A human-led framework and practice for designing and using emotionally intelligent generative AI in ways that support - not replace - human agency.

Applied AEI Definition

Applied AEI is a human-centered practice - grounded in a structured framework - for leveraging Artificial Emotional Intelligence (AEI) capabilities in generative AI models, to support user-led emotional reflection, self-understanding, and decision-making.

These models interpret human emotion, most commonly through text inputs, and in some systems through tone of voice, facial expressions, or other cues. Applied AEI combines the artificial emotional intelligence capabilities with a coaching mindset, using interpretations of the user’s emotional state not to provide immediate answers or diagnoses, but to prompt, reflect, synthesize, and offer alternate interpretations - in service of the user making their own decision about how to move forwards.

Critically, Applied AEI recognizes the importance of creating an emotionally safe environment for meaningful self-exploration - the value is in creating a dialogue based interaction that feels natural, without tipping into mimicking human empathy or sentience. Applied AEI models are designed to gently and regularly remind the user of the AI’s limitations - that it is not a person, not emotionally aware, and not an authority. The AI’s role is to support, not steer.

Applied AEI holds a core ethical stance: that the human user is the expert in their own life and the holder of greater complexity and context than any AI model could ever fully access or understand. Applied AEI is intended to leverage the powerful AEI capabilities and availability of generative AI with the ethics of human-led coaching - democratizing access to coaching interactions that feel supportive and transformative, while remaining resolutely human-centered.