Think Again: The Power of Knowing What You Don't Know Adam Grant (good books to read for beginners .TXT) 📖

down their opponents’ proposals and doubled down on their own positions, which prevented both sides from opening their minds. The skilled negotiators rarely went on offense or defense. Instead, they expressed curiosity with questions like “So you don’t see any merit in this proposal at all?”

Questions were the fourth difference between the two groups. Of every five comments the experts made, at least one ended in a question mark. They appeared less assertive, but much like in a dance, they led by letting their partners step forward.

Recent experiments show that having even one negotiator who brings a scientist’s level of humility and curiosity improves outcomes for both parties, because she will search for more information and discover ways to make both sides better off. She isn’t telling her counterparts what to think. She’s asking them to dance. Which is exactly what Harish Natarajan does in a debate.

DANCING TO THE SAME BEAT

Since the audience started out favoring preschool subsidies, there was more room for change in Harish’s direction—but he also had the more difficult task of advocating for the unpopular position. He opened the audience’s mind by taking a page out of the playbook of expert negotiators.

Harish started by emphasizing common ground. When he took the stage for his rebuttal, he immediately drew attention to his and Debra’s areas of agreement. “So,” he began, “I think we disagree on far less than it may seem.” He called out their alignment on the problem of poverty—and on the validity of some of the studies—before objecting to subsidies as a solution.

We won’t have much luck changing other people’s minds if we refuse to change ours. We can demonstrate openness by acknowledging where we agree with our critics and even what we’ve learned from them. Then, when we ask what views they might be willing to revise, we’re not hypocrites.

Convincing other people to think again isn’t just about making a good argument—it’s about establishing that we have the right motives in doing so. When we concede that someone else has made a good point, we signal that we’re not preachers, prosecutors, or politicians trying to advance an agenda. We’re scientists trying to get to the truth. “Arguments are often far more combative and adversarial than they need to be,” Harish told me. “You should be willing to listen to what someone else is saying and give them a lot of credit for it. It makes you sound like a reasonable person who is taking everything into account.”

Being reasonable literally means that we can be reasoned with, that we’re open to evolving our views in light of logic and data. So in the debate with Harish, why did Debra neglect to do that—why did she overlook common ground?

It’s not because Debra is eight years old. It’s because she isn’t human.

Debra Jo Prectet is an anagram I invented. Her official name is Project Debater, and she’s a machine. More specifically, an artificial intelligence developed by IBM to do for debate what Watson did for chess.

They first dreamed the idea up in 2011 and started working intensively on it in 2014. Just a few years later, Project Debater had developed the remarkable ability to conduct an intelligent debate in public, complete with facts, coherent sentences, and even counterarguments. Her knowledge corpus consists of 400 million articles, largely from credible newspapers and magazines, and her claim detection engine is designed to locate key arguments, identify their boundaries, and weigh the evidence. For any debate topic, she can instantaneously search her knowledge graph for relevant data points, mold them into a logical case, and deliver it clearly—even entertainingly—in a female voice within the time constraints. Her first words in the preschool subsidy debate were, “Greetings, Harish. I’ve heard you hold the world record in debate competition wins against humans, but I suspect you’ve never debated a machine. Welcome to the future.”

Of course, it’s possible that Harish won because the audience was biased against the computer and rooting for the human. It’s worth noting, though, that Harish’s approach in that debate is the same one that he’s used to defeat countless humans on international stages. What amazes me is that the computer was able to master multiple complex capabilities while completely missing this crucial one.

After studying 10 billion sentences, a computer was able to say something funny—a skill that’s normally thought to be confined to sentient beings with high levels of social and emotional intelligence. The computer had learned to make a logical argument and even anticipate the other side’s counterargument. Yet it hadn’t learned to agree with elements of the other side’s argument, apparently because that behavior was all too rarely deployed across 400 million articles by humans. They were usually too busy preaching their arguments, prosecuting their enemies, or politicking for audience support to grant a valid point from the other side.

When I asked Harish how to improve at finding common ground, he offered a surprisingly practical tip. Most people immediately start with a straw man, poking holes in the weakest version of the other side’s case. He does the reverse: he considers the strongest version of their case, which is known as the steel man. A politician might occasionally adopt that tactic to pander or persuade, but like a good scientist, Harish does it to learn. Instead of trying to dismantle the argument that preschool is good for kids, Harish accepted that the point was valid, which allowed him to relate to his opponent’s perspective—and to the audience’s. Then it was perfectly fair and balanced for him to express his concerns about whether a subsidy would give the most underprivileged kids access to preschool.

Drawing attention to common ground and avoiding defend-attack spirals weren’t the only ways in which Harish resembled expert negotiators. He was also careful not to come on too strong.

DON’T STEP ON THEIR TOES

Harish’s next advantage stemmed from one of his disadvantages. He would never have access to as many facts as the computer. When the audience was polled