This document discusses the convergence of computing and human potential that is leading towards a global brain. It provides examples like the Google autonomous vehicle, which relies on data from human drivers, and Wikipedia, which is the product of collective human intelligence and cooperation. The emerging global brain consists of humans connected and augmented by technology, working together to solve problems at a massive new scale.

1. Towards a Global Brain:
Man-machine symbiosis, cooperation,
and the future of society
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2. “The skill of writing is to
create a context in which
other people can think.”
-Edwin Schlossberg
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Often, the shape of the emerging world is right in front of our faces, but we can’t see it because we aren’t framing it in the
right way.

3. The extraordinary convergence
of computing and human potential
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What I want to give you now is some context for thinking about the extraordinary convergence
of computing and human potential

4. Towards a global brain
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That is leading us towards what we might truly call a global brain.

5. The Google Autonomous Vehicle
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I’m going to start in what might be an unexpected place, with the Google autonomous vehicle. This car is thought-provoking on
a number of levels.

6. 2005: Seven Miles in Seven Hours
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You see, back in 2005, when a car named Stanley won the DARPA Grand Challenge, it went seven miles in seven hours.

7. 2011: Hundreds of thousands of miles in ordinary traffic
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Yet only six years later, Google announced a robotic car that has driven over a hundred thousand miles in ordinary traffic.

8. Artificial Intelligence?
“the science and engineering
of making intelligent machines”
-John McCarthy, 1956
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Was this a triumph of artificial intelligence, like IBM’s Watson beating human Jeopardy champions?

9. “We don’t have better algorithms. We just have more
data.” - Peter Norvig, Chief Scientist, Google
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It was surely that. But there’s another important factor that is easy to overlook. Google’s chief scientist, Peter Norvig, says that
the algorithms aren’t any better. Google just has more data. What kind of data?

10. AI plus the recorded memory of augmented humans
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It turns out that the autonomous vehicle is made possible by Google Streetview. Google had human drivers drive all those streets
in cars that were taking pictures, and making very precise measurements of distances to everything. The autonomous vehicle 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 to me, “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.”

11. Man-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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The Google Autonomous Vehicle is thus an example of what JCR Licklider, the legendary DARPA program manager who funded
the original development of TCP/IP was writing about in his 1960 paper entitled Man-Computer Symbiosis. He wrote:

12. Harnessing Collective Intelligence
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So, in a surprising way, the Google Autonomous Vehicle is another unexpected example of the trend that I’ve referred to as
Harnessing Collective Intelligence. It’s another miracle of computer-mediated human cooperation!. This is a thread that runs
through all the great inventions of the web, from Google itself, Wikipedia, social platforms like Twitter and Facebook are all
technologies for harvesting and coordinating the products of thousands or even millions of minds, increasingly in close to real-
time.

13. A few key assertions
§ We are building a network-mediated global mind
§ It is not the “skynet” of the Terminator movies
§ It is us, augmented
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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. We are building a network-mediated global mind. It is not the “skynet” of the
Terminator movies. It is us, augmented
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 is suggestive. But there’s a lot more here than just imagery. The global brain is a
human-computer symbiosis.

14. “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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Let me come at this idea from another angle.
At our Emerging Technology Conference in 2005, Amazon CEO Jeff Bezos recounted a conversation he’d had with computer
scientist Danny Hillis, in which Danny said [quote above]. Now this is nothing new. Speech, the written word, printed books and
newspapers, the telephone, radio and television are all technologies for passing knowledge from mind to mind.

15. 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.

16. We are all Khaled Said
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This new real time mind-sharing capability can be used to organize large numbers of people for political purposes, as we saw in
the recent uprisings in the Middle East.

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Technology-enabled cooperation can be very simple, as with a wiki. Here’s for example, is the initial wikipedia page for the
great earthquake that hit Japan last year.

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Within a short time, through thousands of edits by thousands of interested individuals, it turned into a full-featured
encyclopedic account of the earthquake and its aftermath. Let’s watch that in action.

19. “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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What’s important to realize is the human element in these applications. A community of hundreds of million humans linking to
documents makes Google possible. At its deepest level, the web is social. It’s not just overtly social applications like Facebook,
Twitter, and Google+.
Michael Nielsen has written a wonderful book about how collective intelligence can be applied to problems of science. He takes
lessons from the consumer internet and applies them to much more challenging intellectual activities. He emphasizes, in his
discussion of Wikipedia, that it is not just a collection of documents, but the product of a community. He says [quote above]

20. “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 advertisers call “the Wanamaker problem” after 19th century department store magnate John
Wanamaker, who said [quote above] What Google did with pay-per-click advertising was to solve the Wanamaker problem, by
building a business model that only charged advertisers when consumers clicked on their ads, and harnessing collective
intelligence to predict which of those ads would be most likely be clicked on.

