Emotional Awareness for AI

Emotionally aware, privacy-first AI for care and human-facing systems.


SECE Framework

Core model | Structured Emotional Cognitive Engine.

SECE Framework

The Structured Emotional Cognitive Engine (SECE) is a conceptual model for designing emotionally aware, ethically aligned AI systems for long-term human interaction.

SECE framework diagram A hub-and-spoke diagram showing SECE in the center with five connected principles: emotional state awareness, relational continuity, local memory, context-sensitive behavior, and ethical guardrails. SECE framework A simple map of the project’s core operating principles. SECE Structured Emotional Cognitive Engine Emotional state awareness Meaning is shaped by feeling, vulnerability, and tone. Relational continuity Trust grows through stable interaction across time. Local memory Sensitive context remains private and controlled. Context-sensitive behavior Responses adapt to user state, setting, and risk. Ethical guardrails Dignity, safety, and human oversight stay central.

Core principles

  • emotional state awareness | systems should account for emotional context, not only literal content
  • relational continuity | long-term interaction needs memory, consistency, and stability
  • privacy-first local memory | sensitive histories should remain under local control whenever possible
  • context-sensitive behavior | responses should adapt to user state and circumstance
  • ethical guardrails | dignity, safety, and respect must be built into the operating logic

What this means in practice

  • assistive systems should not sound clinically correct but emotionally careless
  • continuity should reduce repetitive burden and improve trust over time
  • human handoff should be treated as a strength, not a failure mode
  • deployment choices matter as much as model capability in vulnerable settings

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