According to recent studies on mental health, one in ten children is affected by a serious psychological problem, with future projections showing an alarming increase in this trend. That’s why we have taken the initiative to explore new models of engagement and investigate the potential use of empathy applied to human-machine interaction. In mental health everyone is different, so it is important that every voice is heard.
During a 5 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, acting 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 and collective caretaking of how one feels.
Research & Insights
“I’ve been amazed how working with Method, the team has been able to move so quickly from learning about our professional field to being able to contribute so perceptively as if they had been working with us for years.”
Making children the experts
Can we make an empathetic AI?
Awards for FINE
Fast Company’s World Changing Ideas, Nominee: App Category
Let’s work together
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