Artificial Intelligence

Artificial Intelligence
Blue Paper
January 26, 2016

Artificial intelligence—a new machine age
When computers mimic the capabilities of the human brain, that is artificial
intelligence (AI). From the outside, AI looks like computers that have independent
thoughts. Have no fear, however. The gears of their machine “brains” may be turning,
but, for right now, they’re not really thinking—at least not the way that human beings
think.
Popular culture has held artificial intelligence in great esteem for decades. The
excitement around conscious robots has grown as computers have become ingrained
in every aspect of our lives.
You don’t have to look long for examples of artificial intelligence. And, the applications
are diverse:
• Self-driving car: A Wired
®
magazine reporter got behind the wheel of—but
did not drive—a “piloted” Audi
®
A7 for a 500-mile excursion. “It’s so
sophisticated that I never felt anything unusual,” the reporter wrote.[1]
• Robot butler: The Aloft
®
hotel in Cupertino, Calif., dispatches cute, 3-foot-
tall rolling robots with toiletries and food. The robot asks guests to rate the
delivery service on a touchscreen before saying goodbye.[2]
• Document examiners: E-discovery software was used to sift through 1.5
million documents in about a month for less than $100,000. This task would
have been performed by paralegals and lawyers for a significantly higher
cost.[3]
• Game show champ: The IBM
®
Watson™ computer defeated two human
“Jeopardy!
®
” champions. IBM is developing versions of Watson for health
care and retail applications.[4]
Yet, for all its promise, artificial intelligence seems to live under a dark cloud. Elon
Musk, the tech industry superstar who runs an electric car company and a space
exploration company, said AI is “summoning the demon.”[5] And, movies about the
dangers of AI are too numerous to mention.
Artificial intelligence is opening exciting doors in our personal and professional lives,
but the technology is not without risk—real and perceived. Taking advantage of the
opportunities offered by artificial intelligence calls for understanding the basics of AI,
examining applications of the technology and exploring its pros and cons.
A crash course in artificial intelligence
Artificial intelligence exists because of deep learning (or machine learning). And, deep
learning starts with neural networks. Neural networks simulate the web of neurons in
the human brain.[6] Data make neural networks smarter. The idea behind training the
neural network is this: “Feed enough photos of a dog into these neural nets, and they
can learn to recognize a dog. Feed them enough human dialogue, and they may learn
to carry on a conversation.”[7] Training neural networks is the engine of deep
learning.
Artificial Intelligence Page 2 of 12 info.4imprint.com

As the neural net is trained, the computer has a job to do: “Come up with a statistical
rule that correlates inputs with the correct outputs.”[8] This rule is a deep learning
algorithm, and its accuracy improves with additional data and time—just like the
performance of the human brain.[9]
Deep learning is edging machines toward almost humanlike understanding:[10]
“Machine learning is a way of getting computers to know things when they see
them by producing for themselves the rules their programmers cannot specify.
The machines do this with heavy-duty statistical analysis of lots and lots of
data.”
Programming deep learning algorithms does not require subject matter expertise. For
example, a team in Switzerland developed a deep learning algorithm that’s been used
to read Chinese at the native speaker level.[11] No one on the team can speak or
understand Chinese. An algorithm used at the world-renowned European Organization
for Nuclear Research (CERN) physics lab helped spot subatomic particles better than
software written by physicists.[12] Programmers set the wheels of deep learning in
motion, and computers make continuous improvement.
The human brain solves complex problems by having sets of rules, and it’s easy to
translate rules into programming. That’s why artificial intelligence excels at complex
tasks with explicit rules. To compare, the human brain is naturally good at tasks with
implicit rules—facial identification, recognizing speech, picking out objects in
pictures.[13] AI can complete these simple tasks with a lot of data and training.
Today’s artificial intelligence landscape
Business spending on artificial intelligence is exploding. In 2010, venture capital (VC)
spending on AI was less than $20 million. In 2014, it was close to $300 million. Figure
1 below shows the rapid rise in AI dollars:[14]

