A consortium of top AI experts proposed concrete steps to help machine learning engineers secure the public’s trust. Dozens of researchers and technologists recommended actions to counter public skepticism toward artificial intelligence, fueled by issues like data privacy.

Deep learning promises to help emergency responders find their way through disaster zones. MIT researchers developed a tool that maps where hurricanes and other calamities have wiped out roads, helping to show aid workers the fastest ways to get to people in need.

A new algorithm can triage programming bugs, highlighting dangerous flaws. Microsoft researchers developed a machine learning model that reads the titles of bug reports and recognizes those describing flaws that compromise security.

Computer vision is helping construction workers keep their social distance. Smartvid.io, a service that focuses on construction sites, offers a tool that recognizes when workers get too close to each other. The tool sends distancing warnings and reports to construction superintendents.

It’s time to stop flushing valuable data down the toilet. The Precision Health Toilet, a suite of sensors that attach to an ordinary commode, monitors human waste for input for signs of disease. It identifies individual users by scanning where the sun doesn’t shine.

The wearable revolution is helping doctors figure out what’s troubling your ticker — thanks to deep learning. The problem: Arrhythmias, a range of conditions in which the heart beats too fast, too slow, or erratically, can cause heart attack or stroke.

An AI-driven alarm system helps rescue patients before infections become fatal. The problem: Machine learning can spot patterns in electronic health data indicating where a patient’s condition is headed that may be too subtle for doctors and nurses to catch.

Doctors are overwhelmed by clerical work. Healthcare-savvy voice assistants are picking up the slack.

AI experts convened to discuss how to combat the coronavirus crisis. An online conference hosted by Stanford University’s Institute for Human-Centered AI explored how machine learning is being deployed to address this pandemic — and prepare for the next one.

An unconventional approach to modifying data is cutting the amount of work required to train self-driving cars. Waymo unveiled a machine learning pipeline that varies lidar scans representing pedestrians and other objects.

Unexploded munitions from past wars continue to kill and maim thousands of people every year. Computer vision is helping researchers figure out where these dormant weapons are likely to be.

Chatbots designed to recognize Covid-19 symptoms dispense alarmingly inconsistent recommendations. Given the same symptoms, eight high-profile medical bots responded with divergent, often conflicting advice.

Are you secretly yearning to have a My Little Pony character voice your next online presentation? A new web app can make your dreams come true. 15.ai translates short text messages into the voices of popular cartoon and videogame characters.

Women continue to be severely underrepresented in AI. A meta-analysis of research conducted by Synced Review for Women’s History Month found that female participation in various aspects of AI typically hovers between 10 and 20 percent.

Neural networks revealed both how hard Covid-19 has hit the Chinese economy, and hopeful signs that a renaissance may be underway. Researchers analyzed satellite imagery, GPS signals, and social media to get a multifaceted view of the pandemic’s impact.