Many executives ask me what artificial intelligence
can do. They want to know how it will disrupt their industry and how they can
use it to reinvent their own companies.
But lately the media has sometimes
painted an unrealistic picture of the powers of AI. (Perhaps soon it will take
over the world!) AI is already transforming web search, advertising,
e-commerce, finance, logistics, media, and more. As the founding lead of the
Google Brain team, former director of the Stanford Artificial Intelligence
Laboratory, and now overall lead of Baidu’s AI team of some 1,200 people, I’ve
been privileged to nurture many of the world’s leading AI groups and have built
many AI products that are used by hundreds of millions of people.
Having seen
AI’s impact, I can say: AI will transform many industries. But it’s not magic.
To understand the implications for your business, let’s cut through the hype
and see what AI really is doing today.
Surprisingly, despite
AI’s breadth of impact, the types of it being deployed are still
extremely limited. Almost all of AI’s recent progress is through one type, in
which some input data (A) is used to quickly generate some simple response (B).
For
example:
Being able to input A and output B will transform many
industries. The technical term for building this A→B
software is supervised learning. A→B is
far from the sentient robots that science fiction has promised us.
Human
intelligence also does much more than A→B.
These A→B systems have been improving rapidly, and the best
ones today are built with a technology called deep learning or deep neural
networks, which were loosely inspired by the brain.
But these systems still
fall far short of science fiction. Many researchers are exploring other forms
of AI, some of which have proved useful in limited contexts; there may well be
a breakthrough that makes higher levels of intelligence possible, but there is
still no clear path yet to this goal.
Today’s supervised
learning software has an Achilles’ heel: It requires a huge amount of data. You
need to show the system a lot of examples of both A and B. For instance,
building a photo tagger requires anywhere from tens to hundreds of
thousands of pictures (A) as well as labels or tags telling you if there are
people in them (B). Building a speech recognition system requires tens of
thousands of hours of audio (A) together with the transcripts (B).
So what can A→B do?
Here’s one rule of thumb that
speaks to its disruptiveness:
If a typical person can
do a mental task with less than one second of thought, we can probably automate
it using AI either now or in the near future.
A lot of valuable work
currently done by humans — examining security video to detect suspicious
behaviors, deciding if a car is about to hit a pedestrian, finding and
eliminating abusive online posts — can be done in less than one second. These
tasks are ripe for automation. However, they often fit into a larger context or
business process; figuring out these linkages to the rest of your business is
also important.
AI work requires carefully
choosing A and B and providing the necessary data to help the AI figure out the
A→B relationship. Choosing A and B creatively has already
revolutionized many industries. It is poised to revolutionize many more.
After understanding what AI
can and can’t do, the next step for executives is incorporating it into their
strategies. That means understanding where value is created and what’s hard to
copy. The AI community is remarkably open, with most top researchers
publishing and sharing ideas and even open-source code. In this world of open
source, the scarce resources are therefore:
Data. Among leading AI teams,
many can likely replicate others’ software in, at most, 1–2 years. But it is
exceedingly difficult to get access to someone else’s data. Thus data, rather
than software, is the defensible barrier for many businesses.
Talent. Simply downloading and
“applying” open-source software to your data won’t work. AI needs to be
customized to your business context and data. This is why there is currently a
war for the scarce AI talent that can do this work.
Much has been written about
AI’s potential to reflect both the best and the worst of humanity.
For
example, we have seen AI providing conversation and comfort to the lonely; we
have also seen AI engaging in racial discrimination. Yet the biggest harm that
AI is likely to do to individuals in the short term is job displacement, as the
amount of work we can automate with AI is vastly bigger than before. As
leaders, it is incumbent on all of us to make sure we are building a world in
which every individual has an opportunity to thrive. Understanding what AI can
do and how it fits into your strategy is the beginning, not the end, of that
process.
No comments:
Post a Comment