Identifying depression usually requires person-to-person interaction but new depression detecting AIs can help identify mental illness by identifying patterns in speech and word choice. Developed by researches at MIT, this new neural network engages users in an organic conversation and writing style. The nature of the AI allows users to engage in a more relaxed state and offers a diagnosis without any pretense of depression identification.
According to the AI's lead designer, Tuka Alhanai, the first hints towards a person's depression is "through their speech." The depression detecting AIs are being labeled as "context-free," simply because there are no constraints in the types of questions asked, or the responses needed for a diagnosis. The depression detecting AIs will hopefully be incredibly helpful to clinicians in diagnosing people with greater accuracy.