Microsoft researcher Dafna Shahaf, who headed the study, began by attempting to convey to the AI linguistic hallmarks of comedy, like sarcasm and wordplay. Shahaf fed the program hundreds of old New Yorker captions and cartoons and, with the aid of crowdsourced workers from Amazon’s Mechanical Turk, painstakingly organized each by two categories: context and anomalies. The ‘context’ label described what was pictured — in an office setting, objects like “secretary” and “phone” — while ‘anomalies’ highlighted any potential source of humor — an unexpected “stairway” in said office, for example.
Shahaf then set the software loose at the offices of the New Yorker, tasking it with identifying (or trying to identify) the funniest cartoon captions among a week’s worth of reader submissions. The result? The AI and the editors agreed about 55.8 percent of the time, or on about 2,200 selections. That’s nothing to sneeze at, Shahaf told Bloomberg — on average, the AI saved Mankoff “about 50 percent of [the] workload.”
It isn’t difficult to imagine applications beyond editorial decision-making. The techniques might one day be used to improve Microsoft’s real-time translation efforts (such as Skype Translator), or, Eric Horvitz told Bloomberg, help flesh out the personalities of digital assistants like Siri and Cortana.
And Microsoft’s software isn’t the only AI humorist around, surprisingly. An Israeli student developed a system capable of recognizing “patronizing sounding semantics” and “slang words in phrases in text” by feeding it more than 5,000 Facebook posts. Hebrew University’s SASI, or Semi-supervised Algorithm for Sarcasm Identification, can recognize sarcastic sentences in Amazon.com product reviews. And a scientist at Purdue University has designed algorithms capable not only of identifying jokes, but explaining why a particular joke is funny.
But consistently hilarious robots are a ways off. While Microsoft’s AI found that brevity played best in the New Yorker’s caption section, a University of Michigan system favored downbeat punchlines. Reconciling the two — deriving an objective humor metric — will take a lot more algorithmic fine-tuning. “Computers can be a great aid,” Mankoff told Bloomberg, “[but] there are more things in humor and human beings than are dreamt of in even Microsoft’s algorithms.”
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