Awesome, not awesome.
#Awesome
“[AI in mental illness] is one of the most exciting new directions that we have. Because mental health problems, particularly depression but all across the board, are so important. They’re also understaffed in terms of capable counselors, psychologists, psychiatrists and mental health professionals in general. So the ability to quantify, in real time, a person’s state of mind is an extraordinary new development. Whether that’s how you strike a keyboard, the intonation of your speech, your breathing or all of the other parameters that can be assessed passively, without any effort…The field using AI in mental health care, while it’s still very underdeveloped and early, is one of the greatest opportunities going forward. Because there’s a terrible mismatch of the burden of mental health and the field’s ability to support people. I think the promise here is quite extraordinary. It’s using technology to enhance human mental health, which never tends to get the same respect as physical health.” — Alex Orlando, Journalist Learn More from Discover >
#Not Awesome
“An even more sobering thought is that driverless cars might make some problems we want them to solve — like traffic, sprawl and air pollution — even worse. If driverless cars quadruple the capacity of highway lanes, but people travel many more miles when they don’t have to do the driving, then traffic may not get better. We want ambitious technology that can really change the world. But sometimes I worry that optimism can make us less likely to confront the reality of congestion, air pollution and road safety.” — Shira Ovide, Writer Learn More from The New York Times >
What we’re reading.
1/ Artificial Intelligence is being used to track the pandemic, but will we be comfortable living under mass surveillance in the future?. Learn More from The Guardian >
2/ Researchers are using machine learning to analyze the protein interactions between SARS-CoV-2 and human cells, to find weaknesses that we can use to inhibit its infectious abilities. Learn More from News@Northeastern >
3/ Facebook claims its algorithms are getting better at detecting hate speech, while refusing to estimate how much hate speech is posted by its users. Learn More from WIRED >
4/ Machine learning models fed with data from normal behavior fail to work properly when behavior gets weird — like during a pandemic. Learn More from MIT Technology Review >
5/ The Library of Congress digitizes millions of newspapers from decades of US History, hoping people will find interesting ways to use machine learning to analyze the dataset. Learn More from TechCrunch >
6/ In the near term, the largest leaps in the field of AI are most likely to happen in computer vision, training data, and natural language processing. Learn More from The Next Platform >
7/ Elder care robots that we hoped would decrease loneliness for older populations may not offer “proper human companionship.” Learn More from Inverse >
Links from the community.
“Kite Launches AI-Powered JavaScript Completions” submitted by Samiur Rahman (@samiur1204). Learn More from Kite >
“Why You Should Consider an A.I. Running Coach” submitted by Avi Eisenberger (@aeisenberger). Learn More from elemental >
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