• Login
  • Register

Work for a Member company and need a Member Portal account? Register here with your company email address.

Post

Fast Company's 2025 World Changing Ideas Awards: Media Lab Honorees

 Fast Company 

Congratulations to all of the winners and honorees in Fast Company's 2025 World Changing Ideas Awards, including the Media Lab community members and projects listed  below.

Future You 

Pat Pataranutaporn, Pattie Maes, Kavin Winson, and Thanawit (Tae) Prasongpongchai have been selected as honorees in the Academic Excellence category.

From Fast Company:
A team including researchers from MIT, KBTG, UCLA, and Harvard has developed an AI-powered digital twin that serves as a model of users' future selves. The tool has so far reached over 52,000 users across more than 190 countries, giving people the opportunity to discuss their aspirations and potential futures with an AI version of themselves. Research so far has indicated that the AI system reduces people's anxiety and helps them feel more connected to their future selves, which can lead to better long-term planning, health, and academic performance. Since the system relies on AI interaction rather than human role-playing, it's set up for scalability, and researchers have tested its applicability to group therapy sessions at Harvard Medical School.


BuzzCam

Patrick Chwalek and Marie Kuronaga have been selected as honorees in the Technology Solutions category. 

From Fast Company:
The BuzzCam is a noninvasive ecological monitoring device that can identify bee species by their distinctive buzzes without disturbing the insects or their habitats. That, in turn, can help scientists and farmers understand what's happening with important pollinator species in particular areas. In March 2024, the BuzzCam team deployed nine of the devices in Argentina and Chile, capturing buzz recordings of two bee species as field workers noted simultaneous observations with a custom iOS app. The data has been published and made open source—and used to develop new machine learning systems to classify bee buzzes with high accuracy. The team plans to deploy the system in Patagonia and beyond to collect new information about the presence of various bee species.

Related Content