WHY THIS MATTERS IN BRIEF
Most humans are good at debating, and now AI is getting better at it too, but its ability to analyse huge volumes of data in real time makes it a formidable tool and opponent.
Over the past year IBM’s Artificial Intelligence (AI) platform Watson has been practising its debating skills, and the other day it made another debut on a new Bloomberg TV show called “That’s Debatable” which aired in the US the other day.
“Is it time to redistribute the wealth?” That’s the topic two former Clinton administration officials, a former Greek finance minister and a researcher who has studied the economics of prostitution, explored in the debate – with a little help from IBM Watson which, as you can see from the video explainer, took all of the public’s input and distilled them down into debating points and questions.
The show, which is a series, was produced by the media and events company Intelligence Squared and Bloomberg, with sponsorship from Big Blue, and John Donvan, an Emmy-winning journalist who has moderated debates for Intelligence Squared since 2008, served as the show’s host and moderator.
How it all works
The first debate featured four esteemed economists: Larry Summers, the former US Treasury secretary and former president of Harvard University, Robert Reich, the former US Labor secretary, Yanis Varoufakis, the outspoken former Greek finance minister, and Allison Shrager, a senior fellow at the Manhattan Institute known for her 2019 book, An Economist Walks Into a Brothel: And Other Unexpected Places to Understand Risk. But IBM is no doubt hoping that, at least to some extent, its Watson that will steal the show.
In particular, the television program highlights one of Watson’s newest capabilities – categorising and summarizing thousands, or even hundreds of thousands, of individual comments and opinions, and distilling them down to a handful of key points.
Called “key point analysis,” the capability has grown out of IBM’s “Project Debater” research, spearheaded by a team in its AI lab in Israel, which has involved building AI software capable of successfully debating humans – and helping humans surface strong arguments from a variety of different types of sources.
IBM hopes that it will be able to sell the technology to companies as a new way to conduct market research and solicit views from both employees and customers, as well as assist in negotiations, and eventually help company executives make decisions faster by helping them quickly see and, if necessary, debate both sides of an argument.
The company also thinks the technology could be used by governments to better understand the views of citizens by helping them distil an entire populations viewpoints and opinions into actionable summaries. Although that said, if it were to be used in this way, which it likely will one day, Watson could unintentionally introduce bias into the government policy making process, and bearing in mind that elsewhere China has already unveiled an AI politician, and Elon Musk has warned of an “immortal AI dictator,” this could create even more challenges for our increasingly polarised echo chamber of a society and its leaders to content with.
“Topic clustering and argument generation, those capabilities came from Debater and these are now being used with select customers,” Dakshi Agrawal, IBM’s chief architect for AI, said. He said key point analysis will allow businesses to “collect tens of thousands of data points and distil them down to make more data-driven decisions.”
The company has staged a series of “grand challenge” public events in the past three years designed to showcase the AI based technology, of which the “It’s Debatable” TV program is the latest.
The key point summarisation tool being featured in the television show can analyse thousands of comments that users submit through a website in response to a question, in this case, the debate proposition: “It is time to redistribute the wealth?”
Using natural language processing – the kind of AI that can analyse and to some extent “understand” language – the IBM system scores these comments for relevancy, discarding those it sees as not being germane to the topic. Then it groups the remaining ones into two broad categories: those that support the proposition, and those that oppose it.
It then further groups the comments in each camp into a handful of key points, using its language processing algorithm to summarise the essence of each point and avoiding repetition of points that are simply expressing the same idea using different language.
The software also tells a user know how often each key point was mentioned by those submitting comments.
“Actually conveying the prevalence of each key point in the data, this is important for decision-makers,” Noam Slonim, the IBM engineer who leads the Project Debater team, said.
Donvan, the “It’s Debatable” host, said that the technology was a much better way to allow the audience to participate in the debate compared to what he and other debate moderators have typically done in the past, which is to simply call on audience members interested in making a comment more or less at random.
“Audiences can be very tricky for me in that I randomly call on people to raise their hands and ask a question of the debaters, and to be honest I have to throw out a large number of the questions because they are repetitive, or they off in outer space, or they are just not well articulated,” he said. “This helps with that challenge.”
Clea Connor, Intelligence Squared’s Chief Executive Officer, said the key point analysis AI allowed the company to incorporate views from a much broader and diverse group of people. It does so by enabling people anywhere in the world to submit opinions via a Web page. “This innovation is really helping us understand what a much larger group of people than the four or six hundred that could attend the event live previously, in this case thousands of people, where they really stand on the issue,” she said.
Slonim said he thought the technology could even be used to make future US Presidential Debates more participatory, which is an interesting idea.
To train an AI system to score arguments for quality, IBM had to create a database of 30,000 human-generated positions on a wide variety of topics which were then assessed by small human focus groups of 10 to 15 individuals, Slonim said. The results of this exercise were then used to teach the AI what constituted a coherent, strong argument.
The key point analysis feature is a refinement of a technology, which IBM called “Speech by Crowd,” that it unveiled last November in a debate held at the Cambridge Union debating club at Cambridge University where Watson took to the floor to battle students on the pros and cons of AI – figuratively of course.