The challenges of using machine learning to identify gender in images
This essay on the lessons we learned about deep learning systems and gender recognition is one part of a three-part examination of issues relating to machine vision technology.
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This essay on the lessons we learned about deep learning systems and gender recognition is one part of a three-part examination of issues relating to machine vision technology.
The ability of governments and law enforcement agencies to monitor the public using facial recognition was once the province of dystopian science fiction. But modern technology is increasingly bringing versions of these scenarios to life.
A computer can be trained to predict whether an image shows a man or a woman. Can you identify which parts of the face are most essential to the computer’s decision?
People across 26 countries say it is likely their country will be targeted by a cyberattack, but they are divided over whether their nation is well prepared to handle one.
Roughly six-in-ten U.S. teens have been bullied or harassed online. Senior Researcher Monica Anderson discusses the methods and meaning behind the data.
Stories from experts about the impact of digital life, from @pewresearch and @ImagineInternet.
While many technology experts and scholars have concerns about the social, political and economic fallout from the spread of digital activities, they also tend to report that their own experience of digital life has been positive.
A majority of Republicans say technology firms support the views of liberals over conservatives and that social media platforms censor political viewpoints. Still, Americans tend to feel that these firms benefit them and – to a lesser degree – society.
Here are some key findings about Americans’ views of government information-gathering and surveillance, drawn from Pew Research Center surveys since the NSA revelations:
Predictions from experts about the future of well-being in a tech-saturated world, from @pewresearch and @ImagineInternet.
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