You can schedule a video meeting directly from the Calendar screen in Teams. When you go to create a new meeting, you’ll have the option of inviting an entire Office 365 Group or individual team members. The Teams Scheduling Assistant lets you quickly check to see when attendees are free. Once you click Send, attendees will receive a notification in Teams as well as an email alert.
When you join a Meeting, you’ll be able to chat via video with the other attendees. But Teams Meetings is more than just a replacement for Skype. It includes added features such as automatic captions, a background blur effect, screen sharing, whiteboard sharing, and even the ability to record calls. Plus, Teams gives you the ability to invite up to 1,000 attendees to a standard meeting, making it a great option for even the largest organizations.
Article by: Dave Bollard – Head of Marketing | 801-436-6636Apple and Google’s common coronavirus contact tracing solution for smartphones continued to attract a lot of attention and debate over the course of the past week, and understandably so. It’s an unprecedented partnership between the world’s dominant smartphone operating system makers, but people are worried about privacy, and the notion that whatever tracking tool made in the name of coronavirus will outlive the crisis. But debate over Apple and Google’s contact tracing solution seems to have opened up an old argument between people who see a tech solution for every problem and those who say tech can’t solve all our problems. Those debates certainly carry over to the kind of AI being deployed right now, and the important question of when a company should ship or shelve a coronavirus solution.
A lot of AI is being deployed in the pandemic to save lives and someday soon help us resume daily lives, much of which you’ve been able to read about here. But they aren’t all winners.
In February, a robotics company sent its service robot to Times Square in New York for passerbys to answer questions to help them understand if they had coronavirus, but the experience relied on a touchscreen. Given how bad things are in New York City today, that seems pretty irresponsible.
AI is also being used in more productive ways to understand how coronavirus and social isolation are impacting people’s psychological health and well-being. Some AI, like a flu model from Delphi Group at Carnegie Mellon University, is being repurposed to forecast coronavirus models for the United States. An MIT model out this week suggests the effectiveness of social distancing and potential of an “explosion” in cases if those measures were relaxed today.
Of course, also present in this environment is opportunism from startups anxious to remain relevant, raise funding, or attract publicity at a time when much economic activity at a virtual standstill.
Innovation in a crisis can lead to outcomes that better human lives, or distract from priorities like testing, personal protective equipment, and protecting health care workers and the most vulnerable among us.
Some initiatives seem almost outlandish in their ambition, or, however promising, unable to join the fight. One project straddling that chasm between innovation and what can join the fight soon is Coughs Against COVID.
Cough Against COVID, a project by Wadhwani AI in partnership with the Bill and Melinda Gates Foundation and Stanford University, launched this week. The people behind it collect audio recordings of coughs by people who have confirmed cases of COVID-19. Online submissions for people quarantined at home must be accompanied by a photo of a diagnosis from a doctor. To spur additional research, all data sets collected will be made available in an anonymized, open access data set. In addition to a data collection website, Johns Hopkins University doctors are collecting data directly from patients at a hospital in India.
The hope is the voice recording data can power AI for screening apps being made by public health officials and create an additional diagnosis signal that doesn’t exist today. The project was inspired in part by Global Good’s work around tuberculosis identification in Madagascar with sound, and the work of Massachusetts’ FluSense, which uses cough sounds for health forecasting.
Jigar Doshi is senior researcher at Wadhwani AI, a nonprofit in Mumbai, India. Before moving back to India 3 months ago, Doshi headed machine learning efforts at computer vision startup CrowdAI, a company that worked with Facebook AI Research on multiple projects to assess damage after a natural disaster in order to help government or humanitarian organizations assess need.
Doshi admits he doesn’t know if Cough Against COVID will work, or how much data from coronavirus cases they’ll need to make a robust and accurate model, because COVID-19 is a novel disease. But an additional way to detect it could be helpful in parts of the world where hospitals, health professionals, or diagnostic testing are in short supply.
“It’s sort of a moonshot idea where it may work, and if it works it would really help. We don’t know if it will work, but the only way to find out at this point is to collect the data, do our best modeling,” he told VentureBeat. “This is all centered on limited testing ability, especially as we move away from western countries.”
When we asked what he’d say to people dismissive of the Cough Against COVID as a kind of techno-solutionism, Doshi said “This is one of those things where generally some degree of skepticism towards technical people from their high horse, castle, privilege, whatever you want to call it coming down to help, generally is good.”
Doshi continued to highlight the importance of working with medical professionals to keep things grounded and said the project is only asking COVID-19 patients with mild cases for five minutes of their time to find out if it’s possible.
Charles Onu is founder of Ubenwa, a company using AI to detect birth asphyxia in the sound of crying newborn babies. He sees a lot of merit in work like Cough Against COVID and called it a valid and intriguing venture for a respiratory disease. Onu said he sees promise from research published in June 2019 that demonstrated the ability to recognize and distinguish between the sound of respiratory diseases like bronchitis, asthma, and pneumonia with 80-90% accuracy.
With Ubenwa clinical trials in hospitals on hold due to the crisis, Onu, who is based in Montreal, said Ubenwa is in early talks with Canadian government officials on COVID-19 diagnostics with sound. Onu said he generally agrees with the idea of continuing progress toward experimental efforts, particularly as a way to help in areas where testing and resources are limited.
“One side is making it possible in Canada or the U.S., but also in my village in Nigeria and many places where they may have to go on a very long trip to take a test, so this could definitely close that gap,” Onu said.
Like Doshi, Onu thinks companies and developers deploying AI solutions right now should discuss matters with experts.
“I really hope that at the end of the day, people do whatever you like, but at the deploying, you have a gating mechanism with the public health system to make sure that they’re not spitting out fancy things that don’t solve the problem,” he told VentureBeat.
These are unprecedented times, and what’s needed from moment to the next can change. For example, a month ago, public health officials told people they don’t need to wear face masks unless they’re sick or taking care of someone who’s sick. Now the CDC and others suggest people wear them whenever they’re outdoors and near others.
So when should you ship or shelve a coronavirus-related AI solution? Some of the principles to follow seem similar to ethics principles: speak with stakeholders, and consider societal well-being and the potential impact. The decision should also depend upon whether the tech can deliver immediate results, but what’s considered best might change depending on testing and health care resources.
Some solutions and the companies peddling them, as a cryptographer advising the UK government about contact tracing apps put it, may serve best by just staying out of the way.
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Thanks for reading,
Khari Johnson
Senior AI Staff Writer