Presence Signaling Architecture®
The future requires human signal to overcome artificial noise. The machine must not win. Equip yourself with frameworks to navigate institutions disrupted by artificial intelligence.
This is for you if —
The Platform
Founded by Dr. Tuboise Floyd
Editor in Chief, The AI Governance Record | Host, The AI Governance Briefing | Chief Sensemaking Officer | Founder, Human Signal | TAIMScore™ Certified Assessor
Human Signal is an independent research and media platform dedicated to artificial intelligence governance and institutional risk.
We reverse engineer institutional failures and build frameworks operators can actually use — when organizations treat artificial intelligence as a procurement problem instead of a systems design problem.
This is a presence-first architecture. We guide how you build earned trust and restore visibility in systems designed for observation rather than recognition.
Canonical IP · Human Signal
The intellectual architecture of Human Signal. Each framework is a standalone diagnostic or operational tool for institutional operators governing AI.
Analysis
Two levels of institutional AI governance failure. Structural absence. Structural insufficiency. Permitted is not the same as admissible.
Read the framework →Diagnostic
Governance As a Structural Problem. Most institutions do not have a governance problem because they lack the right software. They have a governance problem because they never built the right structure.
Read the diagnostic →Thesis
Institutions deploying AI fail not because of underperforming models, but because of broken governance structures. The primary risk is never a bad model — it is governance failure.
Read the thesis →Practice
The algorithm is rewriting your source code. Cognitive defense for operators drowning in vendor hype and feed-induced source amnesia. Four interventions to restore your signal.
Read the brief →Framework
Four physical constraints every AI strategy must address: Lithography, Energy, Arbitrage, Cooling. If your strategy does not address all four, you are leaking value.
Read the protocol →Architecture
Presence Signaling Architecture and AI as Presence Interface — frameworks for restoring human visibility in systems designed to observe, not listen.
Read the architecture →Signal Validation
An emergent lexicon entry from the PSA® runtime environment. The fusion of a scored identity-coded signal and a prompt, resulting in a presence-optimized query.
Read the lexicon →Live Diagnostic · GASP™
5 questions. Instant GASP™ structural diagnosis. No login required. Find out if your institution has the governance structure to govern AI accountably — right now.
Run the diagnostic →Open Access · Human Signal Frameworks
Framework documentation is publicly available for research, education, and non-commercial use. PDF copies and source documents are hosted on GitHub. Licensing terms are included in each repository.
Free Study Tool
GOVERN · MAP · MEASURE · MANAGE. Every control from the Trusted AI Model — formatted as interactive flashcards. Study before the workshop. Drill the framework. Test your recall.
Launch Flashcards →19
GOVERN
20
MAP
18
MEASURE
15
MANAGE
TAIMScore™ In Action
Human Signal applies the TAIMScore™ framework to real AI failures on the podcast. These Failure Files™ show exactly what you'll practice in the workshop.
Tap any card to read the full breakdown
Accountability & Training
Microsoft spent $0 on adversarial input controls before releasing TAY in March 2016. Within 16 hours it published racist propaganda. GOVERN 2.2 failure: no accountability structure for what happens when your AI learns from the internet without guardrails. Four TAIM domains failed simultaneously — no testing protocol, no kill-switch SLA, no non-AI fallback, no deactivation authority.
Join the Next Session →Privacy Risk & Socio-Technical Design
A 157-page class action alleged ChatGPT was trained on private data without consent — including children's data and PII. FTC investigation opened. Every org that deployed ChatGPT in a regulated environment without asking "what data was this model trained on?" inherited this risk on sign-up. MAP 1.6 + MEASURE 2.10: privacy risk existed but was never formally scored. Active exposure under HIPAA, TRAIGA, EU AI Act simultaneously.
Join the Next Session →Bias, Fairness & Contextual Deployment
Three Black men. Three wrongful arrests. Facial recognition never validated for the population it was used to identify. Detroit Police acknowledged a 96% misidentification rate when used in isolation. Detroit settled for $300,000. MAP 1.2: no demographic performance analysis documented. MEASURE 2.11: fairness and bias evaluated after arrests made national news — not before deployment.
Join the Next Session →Feedback Systems & Context-Appropriate AI Use
Vanderbilt sent students a post-mass-shooting condolence email. At the bottom: "Paraphrase from OpenAI's ChatGPT." National backlash. Public apology. Permanent reputational damage. MEASURE 3.3 failure: no feedback mechanism existed to flag high-stakes communication contexts where AI output must be reviewed, escalated, or prohibited. The governance layer that asks "must a human own these words?" did not exist.
