Unproductive meetings? AI will measure distractions and help manage success: computers



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Have you ever heard the phrase “this meeting could have been an email”? Microsoft already wants to save you from less meaningful and productive meetings. The company has patented a technology that classifies the quality of these professional meetings based on the facial expressions of those present, as well as their body language, number of participants and conditions (light, ambient temperature, time of day, etc.) In which the meeting took place.

According to GeekWire, the technology also takes into account if workers are distracted by their phones and their positions in the company, as the meeting organizer will be more likely to focus on another task after realizing that it is a waste of time. .

This system can be applied to face-to-face meetings, but also to virtual formats. At the moment, it still depends on a series of cameras and sensors that capture the participants.

Another feature of this technology is to predict the potential for a successful meeting. If the probability is low, other times, spaces or participants are suggested.

Note that it is still a conceptual technology, so it may never be part of a commercial product. However, it is important to point out that this appears to be another attempt by Microsoft to make companies’ productivity tangible by providing them with tools to act proactively. It should be remembered that the company presented, last October, a system for classifying workers’ productivity, a system that has been the subject of numerous criticisms to make surveillance and pressure on them practicable. Right now, to raise popularity ratings, the company must ensure that these tools not only do not pose a risk to user privacy, but do not allow managers to monitor their employees’ daily lives beyond what is reasonable.

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However, this technology is completely aligned with the corporate strategy, especially with regard to the integration of artificial intelligence systems into work tools. If it proves effective, this opens up the possibility of providing companies with a system that helps them plan jobs according to their productivity potential.

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