Awesome, not awesome.
#Awesome
“… [A]n international team [is] using machine learning to comb through social media posts, news reports, data from official public health channels, and information supplied by doctors for warning signs the virus is taking hold in countries outside of China. The program is looking for social media posts that mention specific symptoms, like respiratory problems and fever, from a geographic area where doctors have reported potential cases. Natural language processing is used to parse the text posted on social media, for example, to distinguish between someone discussing the news and someone complaining about how they feel.” — Will Knight, Writer Learn More from WIRED >
#Not Awesome
““Subjecting 5-year-olds to [facial recognition] technology [at schools] will not make anyone safer, and we can’t allow invasive surveillance to become the norm in our public spaces,” said Stefanie Coyle, deputy director of the Education Policy Center for the New York Civil Liberties Union. “Reminding people of their greatest fears is a disappointing tactic, meant to distract from the fact that this product is discriminatory, unethical and not secure.”” — Davey Alba, Reporter Learn More from The New York Times >
What we’re reading.
1/ Actors in the porn industry worry that AI-generated pornography will replace the need for human participation. Learn More from The Guardian >
2/ Attendance at a top AI conference in New York plummets as fears of contracting Coronavirus rise. Learn More from WIRED >
3/ Researchers use AI to predict adverse reactions that can happen when a patient takes multiple prescription drugs — potentially paving the way to save the lives of tens of thousands fo people in the US every year. Learn More from MIT Technology Review >
4/ Law enforcements agents use facial recognition technology to identify child victims of sex abuse and notify them when arrests have been made. Learn More from The New York Times >
5/ A new AI algorithm is able to understand which medical conditions cause certain symptoms, ushering us into a new age of disease diagnosis. Learn More from MIT Technology Review >
6/ If we define creativity as the ability to search for and combine information, it’s possible that machines could “rival” human creativity. Learn More from FastCompany >
7/ Should we would hold algorithms responsible for the moral implications of their outcomes?. Learn More from The Wall Street Journal >
Links from the community.
“Manifold: A Model-Agnostic Visual Debugging Tool for Machine Learning at Uber” submitted by Samiur Rahman (@samiur1204). Learn More from Uber >
“Quotes generated by machine learning” submitted by Avi Eisenberger (@aeisenberger). Learn More from Machine Wisdom >
“The first time I tried coding I built an AI model…” by Anna Gross. Learn More from Noteworthy >
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