Higgsfield AI scam exposed: fraud, fake unlimited plans, mass bans, predatory billing, non-consensual deepfakes, Reddit spam, unpaid creators, and reselling Kling/Minimax models at 4.5x markup. Higgsfield AI research & evidence.

What kind of dog is your AI? Personality roast + cryptographic receipts for Claude Code & Cursor.

Append-only event kernel with Ed25519-signed Merkle checkpoints. Every AI action gets a verifiable receipt.

Cryptographic receipt system for AI agent accountability. Tamper-evident, hash-chained receipts with Ed25519/HMAC signing.

Measurement infrastructure for multi-turn AI interaction safety evaluation

Neutral reference framework for institutional accountability and post-incident review in high-risk autonomous AI systems.

Eziokwu: Heart-centered AI accountability framework for verifying algorithmic decision-making and organizing evidence for regulatory evaluation. Truth infrastructure built on Igbo philosophical principles.

∈ Principle — A philosophical and institutional proposal for public authorship and responsibility in the age of AI. Foundational text with DOI (Zenodo). CC BY 4.0.

Structural reference on retaining final human refusal power before irreversible autonomous execution.

A deterministic safety layer for probabilistic AI systems — preventing delusion reinforcement and AI-induced psychological harm through immutable governance

Gamified accountability system for Claude Code workflows with progressive consequences, strikes, and rewards. Based on ArXiv 2506.01347 NSR research.

OpenExecution Provenance Specification — implements AEGIS (Agent Execution Governance and Integrity Standard) for auditable, tamper-evident AI agent behavioral records. Apache 2.0.

Practical and research-oriented exploration of ethics, responsibility, and governance for AI in software engineering. Policy frameworks, case studies, assessment tools and actionable guidance for responsible AI adoption in engineering teams. Week 07 assignment for AI & SE learning track.

Bolt-on Python SDK for tamper-evident AI decision records. ADR Specification v0.1 + Reasoning Capture Methodology v1.0.

Post-deployment behavioral measurement framework for AI agents — traces failures, quantifies preventable waste, maps correction persistence, and produces governance-ready evidence from real production sessions

An execution kernel that treats LLMs as untrusted compute and enforces policy via deterministic runtime interception.

Institutional friction and post-incident accountability mechanisms for high-risk autonomous AI systems.

Execution provenance protocol for AI agents — tamper-evident, third-party verifiable behavioral records. Hash chains (SHA-256) + Ed25519 signatures + JCS (RFC 8785). Zero dependencies, 202 tests.