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Make your voice heard on ‘That’s Debatable’
Participate in our final debate show facilitated by natural language processing from Watson. Join the discussion by submitting a short argument for or against the position statement below. All of the arguments submitted will be analyzed by Watson to provide insight into the global public opinion.
Then tune in to “That’s Debatable,” presented by Bloomberg and Intelligence Squared, a debate fueled in part by your submission.
‘That’s Debatable’ on Bloomberg TV Watch episode 2 on November 6, 2020
Should you worry about the national deficit?
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.
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.
Episode 1: It’s time to redistribute the wealth
The data is in, interested in hearing the debate results?
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