Figure 1: Total venture capital money spent on AI startups
This rapid rise in VC funding indicates that industry sees AI as the future. Examples of
AI investment include:
• Google
®
: The search engine uses RankBrain, an AI system to interpret
search queries. RankBrain has a success rate of 80 percent when it comes to
guessing which pages should rank on top. To compare, human engineers
guessed right 70 percent of the time.[15]
• Facebook
®
: The social network has an AI lab, and it uses AI to personalize
homepages.[16],[17]
• Baidu
®
: The leading Chinese search engine hired away Andrew Ng, the data
scientist who helped lead deep learning at Google.[18] Deep learning could
improve Baidu’s speech recognition technology, which is important to illiterate
smartphone users. Ten percent of Baidu’s searches are by voice, and that
number could jump to 50 percent by 2020.[19]
• Forbes
®
: The financial news outlet trusts technology by robo-writing firm
Narrative Science
®
to automate the writing of basic financial stories.
All these examples show that industry-leading organizations are putting money into
AI. Most notable, though, is that they trust AI with their profit centers. Artificial
intelligence and deep learning are essential to product development and customer
satisfaction.
The biggest buzz in AI today surrounds quantum computing. Google’s D-Wave 2X
quantum computer has grabbed attention with tests showing that it’s 100 million
times faster than any standard computer. Harmut Neven, engineering director of the
quantum computer experiments, said the fast performance “will carry over to
commercially relevant problems as they occur in tasks relevant to machine
intelligence.”[20]

What does this mean to someone who’s not a computer expert? In short, quantum
computers are very good at optimization problems, which happen when you try to
reach a solution by taking thousands of variables into consideration. For instance, if
you were planning a trip to Europe, you could tell a quantum computer which cities
you’d like to visit and how much you want to spend. The computer would give you an
itinerary based on those elements and even more factors, including:[21],[22]
• Weather
• Baggage fees
• Upgrades
• Routes
• And, many more
Optimized solutions are derived from volumes of data—volumes of data that train
deep learning algorithms. The future of artificial intelligence may be tied to quantum
computing and optimization:[23]
“Imagine NASA being able to use quantum computers to optimize the flight
trajectories of interstellar space missions, FedEx
®
being able to optimize its
delivery fleet of trucks and planes, an airport being able to optimize its air
traffic control grid, the military being able to crack any encryption code, or a
Big Pharma company being able to optimize its search for a breakthrough new
drug.”
Part of the reason quantum computers are so powerful is that they work differently
from standard computers. A standard computer reads everything in 1s and 0s. A
quantum computer, to compare, reads everything in 1s and 0s, and sometimes a 1
and a 0 can exist at the same time.[24]
Google’s D-Wave 2X isn’t the only quantum computer on the block. The Yale Quantum
Institute also is exploring quantum computers.[25] As commercial interest in artificial
intelligence has grown, so has the market for AI products and services.
Artificial intelligence in action
The capabilities of artificial intelligence today are impressive—and they’ll only get
better. Deep learning models for computers likely will improve over time.
We’re at the point where computers can see, hear, speak, write and read.[26] Human
brains now have competition for high-level cognitive activities:
• See: AI learned to identify traffic signs in Germany. The deep learning
algorithm was twice as good as humans at identifying signs.[27]
• Hear and speak: Microsoft
®
demonstrated real-time translation by AI.
Communication between colleagues in California and Germany went from
spoken English to written German to spoken German.[28]

