A week after Donald Trump's election, a thirty-year-old cognitive scientist named Maya Shankar purchased a plane ticket to Flint, Michigan. Shankar held one of the more unorthodox jobs in the Obama White House, running the Social and Behavioral Sciences Team, also known as the President's "nudge unit." When she launched the team, in early 2014, it felt, Shankar recalls, "like a startup in my parents' basement"--no budget, no mandate, no bona-fide employees. Within two years, the small group of scientists had become a staff of dozens--including an agricultural economist, an industrial psychologist, and "human-centered designers"--working with more than twenty federal agencies on seventy projects, from fixing gaps in veterans' health care to relieving student debt. Usually, the initiatives had, at their core, one question: Could the growing body of knowledge about the quirks of the human brain be used to improve public policy? For months, Shankar had been thinking about how to bring behavioral science to bear on the problems in Flint, where a crisis stemming from lead contamination of the drinking water had stretched on for almost two years. She wondered if lessons from the beleaguered city could inform the Administration's approach to the broader threat posed by lead across America--in pipes, in paint, in dust, and in soil. "Flint is not the only place poisoning kids," Shankar said. In recent years, behavioral science has become a voguish field. In 2002, the Israeli psychologist Daniel Kahneman won a Nobel Prize in Economic Sciences for his work with a colleague, Amos Tversky, exploring the peculiarities of human decision-making in the face of uncertainty. A basic premise of the discipline they'd helped to create was that people's cognition is bias-prone, and susceptible to the cognitive equivalent of optical illusions. As a result, small tweaks of presentation or circumstance could make a major difference: if a judge rendered a decision about granting parole just before a meal, the inmate's odds for a favorable outcome dipped to near zero; just after the judge ate, the chances rose to around sixty-five per cent. Grocers had learned that they could sell double the amount of soup if they placed a sign above their cans reading "limit of 12 per person." But, for all the field's potential, its advances seemed mostly to have served the private sector. A prominent exception was the "nudge," a notion advanced by the legal scholar Cass R. Sunstein, now at Harvard Law School, and the University of Chicago behavioral economist Richard Thaler, in their 2008 best-seller "Nudge: Improving Decisions About Health, Wealth, and Happiness."

"Face recognition is an important social skill, but not all of us are equally good at it," says Beijing Normal University cognitive psychologist Jia Liu. A new study by Liu and colleagues Ruosi Wang, Jingguang Li, Huizhen Fang, and Moqian Tian provides the first experimental evidence that the inequality of abilities is rooted in the unique way in which the mind perceives faces. "Individuals who process faces more holistically"--that is, as an integrated whole--"are better at face recognition," says Liu. The findings will appear in an upcoming issue of Psychological Science, a journal published by the Association for Psychological Science. In daily life, we recognize faces both holistically and also "analytically"--that is, picking out individual parts, such as eyes or nose.

VERY soon, you may be able to keep a close watch on your home while you------re miles away. And this time, it------s not just about physical changes, say when a person falls or leaves the gas on. This is about technology that will discern and react to the non-physical aspects, say loneliness and fear, in conjunction with the physical aspects. The ultimate goal is to detect changes in behaviour, such as sudden mood swings or a lessening of the ability to comprehend. They represent telltale signs of potential problems, and early detection may allow the problem to be corrected before it spins out of control.

There are two fields with seemingly endless career opportunities: healthcare and computer science. And when medical care intersects with technology, the possibilities are life changing. Machine learning introduces new insights to healthcare professionals through compiling big data to improve the way doctors and clinicians can diagnose, treat and even predict outcomes for their patients, according to Finale Doshi-Velez (pictured), assistant professor of Computer Science at Harvard's John A. Paulson School of Engineering and Applied Sciences. Doshi-Velez is on the front lines of educating and researching tangible ways to improve mental health through machine learning. She is working with students in several areas, but her focus is on machine learning for healthcare applications focused on dissecting the autism spectrum and helping to alleviate depression. Doshi-Velez spoke with Lisa Martin (@Luccazara), co-host of theCUBE, SiliconANGLE Media's mobile live streaming studio, at the Stanford Global Women in Data Science (WiDS) Conference in Stanford, CA, about her work in these developing fields and how she is preparing the next generation by teaching students the emerging skills they will need in a new workplace.

Foregoing a good night's sleep may wreck the brain's ability to make new memories. A new study from Johns Hopkins University School of Medicine demonstrated that a key purpose of sleep is to recalibrate the brain cells responsible for learning and memory, solidifying lessons learned for when the sleeper is awake. Using a mouse model, the researchers discovered several important molecules that govern the recalibration process, as well as evidence that sleep deprivation, sleep disorders and sleeping pills can interfere with the process. Graham Diering, Ph.D., the postdoctoral fellow who led the study, explained that the results from the mouse study can be used to make determinations about the human brain. "Our findings solidly advance the idea that the mouse and presumably the human brain can only store so much information before it needs to recalibrate," he said in a statement.

Tired of your barista giving you attitude, spitting in your coffee if you only mention Trump, or misspelling your name on your morning cup of joe? Surely a robot could do better. Well, we are about to find out, because on Monday, Cafe X opened its very first robotic cafe in San Francisco's Metreon shopping center Digital Trends reports. Promising "precision crafted specialty coffee in seconds, the way the roaster intended," Cafe X thinks that anything a human can do, its machines can do better. Nicknamed Gordon, after a Cafe X employee, this robot mans, or robots, two standard professional coffee machines in order to serve up espressos and lattes. In the San Francisco location, customers can grab a cup of coffee with beans from AKA Coffee, Verve Coffee Roasters, or Peet's.

Financial firms were the early adopters of the mainframe computer, relational databases, and have eagerly awaited the next level of computational power. Inorganics Intelligence helps Fintech companies in solving human problems, by increasing efficiency. Artificial Intelligence (AI) improves results by applying methods derived from aspects of Human Intelligence at a beyond human scale. Technologies like Machine Learning, Artificial Intelligence (AI), Neural Networks, Big Data Analytics, evolutionary algorithms, and much more have allowed computers to crunch huge varied, diverse and deep datasets than ever before. In early ages of Banking, bankers used to have personal connections to their customers to help them assist well for their decisions.

Researchers at the Massachusetts Institute of Technology have developed wearable tech that could help avoid crossed wires and miscommunication. Using artificial intelligence to detect the "tone" of a conversation based on speech patterns, the researchers were able to use a wearable band to "classify the overall emotional nature of the subject's historic narration". More simply, the band could spot signs of sadness, anger, boredom and so on from a person's voice. The project, by Tuka AlHanai and Mohammad Mahdi Ghassemi at CSAIL, is one of many aimed at'social coaching' designed to help people with chronic social disorders become more comfortable with the complexities of communication. Day-to-day life is underpinned by social interactions that play a key role in our mental health and development.

Sick of diets that only tell you what you can't eat. Suggestic reverses this trend by focusing on telling you what you can have. Starting a diet is a piece of cake. Well … did someone say cake? Even if you don't have the willpower to stick to your culinary resolutions, a new app may be able to help.

Marketing is no longer about right-brain versus left-brain. Technology is getting smarter, and consumers are turning to machines to help them make better purchase decisions. As people turn to their devices to make product recommendations and automate their services, one has to wonder: Will brands start marketing to machines versus humans? "Marketing to machines -- that kind of scares me," says Jeff Barnett, CEO of CRM giant Salesforce Commerce Cloud. While the concept may seem a bit dystopian, it's not completely farfetched.