ARTIFICIAL intelligence () is by turns terrifying, overhyped, hard to understand and just plain awesome.
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For an example of the last, researchers at the University of California, San Francisco were able this year to hook people up to brain monitors and generate natural-sounding synthetic out of mere brain activity. The goal is to give people who have lost the ability to speak – because of a stroke, ALS, epilepsy or something else – the power to talk to others just by thinking.
That’s pretty awesome.
One area where can most immediately improve our lives may be in the area of mental health. Unlike many illnesses, there’s no simple physical test you can give someone to tell if he or she is suffering from depression. Primary care physicians can be mediocre at recognising if a patient is depressed, or at predicting who is about to become depressed. Many people contemplate suicide, but it is very hard to tell who is really serious about it. Most people don’t seek treatment until their illness is well advanced.
Using , researchers can make better predictions about who is going to get depressed next week, and who is going to try to kill themselves.
The Crisis Text Line is a suicide-prevention hotline in which people communicate through texting instead of phone calls. Using technology, the organisation has analysed more than 100 million texts it has received. The idea is to help counsellors understand who is really in immediate need of emergency care.
You would think that the people most in danger of harming themselves would be the ones who use words like “suicide” or “die” most often. In fact, a person who uses terms like “ibuprofen” or “Advil” is 14 times more likely to need emergency services than a person who uses the word “suicide”. A person who uses the crying face emoticon is 11 times more likely to need an active rescue than a person who uses the word “suicide”. On its website, the Crisis Text Line posts the words that people who are seriously considering suicide frequently use in their texts. A lot of them seem to be all-or-nothing words – “never”, “everything”, “anymore”, “always”. Many groups are using technology to diagnose and predict depression. For example, after listening to millions of conversations, machines can pick out depressed people based on their speaking patterns.
When people suffering from depression speak, the range and pitch of their voice tend to be lower. There are more pauses, starts and stops between words. People whose voice has a “breathy” quality are more likely to re-attempt suicide. Machines can detect this stuff better than humans.
There are also visual patterns. Depressed people move their heads less often. Their smiles don’t last as long. One research team led by Andrew Reece and Christopher Danforth analysed 43,950 Instagram photos from 166 people and recognised who was depressed with 70 per cent accuracy, which is better than general-practice doctors.[…]