IBM Showcases Artificial Intelligence Superiority With Project Dabater

IBM Showcases Artificial
Intelligence Superiority
With Project Debater

© 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
Title
Text
Introduction
IBM Showcases Artificial Intelligence
Superiority With Project Debater
The IBM algorithm Deep Blue beat chess champion Garry Kasparov in
1997.
It was 2011 when IBM’s Watson won the game show Jeopardy.
Shortly after, the IBM Research team was ready to go beyond game
playing and began to brainstorm the next feat to challenge an artificial
intelligence algorithm.
They decided to create an AI algorithm that would be trained on the art of
debate.

This past June, a small group of viewers got to see the IBM Project
Debater’s public debut and its first two debates, when it went head-
to-head with Israeli debaters Dan Zafrir and Noa Ovadia on
increased investment in telemedicine and government subsidies for
space exploration respectively.
From all accounts, IBM Project Debater was a formidable opponent
and surprised many with its ability to make human-like arguments.
It even swayed more audience members to its position on
telemedicine that Zafrir did.
The IBM Project Debater’s Public Debut

This project was the latest in IBM Research’s goal to build a system
“that helps people make evidence-based decisions when answers
aren’t black-and-white.” Debate not only helps us convince others
of our opinion, but it can help us understand and learn from other’s
views.
By training machines in this way, it is hoped that in the future, AI
algorithms will be able to help humans make important decisions
regularly.
IBM Project Debater doesn’t just search its database of millions of
articles from well-known newspapers and magazines—its corpus—
but it has AI technology that can “work with humans to discover,
reason and present new points of view.”
Understanding Other Points Of View

The IBM Research team was able to create an algorithm with the
ability to:
• Generate an opinion driven by data
• Listen and understand an opponent, parsing out the critical bits
of data from flowing narrative
• And express the situation and arguments with concise language
and complete human-like sentences.
Algorithm Capabilities

Even though there were visible stumbling blocks in IBM
Project Debater's debating skills, for the most part, its
debut was a resounding success.
Since it's gone from theory to actual implementation,
albeit with some tweaks still necessary, it makes you
wonder what's next.
From Theory to Implementation

It might be easy for many people to put too much faith in a
machine. Although a machine can cull through the data at a rate
and depth impossible for humans in a similar timeframe, it's not
immune to bias in its findings.
The machine is only as good as the information it was fed.
If some of the resources it used to develop its argument contained
false logic, the algorithm was influenced by that logic in its debate.
Avoid Blind Trust By Implementing Checks and
Balances

Being able to search and summarize millions of human-generated
articles is no small feat, but Project Debater's prowess isn't
representative—yet—of some superintelligence capable of
reasoning in a self-generated manner (although that's likely on the
horizon).
To avoid machines just echoing back erroneous human opinions—
or being manipulated by a government or corporation for its own
purposes—there needs to be a system of checks and balances to
ensure the program’s credibility.

Natural language processing is progressing on many fronts; however, what
Project Debater exhibited was progress in loosely structured language in
the form of conversations and articles.
An algorithm’s ability to put together an argument based on small pieces of
text supported by facts while understanding all the facets of an argument
(logical, emotional) is a higher level function.
Project Debater can analyze its opponent's argument and determine the
appropriate response supported by facts. This represents a massive leap
from "present information" to "make an argument.
Critical To Natural Language Processing Advances

One of the impressive abilities IBM Project Debater exhibited was
the combination of AI techniques it relied upon to solve many
problems and join them together in a solution.
Now that IBM Research succeeded in this first debate, the team
needs to determine practical applications of this technology that
they can sell.
That’s precisely what Arvind Krishna, Director of IBM
Research said he plans to do: “Project Debater’s underlying
technologies will also be commercialized in IBM Cloud and IBM
Watson in the future.”
Practical Applications Of This Technology

Now that AI has gone beyond playing games to learning the art of
persuasion and debate; it has proven that it can handle the "grey
area” and nuances of human interaction and not just follow clear-
cut rules.
“From our perspective, the debate format is the means and not the
end. It's a way to push the technology forward and part of our
bigger strategy of mastering language,” said Aya Soffer, who runs
IBM Research’s global AI team.
It was an impressive debut, and it will be intriguing to see what’s up
next.

© 2017 Bernard Marr , Bernard Marr & Co. All rights reserved
Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a
strategic business & technology advisor to governments and companies. He helps
organisations improve their business performance, use data more intelligently, and
understand the implications of new technologies such as artificial intelligence, big data,
blockchains, and the Internet of Things.
LinkedIn has ranked Bernard as one of the world’s top 5 business influencers. He is a frequent
contributor to the World Economic Forum and writes a regular column for Forbes. Every day
Bernard actively engages his 1.5 million social media followers and shares content that
reaches millions of readers.
Visit The
Website
© 2017 Bernard Marr , Bernard Marr & Co. All rights reserved
Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a
strategic business & technology advisor to governments and companies. He helps
organisations improve their business performance, use data more intelligently, and
understand the implications of new technologies such as artificial intelligence, big data,
blockchains, and the Internet of Things.
LinkedIn has ranked Bernard as one of the world’s top 5 business influencers. He is a frequent
contributor to the World Economic Forum and writes a regular column for Forbes. Every day
Bernard actively engages his 1.5 million social media followers and shares content that
reaches millions of readers.
Visit The
Website

BernardMarr
hello@bernardmarr.com
www.bernardmarr.com

IBM Showcases Artificial Intelligence Superiority With Project Dabater

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IBM Showcases Artificial Intelligence Superiority With Project Dabater