Join the Next Session →12 Incidents · 12 TAIM Controls
Every failure is a practice scenario.
See the full set — scored, sourced, and mapped.
The AI Governance Briefing
A forensic autopsy of a real-world AI governance failure. New case every month.
Tap the card to read the full breakdown
Chatbot Governance & Accountability Structure
Air Canada's chatbot told a grieving customer he could apply for a bereavement fare retroactively within 90 days. That policy didn't exist. When he submitted the claim, Air Canada denied it — and argued the chatbot was a separate legal entity not binding on the airline. The BC Civil Resolution Tribunal rejected that defense and awarded the customer $812. The precedent: you own what your AI says. GOVERN 1.1 — no accountability structure for AI policy representations. MANAGE 4.1 — no monitoring to detect hallucinated policy claims before they reached customers.
Read Full Analysis →Now Broadcasting
A Human Signal Production
Rapid-fire episodes on AI governance, institutional risk, and finding your human value when the machine noise gets loud.
Dr. Tuboise Floyd sits down with Dr. Michele A. Williams to explore how AI is reshaping — and challenging — digital accessibility. What does meaningful inclusion look like when institutions race to automate? And who gets left behind when the signal isn't designed for everyone?
AI Governance
Finding your human value when AI rewrites the rules. Why "leverage" is replacing judgment — and how to protect your signal.
BAR Method
Background, Action, Result as a personal reinvention framework. Run the ultimate self-interview and rewire your next move.
Identity
Five steps to break autopilot, claim solitude, and find purpose through serving others. A framework for genuine growth.
Career
How market signals shape career opportunities. Stand out by amplifying your story at the right moment, in the right system.
TAIMScore™ — the Trusted AI Model Score — is an enterprise AI maturity and risk assessment framework developed by HISPI Project Cerebellum. It gives auditors, executives, and compliance professionals a structured methodology to score, audit, and manage an organization's AI readiness. Human Signal is an authorized affiliate partner promoting the official TAIMScore™ Assessor Workshop — virtual, hands-on, 6 CPEs.
Dr. Tuboise Floyd is the founder of Human Signal and an independent AI governance researcher. He developed the LEAC Protocol and the Noise Discipline Framework — tools for restoring human visibility and institutional signal in automated, high-noise environments. He hosts the Human Signal podcast and leads the quarterly Town Hall for institutional operators navigating AI disruption. Read his full mission.
The LEAC Protocol is a macro diagnostic tool built from forensic market analysis — not a governance framework. It identifies the physical infrastructure constraints that determine which AI companies survive the infrastructure war and where value erodes.
The market has split in two. While the consumption economy ghosts high-value talent, the investment economy is quietly hardening the physical layer. The four components represent the binding constraints:
If your AI strategy does not address all four constraints, you are leaking value. Companies that solve these physical infrastructure challenges will outlast those focused purely on algorithmic improvements.
Human Signal with Dr. Tuboise Floyd is an AI governance podcast for the Builder Class — leaders, auditors, and institutional operators navigating AI-disrupted systems. Dr. Floyd examines the physics of institutional failure, the limits of automation, and what it takes to govern the machine. Available on Spotify and Apple Podcasts.
Human Signal offers three underwriting tiers — from per-episode Signal Drop Sponsorships ($1,500) to full Seasonal Signal Partnerships ($6,000/quarter) and the Signal Brief Presenting Partner package ($12,000/quarter), which includes named sponsorship of the Quarterly Town Hall and direct introductions to Dr. Floyd's institutional network. See full tier details and inquire.
Wednesday, May 14, 2026 · 2–3 PM ET · Virtual via Zoom
After this hour, you'll know —
The specific governance failures that expose your organization to fiduciary liability right now
How agentic AI systems create accountability gaps your current policies don't cover
What institutional operators are actually doing — not what vendors are selling
Your specific question, answered on tape, by six practitioners with no scripts
Session Structure · 60 min
Intro & framing — the governance reality check
Panel discussion — agentic risk, fiduciary duty, accountability debt
Audience microphone — your questions, live, no filter
Close + what's next
Pre-Sale Pricing
Increases to $75 on May 1
Secure checkout via Stripe · Can't attend live? You still get the recording.
Hear the room before you buy a seat
Dr. Floyd and the panel have been building this conversation for months on the podcast. The format is real. The questions are hard. The answers are unscripted.
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