Awesome, not awesome.
“…We’ve never directly detected or measured dark matter, but we know it exists because we can see its influence on the universe. Many of the movements of different stars and galaxies cannot be explained by the gravity exerted by the matter we can see…A team of researchers from ETH Zurich in Switzerland trained a neural network model (of the type often employed to analyze visual imagery) to look for subtle signs of weak gravitational lensing caused by dark matter. The model was trained by being fed simulated data that taught it what scientists typically look for when hunting for dark matter. The model ended up being 30% more accurate than human scientists at spotting and labeling potential signs of dark matter in images.” — Neel V. Patel, Science and Tech Journalist Learn More from MIT Technology Review >
“A new report from Data and Society raises doubts about automated solutions to deceptively altered videos, including machine learning-altered videos called deepfakes. Authors Britt Paris and Joan Donovan argue that deepfakes, while new, are part of a long history of media manipulation — one that requires both a social and a technical fix. Relying on AI could actually make things worse by concentrating more data and power in the hands of private corporations. The panic around deepfakes justifies quick technical solutions that don’t address structural inequality,” says Paris. “It’s a massive project, but we need to find solutions that are social as well as political so people without power aren’t left out of the equation.” — Zoe Schiffer, Writer Learn More from The Verge >
What we’re reading.
1/ A viral selfie-sharing apps uses machine learning to classify a prominent journalist as a few choice racial slurs. Learn More from The Guardian >
2/ Companies scapegoat algorithms when their employees make ignorant product decisions that discriminate against certain populations. Learn More from The Atlantic >
3/ OpenAI, the AI research lab, built a machine learning agent the played millions of hide and seek games — ultimately learning to cheat and win with ease. Learn More from TechCrunch >
4/ An MIT grade student creates an interesting machine learning tool that will help music produces sample dozens of tracks and combine ones that will lead to the best sounds. Learn More from MIT News >
5/ Seismologists turn to machine learning to predict massive earthquakes and potentially saves thousands of lives if not more. Learn More from Quanta Magazine >
6/ About 70% of the videos watched in YouTube are recommended to users by the company’s machine learning algorithm. Learn More from Penn Today >
7/ For all the progress machine learning has made in the field of drug discovery, one could argue that its progress will ultimately be capped — all because the data pharmaceutical giants produce is not tailored for ingestion by ML algorithms. Learn More from Fast Company >
Links from the community.
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Racial slurs hurled by a machine learning algorithm was originally published in Machine Learnings on Medium, where people are continuing the conversation by highlighting and responding to this story.