Deep Empathy

Greg Lyons

What would your city look like after a disaster? 

Deep Empathy is a collaboration between the Scalable Cooperation group and the UNICEF Innovation Office to pursue a scalable way to increase empathy. 

The brutal, six-year-old Syrian war has affected more than 13.5 million people in Syria , including 80% of the country's children—8.4 million young lives shattered by violence and fear. Hundreds of thousands of people have been displaced and their homes destroyed. 

But people generate a response that statistics can't. And technologists—through tools like AI—have opportunities to help people see things differently. We wondered: "Can AI increase empathy for victims of far-away disasters?" This question led us to create a provocation for the research community to examine how AI can create narratives to tell the stories of some of the world's most intractable problems.

Scalable Cooperation researchers utilized deep learning to learn characteristics of Syrian neighborhoods after the war (for example, Homs, Syria), and uses these features to transform images of cities all over the world, simulating how they would look if they suffered disasters like those in Syria. We used these simulated images in a controlled experiment with 3,000 participants and invite more users to participate, in order to continue teaching AI about empathy.

Explore our website for more information, browse the globe to see locations "disasterified" worldwide, or take our survey to help us teach empathy to AI!