Awesome, not awesome.
#Awesome
“Free will, from a neuroscience perspective, can look like quite quaint… using the fMRI to monitor brain activity and machine learning to analyze the neuroimages, the researchers were able to predict which pattern participants would choose up to 11 seconds before they consciously made the decision. And they were able to predict how vividly the participants would be able to envisage it.” — Sophia Chen, Science Writer Learn More from WIRED >
#Not Awesome
“Users do not need to look for videos of children to end up watching them. [YouTube’s algorithms] can lead them there through a progression of recommendations. So a user who watches erotic videos might be recommended videos of women who become conspicuously younger, and then women who pose provocatively in children’s clothes. Eventually, some users might be presented with videos of girls as young as 5 or 6 wearing bathing suits, or getting dressed or doing a split. On its own, each video might be perfectly innocent, a home movie, say, made by a child. Any revealing frames are fleeting and appear accidental. But, grouped together, their shared features become unmistakable.” — Max Fisher and Amanda Taub, Writers Learn More from The New York Times >
What we’re reading.
1/ YouTube’s recommendation was built to keep people on the site longer so they could be shown more ads, and it wound up steering visitors towards extreme content. Learn More from The New York Times >
2/ A new artificially intelligence prosthetic leg is designed to respond to the thoughts of the person wearing it. Learn More from Quartz >
3/ Artificial intelligence researchers learn that the process of training an AI model can be incredibly hard on the environment, emitting more than 626,000 pounds of carbon dioxide. Learn More from MIT Technology Review >
4/ Artificial intelligence systems must be designed with the goal of preserving human agency, helping people to feel empowered by technology rather than undercut. Learn More from Wharton >
5/ Researchers at Stanford create an algorithm that lets people edit videos as if they were typing a sentence — rewriting one spoken word at a time. Learn More from Stanford >
6/ MIT researchers create an algorithm that builds an image of someone’s face based on a short audio clip of their voice. Learn More from Fast Company >
7/ AI is used to prevent heartache, spotting and removing fake accounts on dating apps before a real user is met with disappointment. Learn More from BBC >
Links from the community.
“The Importance of Predictive Maintenance: Using AI to Increase Operational Efficiency” by Jason Meil. Learn More from Noteworthy >
“Handwriting Recognition Sdk- Part 1” by Ganesh Krishnan. Learn More from Noteworthy >
“Introducing Google Research Football: A Novel Reinforcement Learning Environment” submitted by Samiur Rahman (@samiur1204). Learn More from Google AI >
“Modeling the unseen” submitted by Avi Eisenberger (@aeisenberger). Learn More from Instacart >
🤖First time reading Machine Learnings? Sign up to get an early version of the newsletter next Sunday evening. Get the newsletter >
Algorithms and extremism was originally published in Machine Learnings on Medium, where people are continuing the conversation by highlighting and responding to this story.
Leave a Reply