Awesome, not awesome.
#Awesome
“An AI dying algorithm portends major changes for the field of palliative care… A team at Google, in collaboration with three academic medical centers, used input from more than 216,000 hospitalizations of 114,000 patients and nearly 47 billion data points to do a lot of [deep neural networks] predicting: whether a patient would die, length of stay, unexpected hospital readmission, and final discharge diagnoses were all predicted with a range of accuracy that was good and quite consistent among the hospitals that were studied. A German group used deep learning in more than 44,000 patients to predict hospital death, kidney failure, and bleeding complications after surgery with remarkable accuracy.” — Eric Topol, Physician-scientist Learn More from WIRED >
#Not Awesome
“…Researchers raise the prospect of “adversarial attacks” — manipulations that can change the behavior of A.I. systems using tiny pieces of digital data. By changing a few pixels on a lung scan, for instance, someone could fool an A.I. system into seeing an illness that is not really there, or not seeing one that is…the concern is… that doctors, hospitals and other organizations could manipulate the A.I. in billing or insurance software in an effort to maximize the money coming their way.” — Cade Metz and Craig S. Smith. Learn More from The New York Times >
What we’re reading.
1/ Facebook’s AI-powered content moderation system failed miserably to keep horrific videos of the far right terrorist attack that killed 50 people in New Zealand out of its users’ newsfeeds. Learn More from TechCrunch >
2/ Algorithmic investors trading against Warren Buffet’s investment strategies disprove one of the Oracle of Omaha’s oldest strategies. Learn More from Bloomberg >
3/ The NYPD is bolstering its policing efforts with an algorithm that some attorneys argue “could still reflect bias in department data and could be used in biased policing.” Learn More from FastCompany >
4/ A year ago Facebook announced changes to its News Feed algorithms that would decrease the amount of news seen by its users — but a new report shows that it actually “pushed up articles on divisive topics like abortion, religion, and guns.” Learn More from NiemanLab >
5/ Artificial intelligence is changing the way scientists discover knowledge, and could even one day be the source of breakthroughs in physics and mathematics that humans could not create on their own. Learn More from Quanta magazine >
6/ For AI to become deeply helpful to humans, researchers must look past the Tech industry and collaborate with experts in fields ranging from agriculture to government — and everything in between. Learn More from WIRED >
7/ The Tech giants are scrambling to stop AI-driven experiences on their platforms from spilling over into real-life violence. Learn More from Axios >
Links from the community.
“Remastering Star Trek: Deep Space Nine With Machine Learning” submitted by Avi Eisenberger (@aeisenberger). Learn More from Captrobau >
“Datasets for machine learning” submitted by Samiur Rahman (@samiur1204). Learn More from Dataset list >
“Machine Learning in the Browser using TensorFlow.js” by Suraj Parmar. Learn More from Noteworthy >
“Data Engineering 101” by Augustine Chang. Learn More from Noteworthy >
“Using Machine Learning to redact Personal Identifying Information” by Kenneth Cassel. Learn More from Noteworthy >
“Cascading Insights: Alibaba Advances Machine Reading for Online Question Answering” by Alibaba Tech. Learn More from Noteworthy >
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