Artificial intelligence programmers are developing bots that can identify digital bullying and sexual harassment. Known as "#MeTooBots" after the high-profile movement that arose after allegations against the Hollywood producer Harvey Weinstein, the bots can monitor and flag communications between colleagues and are being introduced by companies around the world. Bot-makers say it is not easy to teach computers what harassment looks like, with its linguistic subtleties and grey lines. Jay Leib, the chief executive of the Chicago-based AI firm NexLP, said: "I wasn't aware of all the forms of harassment. I thought it was just talking dirty. It comes in so many different ways. It might be 15 messages … it could be racy photos."
Asymptomatic people who are infected with Covid-19 exhibit, by definition, no discernible physical symptoms of the disease. They are thus less likely to seek out testing for the virus, and could unknowingly spread the infection to others. But it seems those who are asymptomatic may not be entirely free of changes wrought by the virus. MIT researchers have now found that people who are asymptomatic may differ from healthy individuals in the way that they cough. These differences are not decipherable to the human ear.
At least one out of every five people who get the coronavirus doesn't show symptoms and can unknowingly spread the virus to others. Those who don't feel sick and aren't notified of exposure can't know that they should get tested. But researchers at the Massachusetts Institute of Technology may have found a way to identify these silent coronavirus carriers without a test. A study published in September describes an artificial-intelligence model that can distinguish between the coughs of people with the coronavirus and those who are healthy. It can even tell from voluntary, forced coughs whether people were healthy or were asymptomatic carriers, based on sound variations too subtle for the human ear to discern.
An algorithm can detect the coronavirus in people who are asymptomatic, just from listening to the way they cough. Coronavirus patients who don't have symptoms still exhibit subtle changes not always detectable by the naked eye - or ear. Researchers at MIT developed an AI-powered model that distinguishes asymptomatic people from uninfected individuals by analyzing recordings of coughs submitted by tens of thousands of volunteers online. The algorithm accurately identified 98.5 percent of coughs from people who tested positive for the virus, including 100 percent of coughs from asymptomatic patients. The team is gathering more samples, with the goal of producing an app that could be a convenient and free pre-screening tool. Researchers at MIT used AI to analyze thousands of coughs and detect differences in those of people with coronavirus.
As millions of people worldwide battle the symptoms of COVID-19, a group of "silent patients" may not even know they're sick and spreading the virus. Asymptomatic people, by definition, have no physical symptoms of the illnesses they carry. Researchers at the Massachusetts Institute of Technology (MIT) however, say they may be showing symptoms after all -- in the sound of their cough. Their study has created an artificial intelligence program that can identify if someone has coronavirus by the way their coughing sounds. Researchers programmed their AI model with thousands of different recorded coughs from both healthy and sick volunteers.