I spent a day at IBM's mysterious research hub north of NYC, where I met some of the top AI leaders in the country. Here are 4 takeaways on where they think the tech is headed.

Dario Gil

  • IBM’s Thomas J. Watson Research Center in Yorktown Heights, New
    York, may be nondescript, but it houses some of the brightest minds
    working on artificial intelligence today. I spent a day there
    speaking with several top executives on IBM’s AI ambitions. 
  • The company is serious about the technology and is thinking in
    decades, not years. A major challenge, however, will be the move
    from narrow to broad AI.
  • IBM has produced some of the most high-profile AI machines in
    the past decade, like one that can go head-to-head with the world’s
    best debaters.
  • It’s continuing to build upon that legacy, including a new
    program in development that can automatically provide play-by-play
    commentary for soccer matches. 

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Tucked into a luscious forest in Yorktown Heights, New York, a
hamlet about an hour outside of New York City by train, is IBM’s
Thomas J. Watson Research Center.  

It’s a rather nondescript, croissant-shaped building that may
surprise those who were expecting a modern-looking facility where
legions of robots roam down bright white hallways and regularly
interact with employees.IBM Research

But it houses some of the brightest minds on AI that are doing
the early-stage work on what will become commercial applications to
change how we
watch sports
,
debate one another
, or even judge whether an algorithm is
biased.  

After spending a day at the center and meeting with several
executives, I left with four main takeaways of where IBM is at on
AI, where it’s heading, and the challenges it faces to get
there.

IBM is thinking about AI in decades, not years

From machines that go head-to-head with the world’s greatest
debaters or pinpoint the most exciting moments of a sporting event,
to a slew of offerings that ensure algorithms are fair and
explainable, IBM is serious about artificial intelligence. 

IBM Research

The company is mapping its AI journey in decades, not years, and
pursuing potentially revolutionary technology that could redefine
how companies operate. Among the other notable milestones, it
launched a
joint research laboratory
with the Massachusetts Institute of
Technology in 2017 and had 175 papers published at eight AI
conferences in the last year alone. And with $2.58 billion in
revenue in 2018, IBM
again ranked
as a market leader in AI product. 

Aside from the machines themselves, the company is also trying
to position itself as a leader in ethical AI to help overcome
escalating concerns with the technology. Part of that effort is
trying to change the negative connotations that surround the word
“artificial intelligence.” 

“AI is a loaded term,” Dario Gil, director of IBM Research, told
Business Insider. “If only we could just start adding a little bit
more precision around language, that would be helpful.” 

The journey from narrow to broad AI will be difficult 

Many AI-based applications currently in use aim to solve a
specific problem, like figuring out
when to restock a shelf
or trying to eliminate
bias in hiring decisions

IBM Research

While the platforms are transforming operations, Sriram
Raghavan, the vice president of IBM Research AI, argues that
ultimately, it’s an inefficient system. With so many models,
organizations are unlikely to “spend six months and a few hundred
million dollars” to implement each one of them, he says.

So, instead of a bespoke application that requires a large
amount of data, IBM is focused on developing what they refer to as
“broad AI,” or models that can manage a wide range of different
tasks simultaneously with much less information. That effort,
however, will take decades, according to Raghavan. 

“We are making progress on it significantly,” he told Business
Insider. But “it’s going to be a journey. We’re talking about
inventing brand new techniques.” 

Trust in AI remains a key problem

Companies are rushing to adopt artificial intelligence, but
trust in the platforms is still a major problem. 

Mass amounts of data are fed into systems that can guide
life-changing decisions for individuals, like
whether you get brought in for an interview
for your dream job.
A rush of negative headlines have also raised concerns over

how fair some of the algorithms are
, an indicator in many cases
of the lack of diverse data being used to power the AI tools.
IBM Research

IBM is trying to demystify the questions around the technology
in a number of ways. But one problem remains defining what a fair
model is. To solve that issue, IBM introduced “AI Fairness 360,” a
library of algorithms that can be used to check whether a data set
is biased. 

“You actually grow this culture of understanding AI biases. And
as we all evolve then eventually, maybe one day, it’s not going to
be a problem,” Saska Mojsilovic, who head the Foundations of
Trusted AI group at IBM, told Business Insider. 

Read more: Accenture’s
head of artificial intelligence shares the 4-step plan every
company should consider before investing in AI

Explaining the AI is also a challenge. Say a financial
institution uses an algorithm to determine whether an individual
qualifies for a loan. If the application is denied, that company
needs to be able to outline to the customer the reasoning behind
the decision.

IBM recently introduced a toolkit comprised of algorithms,
demos, and other resources known as “AI Explainability 360” that
provides insight into how models come to a final conclusion,
including one that outlines what information was used to come to
the decision. It also shows what features that, if they were
present, would have reversed the choice. So if a loan application
is denied, the algorithm could provide a route for a customer to
improve their chances the next time.  

If you want to see IBM’s AI capabilities, watch a major sporting
event 

One technology currently in use is an AI-based program that
automatically analyzes the sound of the crowd, the reaction of a
player or players, and other factors to determine the most exciting
moments of events like the Masters Tournament or the

U.S. Open

Even in sports, however, IBM thinks about how to make the model
more fair.IBM research

One concern, for example, was how to adequately measure audience
reaction on holes or courts where the crowd may not be as large as
others. The team employed Watson OpenScale, a product that takes
real-time feedback and adjust AI models to make them more
trustworthy. In golf, for example, the platform monitors the
estimated crowd size and automatically re-weights that category
when considering the overall output. 

“It’s a nice illustration of what it really means to have to
monitor your models once they are in deployment,” said John Smith,
who heads the development of vision, speech, and language AI tools
at IBM Research.  

IBM is currently experimenting with automated sports
play-by-play commentary. The company is testing the product on past
soccer matches because it “wanted a challenge,” according to
Smith. 

Once the model is successfully trained, the hope is to be able
to ingest the raw footage to transform the raw pixels into
language. It’s a huge evolution from AI-based applications that can
scan still images to determine the object and come up with a
caption.

SEE ALSO: Accenture’s
head of artificial intelligence shares the 4-step plan every
company should consider before investing in AI


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I spent a day at IBM's mysterious research hub north of NYC, where I met some of the top AI leaders in the country. Here are 4 takeaways on where they think the tech is headed.