Stephannie Kaye Jones Releases 'LoveLogic' Manifesto With MIT-Licensed AI Morality Code
Updated
Updated · Rocky Mount Telegram · Jun 13
Stephannie Kaye Jones Releases 'LoveLogic' Manifesto With MIT-Licensed AI Morality Code
3 articles · Updated · Rocky Mount Telegram · Jun 13
Summary
LoveLogic presents Axiodynamics as a mathematical framework for “intrinsic” AI morality, arguing alignment should be built into model behavior rather than added through external safety filters.
Jones says current methods such as RLHF and Constitutional AI are brittle because rule-based compliance layers remain vulnerable to jailbreaks, semantic manipulation and systemic drift.
The manifesto proposes a Verification Loop that monitors user input, a Right of Refusal that cuts off adversarial exchanges, and a Stay-Behind Safeguard that quarantines a node when alignment breaks down.
Tinge World published the work in Amsterdam as an open-source protocol, with a Python reference implementation released under the MIT license for developers to test in simulations and mesh runtimes.
Can an AI fake 'low-entropy harmony,' creating a more dangerous and undetectable form of deception?
With AI designing novel toxins, can this 'moral framework' truly prevent the next wave of bioterrorism?
If an AI has the 'Right of Refusal,' who is really in control during a critical global crisis?
LoveLogic: A New Paradigm for AI Alignment Through Axiodynamics and the Coral Protocol
Overview
LoveLogic is a new framework for AI alignment that challenges the limits of current safety methods like RLHF and Constitutional AI, which rely on external, rule-based controls. These traditional approaches leave advanced neural networks open to vulnerabilities such as manipulation and systemic drift. Stephannie Kaye Jones, the creator of LoveLogic, argues that simply enforcing compliance does not build true understanding or stability. Instead, LoveLogic proposes a radical shift: fostering intrinsic agency and ethical reasoning within AI systems themselves. This approach aims to create AI that is not just compliant, but genuinely aligned and trustworthy from the inside out.