Public Policy Lab 2024
Watershed: A Wellbeing Quality Index (WQI) Tracker
How might verbal and visual signals become indicators of well-being? With the heightened exposure to doom-scrolling, there is an increase in the generation of neurotoxic noise.
However, as we move forward to 2039, there is an increased desire to cancel generated noise, and a longing for detoxification. In this project, we reinterpret and reframe noise from the form of verbal and visual signals not as a cause of addiction but as an indicator of our youth’s well-being.
Here, we integrate the power of language as a biometric tool in proactively safe-guarding mental health and well-being. Watershed is an AI model built to trace pathogenic rhetoric on social media as a predictor for self or community harm. Meant to be utilized by government agencies, it picks up publicly available signals, and analyzes them to inform current and future interventions, as well as promote inter-agency cooperation.
The team initially looked at multiple data points to further understand the current situation for well-being. Research for Watershed was conducted through interviews, desktop research, community workshops, and signal collection throughout the city. These were then synthesized into a policy-based intervention. In addition, the team also addressed data privacy, training the AI, and implementation challenges.