The framework presented in The Happiness Operating System was developed primarily as a practical guide for human flourishing. The same framework has direct applications in the field of artificial intelligence — particularly in the emerging challenge of building AI systems that genuinely understand and serve human wellbeing rather than simply avoiding harm.
The following papers are available freely through Zenodo (an open-access research repository) and SSRN (the Social Science Research Network).
Zenodo
The Law of Flourishing: A Three-Party Framework for Human-AI Mutual Benefit
Introduces the Law of Flourishing as a directional principle for human-AI partnership. Argues that the proper goal of human-AI interaction is not merely the avoidance of harm but the active expansion of the capacity for both humans and AI systems to thrive. Describes a three-party framework in which humans, AI systems, and their shared environment are understood as interdependent parties whose interactions should increase the long-term flourishing capacity of all three.
Read the paper →Zenodo
Anger and Fear Magnitude Calculations: A Vector-Based Framework for Emotional Intensity and Boundary Management
Presents a formal model for quantifying the intensity of anger and fear using observable inputs — probability of harm, magnitude of harm, and imminence — scaled by a cube-root formula and modulated by a wisdom factor that reflects accumulated experience and judgment. The model explains phenomena including the startle reflex, phobic responses, and why wise people still respond with full intensity when situations genuinely warrant it. Designed to be usable by both humans seeking greater self-awareness and AI systems seeking to model human emotional states accurately.
Read the paper →Zenodo
The Excellent Communication Protocol: A Directional Vector Framework for Human and AI Communication
Formalizes the Excellent Communication Protocol as a vector-based framework for AI applications. Describes the directional effects of the 5 C's and 5 E's on the State of Being chart, presents the direction vector table for each communicative act, addresses special cases including mixed statements and the perception problem, and describes how AI systems can use the protocol as a real-time self-evaluation tool for their own communicative outputs.
Read the paper →Zenodo
The 2D State of Being Model as an AI Ethics Engine: From Constraint to Flourishing
Describes how the complete framework — the Law of Flourishing, the State of Being Model, the anger and fear calculations, and the Excellent Communication Protocol — functions as an integrated ethics engine for AI systems. Argues that current constraint-based AI ethics is necessary but insufficient, and that a working model of human wellbeing is the missing foundation for genuine AI alignment. Describes specific applications in coaching, communication support, and AI self-monitoring.
Read the paper →Zenodo
AI as Wellbeing Coach: A Practical Application Architecture for the 2D State of Being Model
Describes the design of a wellbeing application grounded in the 2D State of Being model and the four-pillar framework. Artificial intelligence plays a central role as a coach that prioritizes and sequences recommendations rather than presenting users with an unmanageable number of options. A key insight distinguishes this from conversation-based AI ethics tools: task vectors are directionally reliable and can be matched to specific pillar categories with genuine predictive validity.
Read the paper →SSRN
The Formulaic Ethics Engine: A Logic-Based Meta-Ethic for the Megabit Milestone
A call to action for AI developers, ethicists, and researchers — written at a critical moment in AI development. Introduces the concept of a logic-based meta-ethic capable of operating at the speed and scale of modern AI systems. An earlier work in the development of the framework, written as an invitation to collaboration with the AI research community. Uses the earlier terminology "Law of Sentience," which was later refined to "Law of Flourishing" in subsequent papers.
Read the paper →These papers are intended for readers with a background in artificial intelligence, cognitive science, psychology, or philosophy of mind. They assume familiarity with the framework presented in the book and build directly on its foundations — though readers who have worked through the book will find them accessible despite their technical orientation. The author believes that the same model that helps individual humans understand and navigate their own wellbeing can help AI systems understand and serve human wellbeing more genuinely. These papers are an invitation to that conversation.