By examining the words people speak, how they express themselves, and occasionally even their typing speed or frequent pauses, conversational AI may determine their emotional state. It might also listen to how someone sounds or appears if voice or video is available to help it better comprehend their feelings. AI is trained utilizing many interactions that exhibit genuine emotions, including those from therapy, to react with compassion and empathy. This enables it to learn how to respond in polite and considerate ways—like repeating back what someone said, showing understanding, or gently asking useful questions—similar to what a real therapist might do. Some artificial intelligence systems also consult mental health professionals to guarantee their replies are supportive and polite.

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By using natural language processing, sentiment analysis, and vocal tone or facial expression analysis if available, the conversational AIs detect emotional states in a therapeutic setting or situation. The AI draws emotional cues: stress, sadness, frustration, or anxiety, among others using the user's diction, syntax, and tone of the sentence. After detecting an emotional state, AI responds empathically to the user by acknowledging the emotions of the user along with validating the user's experience, and promoting open communication. These are inclusive building blocks for trust and emotional safety which is crucial to therapeutic interactions.

Example: if I ask " I’ve been working so hard, but no one at work seems to notice. I feel invisible. " Then AI will respond " That sounds really frustrating. You're putting in so much effort, and it's completely understandable to feel unappreciated. I'm here to listen--do you want to talk more about what's been happening at work? "

AI, in this case, picks up on that frustration and invisibility, responding in empathetic terms with an open invitation to share more: the way a human therapist would react, along those lines.