Collaborating Authors


San Antonio GOP Congressman Will Hurd Reaches Across the Aisle on Artificial Intelligence


Robin Kelly, D-Illinois, to author a detailed report on how to keep the U.S. from falling behind China on artificial intelligence.

Illinois law regulates artificial intelligence use in video job interviews


A new law in Illinois will regulate the use of artificial intelligence in job interviews. The Artificial Intelligence Video Interview Act, House Bill 2557, requires companies to notify the applicant when the system is being used, explain how the AI works, get permission from the applicant, limit distribution of the video to people involved with the process and to destroy the video after 30 days. Matthew Jedreski, counsel at Davis Wright Tremaine LLP in Seattle, is a litigator and employment attorney who updates clients on local and state employment laws. Jedreski said AI video interviews apply psychometrics, which is the science of measuring attitude and personality traits. "It's reading data and then analyzing it to determine whether it can draw conclusions about the person being interviewed," Jedreski said.

It Takes Nine to Smell a Rat: Neural Multi-Task Learning for Check-Worthiness Prediction Artificial Intelligence

We propose a multi-task deep-learning approach for estimating the check-worthiness of claims in political debates. Given a political debate, such as the 2016 US Presidential and Vice-Presidential ones, the task is to predict which statements in the debate should be prioritized for fact-checking. While different fact-checking organizations would naturally make different choices when analyzing the same debate, we show that it pays to learn from multiple sources simultaneously (PolitiFact, FactCheck, ABC, CNN, NPR, NYT, Chicago Tribune, The Guardian, and Washington Post) in a multi-task learning setup, even when a particular source is chosen as a target to imitate. Our evaluation shows state-of-the-art results on a standard dataset for the task of check-worthiness prediction.

How Artificial Intelligence Determines Which Airline Stories Go Viral


Early one afternoon in October 2016, CBS News correspondent Kris Van Cleave was taking the day off, having brunch with three friends in Los Angeles, when his phone began pinging. With increasing urgency, colleagues were sending a tweet, showing a smoldering American Airlines aircraft at Chicago O'Hare. They asked, what did he know? He reached American Airlines spokesman Ross Feinstein just after 161 passengers and nine crew members safely evacuated from the burning Boeing 767-300. Soon, Van Cleave filed a basic story about an incident the NTSB would later say was an uncontained fire in the airline's right engine, caused by a failed turbine disk.

Whether it's for restaurants or Trump, bots have gotten pretty good at shilling


For all the huge potential of artificial intelligence, bots still have a long way to go to pass as human. You don't know whether I'm a dog or not, but you can at least be reasonably confident that I'm not a bot. But then I'm writing articles of between 300 and 3,000 words: there's plenty of room to slip up – especially if you've been trained through machine learning, rather than speaking, reading and writing in English for more than 30 years. In the realm of short-form social media and comments sections, where grammar and syntax are both more fluid and less closely scrutinised, it's far easier for bots to blend in, as a study from the University of Chicago found out last week. The bot they'd trained to review restaurants was astroturfing with the best of them.