• Write: The New York Times
®
published a quiz that asked readers to identify
whether a human or a computer wrote the content. Machines generated six
of the eight writing samples, which had been published in other places.[29]
• Read: AI developed by Stanford University can determine sentiment of
sentences. The creators give it an 85 percent accuracy rate, and the program
is continuously learning and refining itself.[30]
Specific industries also are applying AI. In health care, AI helped discover new
indicators for tumors and develop a predictive model for cancer survival rates.[31]
The technology is driving medical breakthroughs.
Public transportation and trucking have an interest in AI. Self-driving cars, like the
aforementioned Audi, are gaining traction. Alphabet, the parent company of Google,
says regulations are keeping its driverless vehicle from the mainstream.[32] Self-
driving cars likely will have a big impact on how we move around and how stuff gets
shipped.
Governments have put AI to work in security. Britain uses face-recognition technology
for border control. U.S. intelligence agencies use voice-recognition software to convert
phone calls into text, making conversations easier to scan for information.[33] These
are more examples of AI masterfully managing lots of data.
Unsupervised learning is the next step in artificial intelligence. Today, deep learning
algorithms need humans to label data, and computers go from there. Unsupervised
learning algorithms will be able to learn without human help.[34] The learning of
machines eventually could look more like the learning of human brains.
The deeper meaning of artificial intelligence
Artificial intelligence is here, but humankind still is sorting out what it means to our
personal and professional lives. Tech leaders such as Bill Gates, Elon Musk and
Stephen Hawking have warned about AI.[35] But, deep learning algorithms are aiding
doctors and breaking down language barriers. When it comes to AI, should we be
worried?
Why you should worry about AI
As it advances, artificial intelligence technology likely will eliminate jobs held by
humans. Using computers instead of people will reduce labor costs—and could
increase inequality. A Bloomberg
®
report points out, “If the race to develop artificial
intelligence depends on huge amounts of data and computing power, a big chunk of
the future economy could be controlled by a handful of companies.”[36]
Unemployment is only part of the AI picture.
Theoretical physicist Stephen Hawking voiced concern in 2014. “Humans,” he said,
“limited by slow biological evolution, couldn’t compete and would be superseded by
AI.”[37] In a TEDx talk, deep learning expert Jeremy Howard said that growth in
human brain performance is slower than growth in computer performance. To make
his point, he showed the following diagram (see Figure 2):[38]

Figure 2: The growth of machine learning
It’s unclear what will happen when the development of machines outpaces human
capability. The lead scientist behind Google’s quantum computer said one day AI
could “[mimic] common sense.”[39] Without a doubt, the relationship between
humans and non-human beings would shift dramatically if machines had common
sense.
Why you shouldn’t worry about AI
Take a page from “Jeopardy!” champ Ken Jennings when it comes to AI. “I, for one,
welcome our new computer overlords,” he quipped following his game show
domination by IBM’s Watson.[40] Jennings’ attitude shows a relaxed perspective on
the amazing development of deep learning.
Knowledge is not wisdom. Most would agree that knowledge comes from learning, but
wisdom comes from experience. Computers may have knowledge, but, as non-human
entities, they cannot have experiences. They cannot have personal stories or
motivation, and they don’t get context the way people do.
This experience deficit matters a great deal in the world of business, because
businesses are humans solving problems for other humans. Machines, even the most
intelligent computers, can’t conduct in-depth interviews to gain deep understanding of
consumers’ stories. Even though robots can generate functional writing, “emotional
storytelling and complex insights that come from real-life experience is still the
domain of the human brain.”[41] People practice empathy and understand emotion,

both of which drive relationships—lasting relationships that loyal customers have with
brands they love.
Humans may beat computers when it comes to feelings, but AI is becoming so
sophisticated that you don’t feel the technology—and that’s a good thing. Yahoo!
®
president and CEO Marissa Mayer said AI “lets technology get less in the way” so
users can focus on doing more.[42] As the advanced technology fades to the back,
human accomplishments move to the front.
There’s no getting around it: AI is a threat to some human jobs.[43],[44],[45] But,
the anxiety around AI could be refocused. A report from The Economist
®
framed it
like so: “Perhaps the best way to think about AI is to see it as simply the latest in a
long line of cognitive enhancements that humans have invented to augment the
abilities of their brains.”[46] The jobs that remain will be improved because of deep
learning.
Final thoughts on artificial intelligence
The promise of artificial intelligence is both exhilarating and terrifying at the same
time. These competing feelings inspired by AI call back the dual existence of 1s and
0s in quantum computing. Logically, it doesn’t seem like these opposites—delight and
horror, 1 and 0—should be able to share spaces. But, they do nevertheless.
Developments in artificial intelligence only will get faster and more dramatic.
Applications will expand, and new opportunities will emerge. What remains to be seen
is how long the human brain can beat computers at simple tasks governed by implicit
rules and how humankind’s relationship with AI will evolve as the technology charges
ahead.
Endnotes
[1] Davies, Alex. “I Rode 500 Miles in a Self-Driving Car and Saw the Future. It’s
Delightfully Dull.” Wired.com. Conde Nast Digital, 7 Jan. 2015. Web. 21 Dec. 2015.
<http://www.wired.com/2015/01/rode-500-miles-self-driving-car-saw-future-
boring/>.
[2] Smith, Dave. “This is what it’s like to have an adorable robot bring you room
service at a hotel.” Business Insider. Business Insider, Inc, 05 Mar. 2015. Web. 21
Dec. 2015. <http://www.businessinsider.com/robot-room-service-video-aloft-
hotel-2015-3>.
[3] Markoff, John. “Armies of Expensive Lawyers, Replaced by Cheaper Software.”
The New York Times. The New York Times, 04 Mar. 2011. Web. 21 Dec. 2015.
<http://www.nytimes.com/2011/03/05/science/05legal.html?pagewanted=all&_r=0>.
[4] Markoff, John. “Computer Wins on ‘Jeopardy!’: Trivial, It’s Not.” The New York
Times. The New York Times, 16 Feb. 2011. Web. 21 Dec. 2015. <
http://www.nytimes.com/2011/02/17/science/17jeopardy-
watson.html?pagewanted=all>.

