#Awesome
“…A group of researchers in the United States and China has tested a potential remedy for all-too-human frailties: artificial intelligence. In a paper published on Monday in Nature Medicine, the scientists reported that they had built a system that automatically diagnoses common childhood conditions — from influenza to meningitis — after processing the patient’s symptoms, history, lab results and other clinical data. The system was highly accurate, the researchers said, and one day may assist doctors in diagnosing complex or rare conditions..” — Cade Metz, Technology Correspondent Learn More from The New York Times >
#Not Awesome
“Predictive policing algorithms are becoming common practice in cities across the US. Though lack of transparency makes exact statistics hard to pin down, PredPol, a leading vendor, boasts that it helps “protect” 1 in 33 Americans. The software is often touted as a way to help thinly stretched police departments make more efficient, data-driven decisions. But new research suggests it’s not just New Orleans that has trained these systems with “dirty data.” In a paper released today, to be published in the NYU Law Review, researchers at the AI Now Institute, a think tank that studies the social impact of artificial intelligence, found the problem to be pervasive among the jurisdictions it studied. This has significant implications for the efficacy of predictive policing and other algorithms used in the criminal justice system.” — Karen Hao, Reporter. Learn More from MIT Technology Review >
What we’re reading.
1/ Machine learning has become a fundamental technology at some of the largest Tech companies in the world, but it’s taking longer to spread to other industries than many predicted. Learn More from MIT Technology Review >
2/ President Trump signs an executive order this week to spur the development of AI technologies — it does not set aside any new funds for research or development. Learn More from The New York Times >
3/ The Defense Department publishes an AI strategy document of its own, making a point to curry favor with tech employees who’d be hesitant to work with the Pentagon. Learn More from Axios>
4/ Separating pricing algorithms collude without leaving the trace of “concerted action,” raising fears that consumers will be harmed by unfair pricing. Learn More from MIT Technology Review >
5/ Amazon Prime Video and Hulu’s algorithms recommend conspiracy theory videos to people that experts warn can “spread misinformation, and even encourage people to commit violence.” Learn More from Business Insider >
6/ An AI research lab builds an algorithm that creates convincing fake news, and they aren’t sharing their dataset with the public of out fear of it being abused. Learn More from Bloomberg >
7/ The California DMV requires that any company testing autonomous vehicles in the state reports the number of autonomous miles driven by the vehicles and the number of disengagements (when a human has to take the wheel) — Waymo is besting the competition on both measures. Learn More from The Atlantic >
Links from the community.
“Better Together: Humanity + Machine Learning” submitted by Avi Eisenberger (@aeisenberger). Learn More from YouTube >
“Audio AI: isolating vocals from stereo music using Convolutional Neural Networks” submitted by Samiur Rahman (@samiur1204). Learn More from Towards Data Science >
“The art of Machine Learning: my journey” by Thomas Okonkwo (@thomasokonkwo91). Learn More from Noteworthy >
“Designing the Best Model: Kaggle vs. Reality” by Zachary Angell (@zachary.james.angell). Learn More from Noteworthy >
“6 Jars — A unique way of looking at Machine Learning” by Swamy Sriharsha
(@SriharshaCSE). Learn More from Noteworthy >
“2 Weeks of Learning Artificial Intelligence at a Tech Start-up” by Aarohi Gupta (@aarohigupta2211). Learn More from Noteworthy >
“My favorite mind-blowing ML/AI breakthroughs” by Jerry Chi (@peacej). Learn More from Noteworthy >
“Single Machine Learning Engineer Takes Laptop on a Date for Valentine’s Day” by Daniel Bourke (@mrdbourke). Learn More from Noteworthy >
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