Awesome, not awesome.

#Awesome
“Computers were as good or better than doctors at detecting tiny lung cancers on CT scans, in a study by researchers from Google and several medical centers…[b]y feeding huge amounts of data from medical imaging into systems called artificial neural networks, researchers can train computers to recognize patterns linked to a specific condition, like pneumonia, cancer or a wrist fracture that would be hard for a person to see.” — Denise Grady, Science Reporter Learn More from The New York Times >

#Not Awesome
“Beyond its use by repressive regimes, AI can directly interfere with human rights in democratic and open societies. The infinite collection of personal data by AI systems for micro-ad targeting limits the rights of privacy. AI-enabled online content monitoring impedes freedom of expression and opinion, as access to and the sharing of information by users is controlled in opaque and inscrutable ways. Vast AI-powered disinformation campaigns — from troll bots to deepfakes (altered video clips) — threaten societies’ access to accurate information, can disrupt elections and erode social cohesion.” — Kyle Matthews & Alexandrine Royer Learn More from CBC >

What we’re reading.

1/ Facebook’s algorithms help distribute a manipulated video of Speaker Nancy Pelosi that make it seem as if she’s slurring her words. Learn More from The New York Times >

2/ A coalition of countries comes together to develop five democratic principles that will guide the development of artificial intelligence — the first among them is that “AI should benefit people and the planet by driving inclusive growth, sustainable development and well-being.” Learn More from MIT Technology Review >

3/As long as we struggle to define intelligence, we won’t know if a superhuman AI has been created. Learn More from Cerebra Lab >

4/ Leaders in the autonomous vehicles industry fear that not enough thought is being given to the impact the technology will have on public transportation systems and disabled people. Learn More from Axios >

5/ It’s too late to stop the proliferation of facial recognition software, but we can all demand that our governments and companies deploy it within ethical guidelines. Learn More from WIRED >

6/ As machines start to do more tasks that were once reserved for humans, like book restaurant reservations, it will become harder to separate the fake from the real. Learn More from The New York Times >

7/ Fear mongering about AI could actually serve a useful purpose — getting companies think about downsides before they play out in reality. Learn More from TechCrunch >

Links from the community.

“Using Machine Learning To Identify High-Risk Surgical Patients” by Kristin Corey (@kristoncorey). Learn More from Science Trends >

“Video Object Detection with RetinaNet” by Alexander Li. Learn More from Noteworthy >

“Could a Robot Ever Be Conscious?” by Phillip Shirvington. Learn More from Noteworthy >

“You Can Blend Apache Spark And Tensorflow To Build Potential Deep Learning Solutions
“ by Satyajit Maitra. Learn More from Noteworthy >

“Using Machine Learning to Solve Real-World Problems” by Jeff Daniel. Learn More from Noteworthy >

“Artificial Intelligence, far from GAFA” by Mamadou Diagne. Learn More from Noteworthy >

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AI Makes it Harder to Understand What’s Real was originally published in Machine Learnings on Medium, where people are continuing the conversation by highlighting and responding to this story.

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