According to recent studies on mental health, 1 in 10 children is affected by a serious psychological problem, with future projections showing an alarming increase in this trend. That’s why Method took the initiative to explore new models of engagement and investigate the potential use of empathy applied to human-machine interaction.
During a five-month deep dive, we gained first-hand insight into non-intrusive mechanisms for the prevention of depression in childhood and adolescence, collaborating with key experts in the field, children, and parents through an open and co-creative process.
By bringing together design thinking, artificial intelligence, and the principles of crowdsourcing, FINE (Feeling Insecure, Negative, Emotional) enables a digital friend to react empathetically to a child’s emotional state.
A machine learning “empathetic” model has been trained to read and react to emotions appropriately, with a corresponding family hub displaying the child’s and family member’s collective mood over time. The model acts as a central trigger to the habit-forming routine of talking about emotions at home and encouraging the kind of positive behavior change that leads to a preventative, collective caretaking of how one feels.
FINE was a finalist for Fast Company’s Innovation by Design in the Health category and a nominee for Fast Company’s World Changing Ideas.
