordsworth described it). Programs that can write clean prose are amazing achievement, but we've not yet seen one that can figure out what to write about next. We've also never seen software that could create good software; so far, attempts at this have been abject failures.
These activities have on thing in common: IDEATION, or coming up with new ideas or concepts... good new ideas or concepts, since computers can easily be programmed to generate new combinations of preexisting elements like words. This however, is not recombinant innovation in any meaningful sense. It's close to the digital equivalent of a hypothetical room full of monkeys banging away randomly on typewriters for a billion years and still not reproducing a single play of Shakespeare's.
p195 - Sugata Mitra 2013 TED
"I tried to look at where did the kind of learning we do in schools, where did it come from?.. It came from... the last and the biggest of the empire on this plant, [the British Empire].
What they did was amazing. They created a global computer made of people. It's still with us today. It's called the bureaucratic administrative machine. In order to have that machine running, you need lots and lots of people. They made another machine to product those people: the school. The schools would product the people who would then become parts of the bureaucratic administrative machine... They must know three things: They must have good handwriting, because the data is handwritten; they must be able to read, and they must be able to do multiplication, division, addition and subtraction in their head. They must be so identical that you could pick one up from New Zealand and ship them to Canada and he would be instantly functional.
p201 - Gate has said that he chose to go into software when he saw how cheap and ubiquitous computers, especially microcomputers, were becoming. Jeff Bezos systematically analyzed the bottlenecks and opportunities created by low-cost online commerce, particularly the ability to index large numbers of products, before he sets up Amazon. Today, the cognitive skills of college graduates - including not only science, technology, engineering, and math, the so-called STEM disciplines, but also humanities, arts and social sciences - are often complements to low-cost data and cheap computer power. This helps them command a premium wage.
p213 - But it's also important to recognize that hard-to-measure skills like creativity and unstructured problem solving are increasingly important as machines handle more routine work. MIT's Bengt Holmstrom and Stanford's Paul Milgrom did pioneering work showing that strong incentives for achieving measurable goals can crowd out hard-to measure-goals.
p216 - We favor reducing unnecessary, redundant, and overly burdensome regulation, but recognize that this is likely to be slow and difficult work.
(1) regulators rarely like giving up authority once it's granted to them
(2) those companies and industries protected by existing regulations will no doubt lobby strenuously to preserve their privileged positions
(3) separate sets of regulations exist at the federal, state, and municipal levels in America, so comprehensive change cannot be brought about by any single entity
... so prospective entrepreneurs can likely expect to face a continued patchwork of regulations in many areas. Still, we believe that it is important to try to reduce the regulatory burden and make the business environment as welcoming as possible for entrepreneurs
p 251- Our generation will likely have the good fortune to experience two of the most amazing events in history: the creation of true machine intelligence and the connection of all humans via a common digital network, transforming the planet's economics. Innovators, entrpreneurs, scientists, tinkerers, and many other types of geeks will take advantage of this cornucopia to build technologies that astonish us, delight us, and work for us.
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