While millions are working from home and attending several online meetings every week on platforms like Zoom, many have reported feeling unnaturally tired after using them. This “Zoom fatigue” is not caused merely by social interaction, scientists say, but a sudden disruption in the way that we communicate.
“We've evolved to get meaning out of a flick of the eye. Our species has survived because we can produce those signals in a way that's meaningful,” said Jeremy Bailenson, director of Stanford University’s Virtual Human Interaction Lab.
Factors such as delayed responses and monitoring one’s own face while speaking can also have an impact on the way we communicate.
Zoom has become the go-to platform for online webinars and meetings during the coronavirus pandemic, and its use is unlikely to decrease in the near future.
Support for broadband development data bill
Technology Policy Institute President Scott Wallsten has thrown his support behind a bill from Sen. Ed Markey, D-Mass., that would aim at increasing data on broadband development efforts.
Writing on the TPI Blog, Wallsten and Gregory Roston, Director of Public Policy at Stanford University, said that while efforts to increase broadband subsidies for low-income Americans were well-intentioned, they miss the underlying issue.
“Evidence from people’s behavior, as opposed to survey responses, has shown that the price of broadband service is not the primary factor that keeps many low-income households from subscribing,” they wrote.
To increase broadband access across the country, more data on consumer decision-making is necessary, and Markey’s proposal is the best way to collect such data, Wallsten and Roston wrote.
“We need to know more in order to create programs likely to encourage low-income households to subscribe,” they said.
AI healthcare applications accelerating amid the coronavirus
Artificial intelligence applications in medicine will likely become more widely adopted during the coronavirus pandemic, Axios reported.
With the US reaching 100,000 confirmed coronavirus cases on Wednesday, the speed and efficiency offered by AI learning technologies could make diagnosing and treating medical issues easier.
Increasingly common algorithms, like one developed by Mount Sinai Health System and NYU Langone Health, can predict whether coronavirus patients are likely to have difficulty recovering from the sickness.
However, the rapid rollout of such technologies and the lack of data surrounding them may restrict their usefulness.
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