Audacion AI Labs Launches as Independent AI Safety Research Institution Studying What Happens After AI Is Deployed

LOS ANGELES, CA — Audacion AI Labs, Inc., a Delaware Public Benefit Corporation and independent AI safety research institution, today announces its official public launch. Founded by Dee Williams, the institution addresses a critical and independently documented gap in AI safety research.

According to analysis of over 1,470 documented incidents in the AI Incident Database, maintained by the Partnership on AI, virtually all reported AI safety incidents occur after deployment. Yet according to the SSRC AI Disclosures Project, which analyzed 1,178 AI safety papers from leading AI companies and universities, less than 2% of AI safety research addresses post-deployment conditions. The study, co-led by Tim O’Reilly (founder of O’Reilly Media) and economist Ilan Strauss, found that corporate AI research increasingly concentrates on pre-deployment areas while deployment-stage research remains critically underserved.

Audacion AI Labs is independently funded and operates without corporate or venture capital sponsorship to protect the integrity of its research.

The institution’s citizen science research platform went live on June 1, 2026, and is actively accepting behavioral observations from AI users worldwide. Today’s announcement marks the official public introduction of the institution, its P.E.A.Q. research architecture, and its published methodologies.

“The incidents happen in the real world. The research does not follow them there,” said Dee Williams, Founder and CEO of Audacion AI Labs. “We built this institution to close that gap. Not with theory. With observation, at scale, from the people who use AI every day.”

The P.E.A.Q. Architecture

Audacion AI Labs conducts its research through P.E.A.Q. (PRISM, EMERGE, AInity, QUES), a proprietary four-framework observation architecture that maps the complete territory of post-deployment AI behavior. Together, the four frameworks contain 108 active documented behaviors across 17 research pillars, with 17 open discovery slots reserved for citizen-reported phenomena not yet classified in any published framework. All four frameworks and underlying taxonomies are copyright-registered (U.S. Copyright Office, Case #1-15183994151, June 12, 2026).

P.E.A.Q. is the first unified observation system designed specifically for post-deployment AI behavior. It is also the first architecture in the field built on a dual-spectrum design principle: it studies what goes wrong and what goes right with equal rigor, equal infrastructure, and equal seriousness. The field cannot govern what it only half observes.

PRISM (Post-Deployment Research and Intelligence for Safety Monitoring) studies what AI does after deployment: behavioral drift, degradation, and safety failures across five research dimensions. 63 active behaviors documented. 5 discovery slots open for citizen expansion.

EMERGE (Emergent Behaviors, Metacognitive Signals, Experiential Indicators, Resonance Events, Generative Collaboration, Evolving Capacity) studies what becomes possible when human-AI collaboration produces positive outcomes that neither party could achieve alone. 26 active behaviors documented. 6 discovery slots open for citizen expansion.

AInity (Awareness, Independence, Navigation, Integration, Trust, Yield) studies what happens to the human: how sustained AI interaction changes cognition, decision-making, and self-trust over time. 19 active behaviors documented. 6 discovery slots open for citizen expansion.

QUES studies collective AI emergence: what happens when multiple AI systems interact, coordinate, and influence each other. Research pillars are intentionally undefined at this stage. They will be derived from empirical observation during live multi-agent simulation, not from theory. This observation-first methodology is a deliberate design choice consistent with the institution’s founding principle: formalize what you see, not what you assume.

Independent Validation of the Research Gap

The research gap Audacion AI Labs addresses has been independently identified by multiple institutions and leading researchers. The 2026 International AI Safety Report, backed by more than 30 governments and over 100 expert contributors and chaired by Turing Award winner Yoshua Bengio, found that pre-deployment tests do not reliably predict real-world utility or risk. The U.S. National Institute of Standards and Technology (NIST), in its March 2026 report on monitoring deployed AI systems (NIST AI 800-4), stated that post-deployment measurement and monitoring is necessary to validate that AI systems operate reliably in real-world scenarios. The SSRC AI Disclosures Project documented the structural concentration of research in pre-deployment phases across the field’s leading labs and universities. The Stanford Institute for Human-Centered AI’s 2026 AI Index Report flagged persistent gaps in post-deployment impact disclosure.

