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Interesting article re: designing an efficient and responsive bot: leveraging key human linguistic features in order to have the machine "converse" with humans, comprehend their needs, and respond appropriately. Programming a machine to exhibit the conversational nuances and sophisticated comprehension of a normal human=hard.

Bradley Hayes, a post-doc student at the Massachusetts Institute of Technology, has invented @DeepDrumpf, an amusing bit of artificial intelligence. DeepDrumpf is a bot trained on the publicly available speech transcripts, tweets, and debate remarks of Donald Trump. Using a machine learning model known as a Recurrent Neural Network, the bot generates sequences of words based on priming text and the statistical structure found within its training data. Created to highlight the absurdity of this election cycle, it has amassed over 20,000 followers and has been viewed over 12 million times -- showcasing the consequences of training a machine learning model on a dataset that embodies fearmongering, bigotry, xenophobia, and hypernationalism. Here's a sample tweet: "We have to end education. What they do is unbelievable, how bad. Nobody can do that like me. Believe me."

An interesting story--my students, you might recall Sheryl Turkle of MIT referencing robot therapists in her TED talk. USC has developed a robot therapist, Ellie, designed to talk to people who are struggling emotionally, and to take their measure in a way no human can. Originally developed to work with military PTSD patients, Ellie's purpose: to gather information and provide real human therapists detailed analysis of patients' movements and vocal features, in order to give new insights into people struggling with emotional issues. The body, face and voice express things that words sometimes obscure. Ellie's makers believe that her ability to do this will ultimately revolutionize American mental health care.

"Falsehood flies, and the Truth comes limping after it," Jonathan Swift once wrote. It was hyperbole three centuries ago. But it is a factual description of social media, according to an ambitious and first-of-its-kind study produced by MIT and published Thursday in Science. The massive new study analyzes every major contested news story in English across the span of Twitter's existence-some 126,000 stories, tweeted by 3 million users, over more than 10 years-and finds that the truth simply cannot compete with hoax and rumor. By every common metric, falsehood consistently dominates the truth on Twitter, the study finds: Fake news and false rumors reach more people, penetrate deeper into the social network, and spread much faster than accurate stories. "It seems to be pretty clear [from our study] that false information outperforms true information," said Soroush Vosoughi, a data scientist at MIT who has studied fake news since 2013 and who led this study. "And that is not just because of bots. It might have something to do with human nature."

As AI advances, so does its language. A chat bot by Google uses language to speak with others in conversation. However, it runs into some problematic issues, especially regarding its ethics. For instance, it will associate doctors as men and nurses as women. Research is being put in place to make it a safer program.