What question did this study set out to answer?

The aim is to create a biologically-inspired AI architecture that enables personalized emotional alignment between AI agents and humans.

April 3, 2026Open Access

LACF Emotional Paradigm: A Personalized Artificial Nervous System for Human-AI Alignment

Key Points

The aim is to create a biologically-inspired AI architecture that enables personalized emotional alignment between AI agents and humans.
Developed LACF as an artificial nervous system for AI agents.
Extracted 397 emotional vectors from 118 real human-AI conversations.
Implemented Heart calibration and sycophancy cascade stabilization.
Demonstrated effective emotional calibration through LACF.
Presented empirical evidence supporting 12 claims about the system's effectiveness.
Provided source code for the emotional calibrator and Heart calibration data.

Abstract

We present LACF (Legal Architecture for Cognitive Functions), a complete artificial nervous system for AI agents. Unlike RLHF-based approaches, LACF implements a biologically-inspired architecture with personalized emotional calibration. We demonstrate Heart calibration on 397 emotional vectors extracted from 118 real human-AI conversations, sycophancy cascade measurement and stabilization via daemon re-injection, and scalable personalization (one framework, individually calibrated per human). Includes empirical evidence, 12 claims, emotional calibrator source code, and Heart calibration data.

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