Earshot

Description: 

In the current system of aid, relief is distributed based on hypotheses and old knowledge. While most organizations collect data about disasters, they rarely collect data from people experiencing disasters directly. Earshot democratizes information for both those impacted by a natural disaster, and for the organizations and governments that serve them. At the center of the solution is an AI-driven chatbot named Quinn. 

 

Earshot’s Quinn uses a robust database that is built by text messages and phone calls from previous survivors to answer questions: How do I apply for a grant to repair my home? Which pharmacies nearby have the prescription I need? Does the local grocery store have bread? Earshot uses machine learning to convert this database into actionable insights for governments and other organizations to deliver better, faster, and more accurate aid. 

 

Earshot is a subscription-based non-profit organization, where aid organizations and governments receive actionable insights related to disaster relief efforts. End users of our chatbot would include anyone impacted by a disaster who is looking for information or has questions.

 

Winner of the 2020 Rotman Design Challenge. 

 

Designers:

Andrea Noble

Brendan Raftery

Yasmine Abuzeid 

Björg Flygenring Finnbogadittir

Selina Tedesco

Silvia Garuti