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IBM Watson uses natural language processing capability to bring global voices to the debate.
“That’s Debatable” is a limited series presented by
Bloomberg Media and Intelligence Squared U.S. and
sponsored exclusively by IBM—featuring industry
leaders, economists, policy makers, and public
intellectuals to debate some of today’s most pressing
For each episode of “That’s Debatable,” IBM Watson used a new advancement in natural language processing (NLP) from IBM Research to provide insight into three distinct debate topics. More than 5,000 arguments were submitted online from around the world across the three topics, which were then analyzed and distilled into key points that were highlighted on the show and discussed by human debaters.
It’s time to redistribute the wealth
Economic inequality has become a linchpin of modern politics. As nations around the world face a reckoning on race and social justice and work to combat the economic impacts of the pandemic, we ask: Is it time to redistribute the wealth? Should we address growing inequality by overhauling our tax system, expanding our social safety nets, and investing more in public initiatives like universal health care, education, and infrastructure? Or would awealth transfer unduly punish the economic elite, destroy the promise of a meritocracy, and inevitably lead to excessive government intervention in our social and economic lives?
A U.S.-China Space Race Is Good for Humanity
Nearly 70 years ago, the Space Race galvanized international support for scientific achievement and ushered in a new era of technological advancement. And since the historic Apollo 11 mission, the United States has maintained its status as the world’s leading nation in space. But now, China is ramping up its national space industry with huge investments in next-generation technologies that promise to transform military, economic, and political realities here on Earth. Against this backdrop, we ask: Would a new U.S.-China space race be good for humanity? Could a 21st-century great power competition drive innovation, rally public support for science and discovery, and launch humans into the next generation? Or would this competition catalyze an expensive global arms race, militarize space for decades to come, and destroy any hope of international peace and cohesion in the future.
Stop worrying about national deficits?
Governments around the world have spent unprecedented sums — trillions of dollars — to combat the economic impacts of coronavirus. In the United States alone, the national deficit surpassed $3 trillion this year. That’s three times larger than in 2019 and some $2 trillion more than the White House projected back in February. But just what does rising government debt mean for our future? A new crop of economists – adherents to Modern Monetary Theory – have a bold proposition: Don't worry about it. In a modern economy, they argue, deficits are no bogeyman. And they're certainly no excuse to halt state spending on things like education and healthcare. Take Japan, for instance, where the national deficit is a soaring $12 trillion and counting. But others are far more wary. They warn that unless political leaders balance the books, soaring federal debt will undermine the nation's economic future and compromise national security and sovereignty. So, we ask, are rising national deficits cause for concern?
Key point analysis
How it works
Watson uses the latest innovations in natural language processing, available in products like Watson Discovery, to identify the most significant key points and generate coherent narratives.
For “That’s Debatable,” Watson analyzes every submitted argument to determine if the content is for or against the position statement. Watson also removes submissions deemed irrelevant, such as those that are off-topic, or those that are deemed neutral – neither supporting nor contesting the statement.
Watson evaluates the quality of each submitted argument and identifies potential key points by grading and filtering high-quality arguments. It disregards potential key points that are too long, too emotional in tone, are incoherent or include redundancies. The arguments matched to each key point are sorted by the their argument quality and by the confidence in the matching.
The ranking of the quality is based on the machine learning model, which was trained on human assesments of over 30,000 arguments. There is a general correlation between the argument quality score and factors including grammar, clarity and repetition.
Watson now identifies how many arguments support each of the potential key points. It then selects a small set of key points that are diverse and cover the majority of arguments submitted.
Finally, Watson selects the key points cited most often in the submissions. For each key point, a small subset of the strongest arguments that support that key point are selected. Those key points and arguments are then used to formulate coherent, salient narratives — one arguing the pro side of the debate, the other arguing the con side.
Try it yourself
See how your powers of persuasion stack up. Submit an argument either for or against the debate topic from the first episode, then click “Match to key point” to find out if your argument aligns with one of the key points, and how it ranks in comparison to the other statements supporting the same key point. Try it out with the second and third debate topics as well.
Find answers and insights in your documents
Watson Discovery is AI-powered search that uses innovative, market-leading natural language processing to understand your industry's unique language. It quickly finds answers and uncovers meaningful business insights from your documents and webpages, cutting research time by more than 75%.