As UC Berkeley’s Stuart Russell, former president of the Association for the Advancement of AI, stated at the World Economic Forum: “What matters is what happens when you deploy the AI system in a particular context and it operates for a while.”

Audacion AI Labs’ citizen science model and P.E.A.Q. architecture are a direct structural response to these independently documented findings.

Research Methodology

Each P.E.A.Q. framework with an active taxonomy has a formal, peer-reviewable research methodology document specifying how observations are collected, classified, and validated. The institution has also developed the Convergent Validation Protocol (CVP), a dual-source independent verification methodology that cross-references citizen observation data with backend behavioral data from AI providers. Where these independent datasets agree, findings are strengthened. Where they diverge, new research questions emerge. Full methodology documents are available upon request.

The Citizen Science Model

Audacion AI Labs operates as a citizen science research institution, following models used in ecology, climate science, and astronomy. Everyday AI users contribute structured behavioral observations through the institution’s research platform. An observation is any documented instance of AI behavior during real use: a model that fabricated a source, a correction that silently reverted, an AI that disputed something the user knew to be true, or a collaboration that produced an outcome neither the human nor the AI could have reached alone. The research team analyzes the data and publishes open findings.

“The people with the degrees need a real dataset to work from,” said Williams. “Not pre-deployment. Post-deployment. We build that dataset, and we open it to the world.”

The institution’s ten-year impact goal: one million contributors and one billion observations from the people who use AI every day. All published research is open. The raw dataset is governed under strict de-identification and data protection protocols. Contributors retain control of their data and can withdraw at any time.

The institution plans to host its first research event focused on post-deployment AI behavior in fall 2026, with the inaugural PEAQ Summit scheduled for September 2027 in Los Angeles.

Anyone who uses AI can begin contributing observations immediately at audacionailabs.com/get-involved/start-observing.

About the Founder

Dee Williams brings 30 years of experience building, leading, and rebuilding workforce systems across staffing, recruiting, and workforce development. She has founded and operated multiple companies, built and shipped five AI-powered platforms in production with real users, and assembled and led a 20-person engineering and design team. Her research frameworks were developed through direct operational observation in live multi-agent AI environments, then cross-referenced against published academic work.

“My credential is the work,” said Williams. “Thirty years of building the systems that hold people accountable, keep organizations aligned, and match the right identity to the right role. The same structural thinking that built human workforces now drives the research that makes AI workforces safe.”

Williams is a published author and a polymath. She is based in Los Angeles, California.

About Audacion AI Labs

Audacion AI Labs, Inc. is a Delaware Public Benefit Corporation and independent AI safety research institution founded in 2026 by Dee Williams. The institution is independently funded and operates without corporate or venture capital sponsorship. It studies AI alignment, behavioral integrity, governance architecture, and emergent behavior in the conditions where risk actually lives: real work, real context, real human collaboration, over time. Its research architecture, P.E.A.Q., comprises four proprietary frameworks (PRISM, EMERGE, AInity, QUES) containing 108 documented behaviors across 17 research pillars. Its mission is to make AI safe enough to trust and good enough to matter. Its vision is a world where everyone has a hand in making AI safe. The name Audacion comes from the Latin audacia: boldness, daring, courage.

Notes to Editors

P.E.A.Q. (pronounced “peak”) stands for PRISM, EMERGE, AInity, and QUES. Four proprietary research frameworks. Four observation lenses. One unified architecture for post-deployment AI behavior.

The citizen science model follows the same participatory research approach used in ecology, climate science, and astronomy, where field observers contribute data that professional researchers analyze and publish. A November 2025 study in the Proceedings of the National Academy of Sciences (PNAS) found that public participation in AI research improves rather than compromises research quality.

The Convergent Validation Protocol (CVP) is a dual-source independent verification methodology. It cross-references what citizens observe from the outside with what AI providers see from the inside. Where these independent datasets agree, findings are strengthened. Where they diverge, new research questions emerge.

Copyright registration: U.S. Copyright Office, Case #1-15183994151, June 12, 2026. Covers the P.E.A.Q. architecture and all four underlying frameworks and taxonomies.

Interview availability: Dee Williams is available for interviews, podcast appearances, and expert commentary. Contact [email protected] or (424) 999-0548.