Some Context for Thinking About
Technology and Sustainability. A version of my "Towards a Global Brain" talk with a focus on sustainability, given at the Verge conference on the convergence of buildings, transportation, energy, and information, on March 15, 2012.
7. The Google Autonomous Vehicle
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Some of you may have heard last year that Google announced a robotic car that has driven over a hundred thousand miles in ordinary traffic.This is thought provoking on a number of
levels. Let’s talk through a number of them, and the implications for our business.
8. 2005: Seven Miles in Seven Hours
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You see, back in 2005, when a car won the DARPA Grand Challenge, it went seven miles in seven hours.
9. 2011: Hundreds of thousands of miles in ordinary traffic
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10. 1. Artificial Intelligence
“the science and engineering
of making intelligent machines”
-John McCarthy, 1956
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11. But it isn’t just better AI
“We don’t have better algorithms. We just have more data.” - Peter Norvig,
Chief Scientist, Google
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Big data and machine learning really are central. Yet here, only six years later, the Google autonomous vehicle has driven hundreds of thousands of miles in ordinary traffic. What’s
different? Peter Norvig says that the AI isn’t any better. Google just has more data. What kind of data? It turns out that Google had human drivers drive all those streets in cars that
were taking pictures, and taking very precise measurements of distances to everything. The car is actually remembering the route that was driven by human drivers at some previous
time. That “memory”, as recorded by the car’s electronic sensors, is stored in the cloud, and helps guide the car. As Peter pointed out, “picking a traffic light out of the field of view of
a video camera is a hard AI problem. Figuring out if it’s red or green when you already know it’s there is trivial.”
12. 2. Intelligence Augmentation
“The human mind ... operates by association. With one item in its grasp, it snaps
instantly to the next that is suggested by the association of thoughts, in accordance
with some intricate web of trails carried by the cells of the brain. It has other
characteristics, of course; trails that are not frequently followed are prone to fade,
items are not fully permanent, memory is transitory. Yet the speed of action, the
intricacy of trails, the detail of mental pictures, is awe-inspiring beyond all else in
nature.
Man cannot hope fully to duplicate this mental process artificially, but he certainly
ought to be able to learn from it. ... One cannot hope thus to equal the speed and
flexibility with which the mind follows an associative trail, but it should be possible to
beat the mind decisively in regard to the permanence and clarity of the items
resurrected from storage.
Consider a future device for individual use, which is a sort of mechanized private file
and library. It needs a name, and, to coin one at random, "memex" will do.”
– Vannevar Bush, As We May Think, 1945
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17. AI plus the recorded memory of augmented humans
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Big data and machine learning really are central. Yet here, only six years later, the Google autonomous vehicle has driven hundreds of thousands of miles in ordinary traffic. What’s
different? Peter Norvig says that the AI isn’t any better. Google just has more data. What kind of data? It turns out that Google had human drivers drive all those streets in cars that
were taking pictures, and taking very precise measurements of distances to everything. The car is actually remembering the route that was driven by human drivers at some previous
time. That “memory”, as recorded by the car’s electronic sensors, is stored in the cloud, and helps guide the car. As Peter pointed out, “picking a traffic light out of the field of view of
a video camera is a hard AI problem. Figuring out if it’s red or green when you already know it’s there is trivial.”
18. 3. Human-Computer Symbiosis
“The hope is that, in not too many years, human brains and
computing machines will be coupled together very tightly, and
that the resulting partnership will think as no human brain has
ever thought and process data in a way not approached by the
information-handling machines we know today.”
– Licklider, J.C.R., "Man-Computer Symbiosis", IRE Transactions on Human
Factors in Electronics, vol. HFE-1, 4-11, Mar 1960. Eprint
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20. A few key assertions
§ We are building a network-mediated global mind
§ It is not skynet
§ It is us, augmented
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But instead, the global brain is a human-computer symbiosis. The google vehicle is only the latest of a long series of developments that show how we are augmenting ourselves and
connecting ourselves into something bigger. This picture is a routing map of the internet. It’s striking how much it looks like a map of the synapses in a human brain. It’s nowhere
near as dense yet, but the imagery alone is suggestive. But there’s a lot more here than just imagery.
21. “global consciousness is that thing
responsible for deciding that pots
containing decaffeinated coffee should
be orange”
Danny Hillis (via Jeff Bezos)
http://www.oreillynet.com/pub/a/network/2005/03/16/etech_3.html
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22. Friday, July 20, 12
But what’s different now is the way that electronic media speeds up that process. Using twitter, we can instantly learn about trending topics around the world, and share in the
responses of others.
26. “Wikipedia is not an encyclopedia. It
is a virtual city, a city whose main
export to the world is its
encyclopedia articles, but with an
internal life of its own.”
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Michael Nielsen
27. Friday, July 20, 12
Every wikipedia entry has a talk page. Here’s a discussion of why they changed the page to be about the Tohoku earthquake rather than the Sendai earthquake. It turns out that’s how
it’s referred to in Japan.
29. “Would you be willing to cross the street with
information that was five minutes old?”
-Jeff Jonas
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30. “The Wanamaker Problem”
“Half the money I spend on
advertising is wasted; the trouble is I
don't know which half.”
- John Wanamaker (1838-1922)
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That leads me to the whole topic of feedback loops. It isn’t just that this information is going mind to mind. We are increasingly taking this information and creating electronic
feedback loops, which might include humans in different ways. Increasingly, technology is solving what we can call “the Wanamaker problem.”
31. Solving the Wanamaker Problem Beyond Advertising
“Only 1% of healthcare spend now goes to diagnosis. We need to
shift from the idea that you do diagnosis at the start, followed by
treatment, to a cycle of diagnosis, treatment, diagnosis...as we
explore what works.”
-Pascale Witz, GE Medical Diagnostics
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We’re now seeing this same idea spread to other areas of the economy. For example, in healthcare, personalized medicine requires new kinds of diagnostic feedback loops.
32. Friday, July 20, 12
In the city of San Francisco, you’re seeing something similar, where all the parking meters are equipped with sensors, and pricing varies by time of day, and ultimately by demand. I’m
calling these systems of “algorithmic regulation” - they regulate in the same way our body regulates itself, autonomically and unconsciously.
41. The new skills at the heart of the collective intelligence revolution
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This shift requires new competencies of companies. The field has increasingly come to be called “Data Science” - extracting meaning and services from data - and as you can see, the
set of skills that make up this job description are in high demand according to LinkedIn. They are literally going asymptotic.
42. The global brain is us,
connected and augmented
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50. “Access to all the world’s information”
“How can applications be better
when they are social?”
“Changing the world by spreading
the knowledge of innovators”
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51. Data Science Used for Private Gain and Public Harm
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52. How can we make the emerging global consciousness
not only more resilient, but more moral?
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53. We’ve got one world. We’d better get it right.
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