Rana el Kaliouby: What if computers could read our emotions?

Instant Genius - A podcast by Immediate media

Categories:

For many, the coronavirus pandemic and lockdown restrictions has isolated us from the people we love, reducing our social life to screens and Zoom meetings. But even with the added visual, communicating online still isn’t as straightforward as being in-person. It can feel like jokes fall flat when everyone has their microphone off, and the jittering of poor signal can make anyone’s face hard to read. But what if our computers could read and respond to our emotions? If the engagement of a virtual meeting could be shown on-screen to generate a buzz like the one of a live audience? That’s just one possibility of a future with emotionally intelligent machines. Researcher and CEO Rana el Kaliouby believes that by teaching computers to read facial expressions, they could detect early signs of Parkinson’s, prevent drivers from getting behind the wheel when tired, or help teachers design educational programmes that keep kids engaged. Rana speaks to us about making machines empathetic, being named by Forbes as one of America's top 50 women in tech, and how her research into human emotions has affected her personal life. Subscribe to the Science Focus Podcast on these services: Acast, iTunes, Stitcher, RSS, Overcast Read the full transcription This podcast was supported by brilliant.org, helping people build quantitative skills in maths, science, and computer science with fun and challenging interactive explorations. Listen to more episodes of the Science Focus Podcast: Jim Al-Khalili: Why AI is not the enemy Lisa Feldman Barrett: How emotions are made Aleks Krotoski: What happens to your data when you die? Jim Davies: How do you use your imagination? Caroline Criado Perez: Does data discriminate against women? Robert Elliott Smith: Are algorithms inherently biased? Hosted on Acast. See acast.com/privacy for more information. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Visit the podcast's native language site