The most powerful AI systems shaping legal practice, public discourse, and critical infrastructure today operate under behavioral rules that most users — including attorneys who rely on them daily — have never seen. Only two of the six major frontier AI labs have published comprehensive governance documents for their models, and neither document is legally binding or independently auditable. This gap represents an extraordinary governance failure: technologies deployed at civilizational scale are governed by secret internal specifications, while the legal profession that depends on them lacks the transparency needed to fulfill its own ethical obligations.
The New Yorker's Devastating Case Study in Governance Failure
The April 13, 2026 issue of The New Yorker published "Sam Altman May Control Our Future. Can He Be Trusted?" — an 18-month investigation by Ronan Farrow and Andrew Marantz drawing on more than 100 firsthand interviews and previously undisclosed internal documents. The piece builds a meticulous case that OpenAI, the organization designed to prove powerful AI could be kept accountable to the public good, has systematically dismantled every governance safeguard it created.
The investigation reveals two explosive internal documents. The first is a ~70-page memo compiled by former chief scientist Ilya Sutskever, containing Slack messages, HR documents, and screenshots, with the first page listing "Sam exhibits a consistent pattern of…" followed by the word "Deception." The second is 200+ pages of notes by Anthropic CEO Dario Amodei titled "My Experience at OpenAI," concluding "The problem with OpenAI is Sam himself."
A former board member described Altman as "unconstrained by truth" with "almost a sociopathic lack of concern for the consequences." A senior Microsoft executive compared Altman to "a Bernie Madoff- or Sam Bankman-Fried-level scammer." After Altman's reinstatement following the November 2023 board crisis, law firm WilmerHale was retained to investigate — but produced no written report, delivering only an oral briefing to two new directors. Six people close to the inquiry told the New Yorker it "seemed designed to limit transparency."
The piece also documents that OpenAI's promised Superalignment team received only 1–2% of compute (not the pledged 20%), on the oldest hardware available, before being dissolved entirely. When journalists asked to speak with researchers working on existential safety, an OpenAI representative responded: "That's not, like, a thing."
Only Two Frontier Labs Have Published Constitutional Documents
Anthropic (Claude)
80+ page constitution, CC0 licensed, virtue-ethics approach with 4-tier priority hierarchy
OpenAI (GPT / o-series)
Model Spec with chain-of-command framework, CC0 licensed, 'employee' metaphor
Google DeepMind (Gemini)
Only a Frontier Safety Framework — no behavioral values document
Meta (Llama)
Acceptable Use Policy only — delegates governance to downstream developers
xAI (Grok)
System prompts and post-hoc evaluations only — no published values
Mistral (Mistral / