Software that automatically detects emotions may soon help negotiators refine their tactics.
Negotiation is a fundamental business skill—one that is inextricably bound up with human emotion and psychology as much as economic calculus. Perhaps one day, robot lawyers will go forth to negotiate on our behalf. But, in the meantime, at least one negotiation expert thinks A.I. can be used today to improve humans’ negotiation tactics.
Jared Curhan is a professor at M.I.T.’s Sloan School of Business who specializes in negotiation. His particular focus is on what researchers call “subjective value.” That’s a fancy term for how people feel about the outcome of a negotiation: do they think they got a fair deal or got screwed?
Negotiation theorists once dismissed subjective value as irrelevant. But Curhan and others have shown that it is a good predictor of economic payoffs—especially when parties will have to negotiate with one another more than once over the course of a relationship.
Like most negotiation trainers, Curhan teaches students through role-playing exercises. For the past several years, he’s been using software that can run these games and provide immediate feedback to students on their performance in the form of computer-generated graphs and charts showing how well they’ve done in both economic and subjective terms. Now he’s adding A.I. to that mix.
Curhan has partnered with a company called Affectiva, which was spun out of MIT’s famed Media Lab, that uses computer vision to identify emotions from facial expressions. He’s using Affectiva’s software to analyze videos of negotiation simulations. “We are trying to isolate particular emotions that have influence on the outcome of negotiations,” Curhan says. “How do you make a positive impression on your counterparty and how does that relate to your facial expression?”
Right now, Curhan is just gathering data. “We don’t know which emotional expressions are favorable and which aren’t,” he says. He hopes to find out—and then teach students how to alter their facial expressions to avoid negative outcomes. He even envisions a day when an A.I.-enabled alarm could warn a negotiator when a counterparty’s facial expressions indicate a bargaining session is about to go south.
That’s just one example of A.I.’s implications for negotiation. Another is IBM’s “Project Debater” A.I. It can analyze a proposition and automatically highlight the best arguments for and against it, factoring in both logical and emotional impact. These technologies could transform business negotiations—and probably do so long before we have robot lawyers.
Jeremy Kahn
@jeremyakahn
