Why We Should Not Know Our Own Passwords

The Conversation 3/9/2017

Elon University Professor Megan Squire looks into possible methods for protecting the data on your smartphone and social media accounts. The article focuses on potential searches by US border agents of people traveling from other countries. She explains several different methods of smartphone privacy protection, such as a system that uses your locations and habitual gesture patterns to identify you, or passwords even you don’t know.

Machine Learning Reveals Lack of Female Screen Time in Top Films

New Scientist, 3/8/2017

Shri Narayanan, from the University of Southern California, has developed a new program that runs facial recognition software and voice recognition software simultaneously to analyze gender bias in high-grossing box-office films. This program has analyzed 300 films, and the study shows that women are underrepresented on the big screen. Narayanan is also using machine learning and natural language processing to evaluate film scripts, to explore further biases.

Virtual Reality Training for “Safety-Critical” Jobs

University of Exeter, 3/6/2017

A virtual-reality training system currently in development by Exeter-based researchers and experts from the nuclear power industry could help prevent accidents in high-risk jobs. Employees using the system could gain experience with high-stress tasks in a safe environment, while employers could use the eye tracking and physiological sensor data to better understand how workers learn and how they react under pressure.

Bridging a Digital Divide That Leaves Schoolchildren Behind

The New York Times, 2/22/2017

The federal government is attempting to bridge the growing digital divide in low-income families by expanding a subsidy program, Lifeline, to include broadband Internet access. The Federal Communications Commission’s main goal in revising Lifeline is to address the increasing number of students without online access needed to complete schoolwork and homework. Other methods are being used to in an effort to patch this divide, such as wifi-equipped buses and school-provided wireless hotspots.

Scientists Reveal New Super-Fast Form of Computer That “Grows As It Computes”

University of Manchester, 3/1/2017

Researchers from the University of Manchester have demonstrated that it is possible to build a super-fast self-replicating computer. Because it is composed of DNA molecules rather than electrical circuitry, when presented with a choice, such a computer can replicate itself to simultaneously compute the solutions. Demonstrating that this (previously only theoretical) machine is physically possible opens up new possibilities in the future of scientific computing.

Machine-Learning Algorithms Can Predict Suicide Risk More Readily Than Clinicians, Study Finds

Newsweek, 2/27/2017

Human clinicians are known not to be very accurate at predicting suicides, so researchers are developing machine-learning algorithms that use multiple factors to identify short-term suicide risk. Data scientists trained the algorithm on data from thousands of clinical records, from both non-fatal suicide cases and random patients. Accuracy was significantly better than studying only one risk factor at a time. Using such a system could aid clinicians in targeting at-risk patients and treating them early.

AI Predicts Autism From Infant Brain Scans

IEEE Spectrum, 2/15/2017

Researchers at the University of North Carolina, Chapel Hill have applied deep-learning algorithms to brain scans of children with a high risk of autism. Algorithms used three indicators, brain surface area, volume, and the gender of the child, to determine if 6- to 12-month-old infants were likely to develop autism. The results were 81% accurate at predicting later diagnosis. This improves over a 50% prediction rate from behavioral questionnaires.