Artificial
Intelligence (AI) is advancing so rapidly that even its developers are being
caught off guard. Google co-founder Sergey Brin said in Davos, Switzerland, in
January that it “touches every single one of our main projects, ranging from
search to photos to ads … everything we do … it definitely surprised me, even
though I was sitting right there.”
Intelligent
machines are taking over thousands of jobs, and being qualified is no longer
enough to keep your job. Earlier this year, consulting firm McKinsey and Co.
released a study that said 51% of all jobs could be automated in the next 20
years. Even specialized professions like medicine, law and banking are feeling
the heat of Artificial Intelligence (AI). A few months ago, investment bank JP
Morgan made the news by introducing intelligent machines to review financial
deals that once kept employees busy for thousands of hours. Diagnostics and
other decision-making skills previously thought of as the exclusive preserve of
human beings, will soon be better handled by machines
The
long-promised AI, the stuff we’ve seen in science fiction, is coming and we
need to be prepared. Today, AI is powering voice assistants such as Google
Home, Amazon Alexa and Apple Siri, allowing them to have increasingly natural
conversations with us and manage our lights, order food and schedule meetings.
Businesses are infusing AI into their products to analyse the vast amounts of
data and improve decision-making. In a decade or two, we will have robotic
assistants that remind us of Rosie from “The Jetsons” and R2-D2 of “Star Wars.”
This has
profound implications for how we live and work, for better and worse. AI is
going to become our guide and companion — and take millions of jobs away from
people. We can deny this is happening, be angry or simply ignore it. But if we
do, we will be the losers. As I discussed in my new book, “Driver in the
Driverless Car,” technology is now advancing on an exponential curve and making
science fiction a reality. We can’t stop it. All we can do is to understand it
and use it to better ourselves — and humanity.
Rosie and
R2-D2 may be on their way but AI is still very limited in its capability, and
will be for a long time. The voice assistants are examples of what
technologists call narrow AI: systems that are useful, can interact with humans
and bear some of the hallmarks of intelligence — but would never be mistaken
for a human. They can, however, do a better job on a very specific range
of tasks than humans can. I couldn’t, for example, recall the winning and
losing pitcher in every baseball game of the major leagues from the previous
night.
Narrow-AI
systems are much better than humans at accessing information stored in complex
databases, but their capabilities exclude creative thought. If you asked
Siri to find the perfect gift for your mother for Valentine’s Day, she might
make a snarky comment but couldn’t venture an educated guess. If you asked her
to write your term paper on the Napoleonic Wars, she couldn’t help. That is
where the human element comes in and where the opportunities are for us to
benefit from AI — and stay employed.
Nearly 20 years ago, in 1997 former world chess champion Garry
Kasparov had played chess against IBM’s supercomputer Deep Blue. The match was
a watershed for AI and an extraordinary technical feat. Strangely, although
Kasparov lost, it left me more in awe of the incredible capabilities of the
human brain than of the machine. His account of the Deep Blue match itself is
fascinating. Famously, Kasparov stormed out of one game and gave antagonistic
press conferences in which he protested against IBM’s secrecy around the Deep
Blue team and its methods, and insinuated that the company might have cheated.
In Deep Thinking,
Kasparov offers an engaging insight into his psychological state during the
match. To a degree, he walks back on his earlier claims, concluding that
although IBM probably did not cheat, it violated the spirit of fair competition
by obscuring useful information.
Then, he sets out the details of that titanic event in his
book Deep Thinking.
In his
book, he acknowledges that he is a sore loser but was clearly traumatised by
having a machine outsmart him. He was aware of the evolution of the technology
but never believed it would beat him at his own game. After coming to grips
with his defeat, 20 years later, he says fail-safes are required … but so is
courage.
Kasparov
wrote: “When I sat across from Deep Blue twenty years ago I sensed something
new, something unsettling. Perhaps you will experience a similar feeling the
first time you ride in a driverless car, or the first time your new computer
boss issues an order at work. We must face these fears in order to get the most
out of our technology and to get the most out of ourselves. Intelligent
machines will continue that process, taking over the more menial aspects of
cognition and elevating our mental lives toward creativity, curiosity, beauty,
and joy. These are what truly make us human, not any particular activity or
skill like swinging a hammer — or even playing chess.”
In other
words, we better get used to it and ride the wave.