[5] ” Rise of the Machines: Artificial intelligence scares people—excessively so.”
Economist. The Economist Newspaper, 9 May 2015: n. pag. 9 May 2015. Web. 21
Dec. 2015. <http://www.economist.com/news/briefing/21650526-artificial-
intelligence-scares-peopleexcessively-so-rise-machines>.
[6] Ibid
[7] Metz, Cade. “For Google, Quantum Computing Is Like Learning to Fly.” Wired.com.
Conde Nast Digital, 11 Dec. 2015. Web. 21 Dec. 2015. <http://www.wired.com/2015/
12/for-google-quantum-computing-is-like-learning-to-fly/>.
[9] The Wonderful and Terrifying Implications of Computers That Can Learn. Perf.
Jeremy HowardTED. TED Conferences, LLC, Dec. 2014. Web. 21 Dec. 2015.
<http://www.ted.com/talks/
jeremy_howard_the_wonderful_and_terrifying_implications_of_computers_that_can_learn>.
Jeremy Howard. TED. TED Conferences, LLC, Dec. 2014. Web. 21 Dec. 2015.
[13] Ibid
[14] Clark, Jack. “Artificial Intelligence.” Bloomberg. Bloomberg LP, 9 July 2015. Web.
21 Dec. 2015. <http://www.bloombergview.com/quicktake/artificial-intelligence>.
[15] Clark, Jack. “Google Turning Its Lucrative Web Search Over to AI Machines.”
Bloomberg. Bloomberg LP, 26 Oct. 2015. Web. 21 Dec. 2015.
<http://www.bloomberg.com/news/articles/2015-10-26/google-turning-its-lucrative-
web-search-over-to-ai-machines>.
[17] Clark, Jack. “Google Turning Its Lucrative Web Search Over to AI Machines.”
Bloomberg. Bloomberg LP, 26 Oct. 2015. Web. 21 Dec. 2015.

<http://www.bloomberg.com/news/articles/2015-10-26/google-turning-its-lucrative-
web-search-over-to-ai-machines>.
[18] McMillan, Robert. “AI Won’t End the World, But It Might Take Your Job.”
Wired.com. Conde Nast Digital, 2 Feb. 2015. Web. 21 Dec. 2015.
<http://www.wired.com/2015/02/ai-wont-end-world-might-take-job/>.
[20] Neven, Hartmut. “When can Quantum Annealing Win?” Google Research Blog.
Google, 8 Dec. 2015. Web. 21 Dec. 2015. <http://googleresearch.blogspot.com/2015/
12/when-can-quantum-annealing-win.html>.
[21] Basulto, Dominic. “Why Google’s new quantum computer could launch an
artificial intelligence arms race.” Washington Post. The Washington Post, 10 Dec.
2015. Web. 21 Dec. 2015. <https://www.washingtonpost.com/news/innovations/wp/
2015/12/10/why-googles-new-quantum-computer-could-launch-an-artificial-
intelligence-arms-race/>.
[22] Google and NASA’s Quantum Artificial Intelligence Lab. Google, 2013. YouTube.
Web. 21 Dec. 2015. <https://youtu.be/CMdHDHEuOUE>.
[24] Google and NASA’s Quantum Artificial Intelligence Lab. Google, 2013. YouTube.
Web. 21 Dec. 2015. <https://youtu.be/CMdHDHEuOUE>.
[27] Ibid