21. Friday, July 20, 12
We’re now seeing this same idea spread to other areas of the economy. For example, these kinds of feedback loops enabled by
data are part of what the US government is trying to do in healthcare with Accountable Care Organizations.

22. “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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Personalized medicine requires new kinds of diagnostic feedback loops. Pascale Witz of GE Medical Diagnostics explained how

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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. All of the technology “smart city” initiatives need to
be seen as ways of instrumenting not just the physical city but the social life of the humans who live in it.

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The idea of the social life of the city as captured by technology becomes clear in this visualization done by Wired Magazine of 24
hours of 311 calls from the city of New York, showing what issues citizens are contacting their government about. This same
kind of ebb and flow comes increasingly from the data exhaust from our devices.

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This shift requires new competencies of companies and governments. 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.

26. 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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I want to turn to another aspect of man-machine symbiosis, this time in terms of information retrieval. In 1945, Vannevar Bush
wrote a famous and influential article called “As We May Think” that in many ways prefigured the ideas of the World Wide Web.

27. A device that knows
where I am better than I
do, a knowing assistant
telling me where to go
and how to get there.
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The current state of the art of this kind of near-miraculous information retrieval can be seen in today’s smartphones. For
example, a smartphone equipped with mapping software knows exactly where you are. But note that the information being
retrieved is generated by human beings, often through collective activity.

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Returning to IBM’s Watson, we see that it too is a product of man-machine symbiosis. After all, the documents that it “reads” to
perform its feats of apparent intelligence are human documents. In the three seconds it has to come up with a Jeopardy
question, it has time to read and process the equivalent of 200 million pages. And now that speed of information retrieval is
being used for more than parlor tricks, as IBM works to train Watson to act as an assistant in healthcare. The average physician
is able to read the latest research in his field perhaps five hours a week; Watson’s ability to read everything and suggest
potentially relevant answers makes it an ideal assistant. “Watson makes suggestions, not decisions,” says IBM’s Dr. Randy Kohn.

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This is the real opportunity for new information retrieval UIs like Google’s Project Glass - in specialized settings where access to
a computer can be seen as a powerful kind of human augmentation. I expect it to be used in professional settings before it
becomes popular as a consumer device. (In social settings, it will require even more profound resets of behavior than the
“always-on” mobile phone.)

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You can see a preview of where this is taking us in the Apple Store. Where most stores (at least in America) have used
technology to eliminate salespeople, Apple has used it to augment them. Each store is flooded with smartphone-wielding
salespeople who are able to help customers with everything from technical questions to purchase and checkout. Walgreens is
experimenting with a similar approach in the pharmacy, and US CTO Todd Park foresees a future in which health workers will be
part of a feedback loop including sensors to track patient data coupled with systems that alert them when a patient needs to be
checked up on. The augmented home health worker will allow relatively unskilled workers to be empowered with the much
deeper knowledge held in the cloud.

31. The global brain is us,
connected and augmented
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This global brain is doing more than letting us spread news and gossip more quickly.

32. § patientslikeme and collaborative clinical trials
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patientslikeme allows patients to share their symptoms and solutions, and are starting to provide a basis for crowdsourced
clinical trials of new treatments.

33. § Jen’s TED talk, possums
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Or consider the point Jen Pahlka made in her recent TED talk about government services. When we use crowdsourced services
like xxx, which let neighbors help each other rather than calling a city call center for help, we not only save money, we make our
society stronger.

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And of course, there’s the latest sensation in cooperative applications, crowdfunding, as exemplified by Kickstarter.

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But this technology of collective action and man-machine collaboration can be used for immense social good. For example, after
the devastating earthquake in Haiti last year

36. Mission 4636
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a whole set of new tools for cooperation were deployed to coordinate the activities of volunteers. For example, the Ushahidi
crowd-reporting platform was used to report people in need of rescue via SMS to a special shortcode, the collaborative
OpenStreetMap project was used to quickly map shanty towns so that rescuers could be sent to the right location, and crowd
work platforms like Crowdflower, SamaSource and Amazon Mechanical Turk were used to translate reports from Haitian Creole
into English via volunteers in Haitian diaspora communities thousands of miles away. These applications show a man-machine
symbiosis including smartphone-wielding humans as sensors, remote processors (translators), and as augmented actors, guided
to the locations where they were needed, and told where to dig.

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But they can also be used to manipulate financial markets for private gain, to the detriment of society. Our financial markets are
a great example of collective intelligence gone wrong, abused for private gain rather than public good.

38. How can we make the emerging global
consciousness not only smarter and
more capable, but more moral?
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So that leads me to my concluding question.

39. We’ve got one world. We’d better get it right.
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