In Deep Thinking, Kasparov also delves into the renaissance
of machine learning. He highlights the radical differences between Deep Blue
and AlphaGo, a learning algorithm created by my company DeepMind to play the
massively complex game of Go. In March 2016, AlphaGo defeated 18-time world
champion Lee Sedol, widely hailed as the greatest player of the past decade.
Whereas Deep Blue followed instructions carefully honed by a
crack team of engineers and chess professionals, AlphaGo
played against itself repeatedly, learning from its mistakes and developing
novel strategies. Several of its moves against Lee had never been seen in human
games, which upended centuries of traditional Go wisdom by playing on the fifth
line early in the game.
Most excitingly, because its learning algorithms can be
generalized, AlphaGo holds promise far beyond the game for which it was
created. Kasparov relishes this potential, discussing applications from machine
translation to automated medical diagnoses. AI will
not replace humans, he argues, but will enlighten and enrich us. His position is especially notable coming from someone who
would have every reason to be bitter about AI’s advances.
Human
superiority over animals is based on our ability to create and use tools. The
mental capacity to make things that improved our chances of survival led to a
natural selection of better toolmakers and tool users. Nearly everything a
human does involve technology. For adding numbers, we used abacuses and
mechanical calculators and now spreadsheets. To improve our memory, we wrote on
stones, parchment and paper, and now have disk drives and cloud storage.
AI is the
next step in improving our cognitive functions and decision-making.
Think
about it: When was the last time you tried memorizing your calendar or Rolodex
or used a printed map? Just as we instinctively do everything on our
smartphones, we will rely on AI. We may have forfeited skills such as the
ability to add up the price of our groceries but we are smarter and more
productive. With the help of Google and Wikipedia, we can be experts on any
topic, and these don’t make us any dumber than encyclopedias, phone books and
librarians did.
A valid
concern is that dependence on AI may cause us to forfeit human creativity. As
Kasparov observes, the chess games on our smartphones are many times more
powerful than the supercomputers that defeated him, yet this didn’t cause human
chess players to become less capable — the opposite happened. There are now
stronger chess players all over the world, and the game is played in a better
way.
Adaptation, Resiliency & Risk-Taking
“No matter how many people are worried about
jobs, or the social structure, or killer machines, we can never go back,” he
concludes.
Kasparov’s intelligent
advice in his book is worth quoting at length:
“The willingness to keep trying new things — different
methods, uncomfortable tasks — when you are already an expert at something is
what separates good from great. Focusing on your strengths is required for peak
performance, but improving your weaknesses has the potential for the greatest
gains. This is true for athletes, executives, and entire companies. Leaving
your comfort zone involves risk, however, and when you are already doing well
the temptation to stick with the status quo can be overwhelming, leading to
stagnation.”
Disrupting Education
Kasparov is particularly concerned about how a deep underlying
conservatism and resistance to experimentation has become a chronic problem
within the traditional educational system. “The
prevailing attitude is that education is too important to take risks. My
response is that education is too important not to take risks,” he says.
Kasparov says, even
though they often receive little encouragement from the older guard, who often
still resist the new methods of learning. “We
need to find out what works and the only way to do that is to experiment,” he argues. “The kids can handle it. They are already doing it on their
own. It’s the adults who are afraid.”
Learning by Doing
“There will be redistribution of jobs. Many
jobs today — like drone operators or 3D printer managers or social media
managers — they didn’t exist 10 years ago, 15 years ago. No doubt in 10, 15
years, there will be many jobs, maybe the best-paid jobs, that don’t exist
today, and we don’t even know how these jobs will look. I think that’s natural.
All we have to do is realize that this process is inevitable, and we have to
prepare us mentally, but also to have some sort of safety cushions to help people
that will have great difficulty in adjusting.”
Much like looking out
over the chessboard and pondering the wisdom of our next move, we cannot be
frozen into inaction because of fear. We must be willing to make that next move. And
then another, and another. And then we must learn from our experiences, and
especially our mistakes, if we hope to prosper. “To keep ahead of the machines, we must not
try to slow them down because that slows us down as well,”
Kasparov concludes in
his closing chapter. “We must speed them up. We must give them, and ourselves, plenty
of room to grow. We must go forward, outward, and upward.” -Wise advice from
the greatest of all grandmasters.
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