While NLP models often seek to capture cognitive states via language, the validity of predicted states is determined by comparing them to annotations created without access the cognitive states of the authors. In behavioral sciences, cognitive states are instead measured via experiments. Here, we introduce an experiment-based framework for evaluating language-based cognitive style models against human behavior. We explore the phenomenon of decision making, and its relationship to the linguistic style of an individual talking about a recent decision they made. The participants then follow a classical decision-making experiment that captures their cognitive style, determined by how preferences change during a decision exercise. We find that language features, intended to capture cognitive style, can predict participants' decision style with moderate-to-high accuracy (AUC ~ 0.8), demonstrating that cognitive style can be partly captured and revealed by discourse patterns.

When it comes to the California DMV, is this a case of brand new year, same old tune? It's a positive sign that the massive bureaucracy's director has been checking out reader complaints about the license renewal process for drivers after age 70, and here's a news bulletin: He's even tossing out some of the crazy test questions that many of you have been griping about. I'll get to that in a moment, but first let's dip into the mail bag, which continues to overflow with tales from the Department of Motor Vehicles. Dave Warburton, 76, of Santa Clarita went to renew his license the first week of January and was told there was no record of his pre-registration in the computer system. "Not off to a good start," he wrote in an email.

Now imagine a city without private cars. A city where transportation is emissions-free, largely self-driving and connected to the internet. A city where cars, as well as taxis, buses, trains and bicycles, are shared. Instead of parked cars and concrete, city streets might be filled with mini parks, markets and more. A look at how innovation and technology are transforming the way we live, work and play.

Why are so many AI researchers so worried about lethal autonomous weapons? What makes autonomous weapons so much worse than any other weapons we have today? And why is it so hard for countries to come to a consensus about autonomous weapons? Not surprisingly, the short answer is: it's complicated. In this month's podcast, Ariel spoke with experts from a variety of perspectives on the current status of LAWS, where we are headed, and the feasibility of banning these weapons. Guests include ex-Pentagon advisor Paul Scharre (3:40), artificial intelligence professor Toby Walsh (40:51), Article 36 founder Richard Moyes (53:30), Campaign to Stop Killer Robots founders Mary Wareham and Bonnie Docherty (1:03:38), and ethicist and co-founder of the International Committee for Robot Arms Control, Peter Asaro (1:32:39). You can listen to the podcast above, and read the full transcript below. You can check out previous podcasts on SoundCloud, iTunes, GooglePlay, and Stitcher. If you work with ...