[29] “Did a Human or a Computer Write This?” The New York Times. The New York
Times, 07 Mar. 2015. Web. 21 Dec. 2015. <http://www.nytimes.com/interactive/
2015/03/08/opinion/sunday/algorithm-human-quiz.html?_r=0>.
[30] Abate, Tom. “Stanford Algorithm Analyzes Sentence Sentiment, Advances
Machine Learning.” Stanford Engineering. Stanford University, 1 Oct. 2013. Web. 21
Dec. 2015. <http://engineering.stanford.edu/news/stanford-algorithm-analyzes-
sentence-sentiment-advances-machine-learning>.
Jeremy Howard.TED. TED Conferences, LLC, Dec. 2014. Web. 21 Dec. 2015.
[32] Drew, Katie. “A lot to talk about in Google’s new self-driving car patent.” CNBC.
CNBC LLC, 19 Dec. 2015. Web. 21 Dec. 2015. <http://www.cnbc.com/2015/12/18/
googles-new-self-driving-car-patent-a-lot-to-talk-about.html>.
[34] Ibid
[35] Sainato, Michael. “Stephen Hawking, Elon Musk, and Bill Gates Warn About
Artificial Intelligence.” New York Observer. Observer Media, 19 Aug. 2015. Web. 21
Dec. 2015. <http://observer.com/2015/08/stephen-hawking-elon-musk-and-bill-gates-
warn-about-artificial-intelligence/>.
[36] Clark, Jack. “Artificial Intelligence.” Bloomberg. Bloomberg LP, 9 July 2015. Web.
21 Dec. 2015. <http://www.bloombergview.com/quicktake/artificial-intelligence>.
[37] Sainato, Michael. “Stephen Hawking, Elon Musk, and Bill Gates Warn About
Artificial Intelligence.” New York Observer. Observer Media, 19 Aug. 2015. Web. 21
Dec. 2015. <http://observer.com/2015/08/stephen-hawking-elon-musk-and-bill-gates-
warn-about-artificial-intelligence/>.
[39] Metz, Cade. “For Google, Quantum Computing Is Like Learning to Fly.”
Wired.com. Conde Nast Digital, 11 Dec. 2015. Web. 21 Dec. 2015.
<http://www.wired.com/2015/12/for-google-quantum-computing-is-like-learning-to-
fly/>.
[40] Markoff, John. “Computer Wins on ‘Jeopardy!’: Trivial, It’s Not.” The New York
Times. The New York Times, 16 Feb. 2011. Web. 21 Dec. 2015. <
http://www.nytimes.com/2011/02/17/science/17jeopardy-
watson.html?pagewanted=all>.

[41] Holland, Taylor Mallory. “Will AI Take Writing Jobs Away from Content
Marketers?” Content Standard. Skyword Inc., 14 Dec. 2015. Web. 21 Dec. 2015.
<http://www.skyword.com/contentstandard/for-storytellers/will-ai-take-writing-jobs-
away-from-content-marketers/>.
[42] “Yahoo’s Mayer: Artificial Intelligence Is Next Big Thing.” Bloomberg. Bloomberg
LP, 16 June 2015. Web. 21 Dec. 2015. <http://www.bloomberg.com/news/videos/
2015-06-16/yahoo-s-mayer-artificial-intelligence-is-next-big-thing>.
[44] McMillan, Robert. “AI Won’t End the World, But It Might Take Your Job.”
Wired.com. Conde Nast Digital, 2 Feb. 2015. Web. 21 Dec. 2015.
<http://www.wired.com/2015/02/ai-wont-end-world-might-take-job/>.
Economist. The Economist Newspaper. 9 May 2015: n. pag. 9 May 2015. Web. 21

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