It’s pretty obvious that remote or hybrid workers are more common nowadays than before 2019. Close to 70% of full-time workers are working from home and since 2020, people have been meeting by video calls 50% more as well. Like everything, the technology industry has been inspired to create ways to make this situation easier for everyone. Now that it is more necessary and common for employers and employees to use technology in order to communicate like video meetings, emotion-recognition software is being created to help digitally gauge a person’s emotions because it may not always be clear through a screen. Uniphore, a software company, was created with just this in mind.
“Uniphore’s software incorporates computer vision, speech recognition, natural-language processing and emotion AI to pick up on the behavioral cues associated with someone’s tone of voice, eye and facial movements or other non-verbal body language, then analyzes that data to assess their emotional attitude.”
There is a lot of controversy around this kind of technology in the scientific field because there are pros and cons to how this data is acquired in order to work. Let us help kind of break down how this technology operates. Whenever you use an app that has a camera or filters, an AI is scanning your facial features to fit the parameters of the screen and filter. Some people think this is interesting and entertaining but this can feel invasive to others so the idea that a widely used video meeting platform such as Zoom may be collecting data in this way can tend to make users feel some type of way.
“Last week, Protocol reported that Zoom is planning to add emotion-recognition software to its product, for now focused on helping sales teams.”
I bet you’re wondering why you should care about this software, besides the fact that Zoom might be using your data. If you are a telemarketer or have called a customer service number, this tech is definitely affecting you. The original goal behind this tech and what has been tested so far is to assist salespeople in determining a customer’s emotional state when speaking to them in order to sell to them more effectively and positively. It can also help measure what parts of a sales call need work and which parts customers are interested in. But like when you tell Alexa or Siri to play a song and it tells you the weather forecast instead, technology doesn’t always get it right all the time and that has been found to be true with this emotion recognition software as well.
“Job applicants are being judged unfairly because their facial expressions or vocal tones don’t match those of employees; students are being flagged at school because their faces seem angry. Researchers have also shown that facial-recognition software interprets Black faces as having more negative emotions than white faces do.”
This technology is still in the early stages since it is only 2 years post Covid shutdowns of 2019 so it obviously still has a long way to go and like all new tech, it will continue to adapt with the ever changing world.
by: Vannesa Bratton | April 1, 2022
Sources:
Crawford, Kate. “Time to Regulate AI That Interprets Human Emotions.” Nature News, Nature Publishing Group, 6 Apr. 2021, https://www.nature.com/articles/d41586-021-00868-5.
Kaye, Kate. “Companies Are Using AI to Monitor Your Mood during Sales Calls. Zoom Might Be next.” Protocol, Protocol, 13 Apr. 2022, https://www.protocol.com/enterprise/emotion-ai-sales-virtual-zoom.
McCarthy, Dan. “Zoom Could Soon Add Controversial Emotion Recognition Features to Its Platform.” Emerging Tech Brew, 19 Apr. 2022, https://www.emergingtechbrew.com/stories/2022/04/19/zoom-could-soon-add-controversial-emotion-recognition-features-to-its-platform?utm_campaign=etb&utm_medium=newsletter&utm_source=morning_brew.
“Statistics on Remote Workers That Will Surprise You (2022).” Apollo Technical LLC, Apollo Technical Engineered Talent Solutions, 16 Jan. 2022, https://www.apollotechnical.com/statistics-on-remote-workers/#:~:text=During%20COVID%2D19%20close%20to,to%20work%20from%20home%20permanently.
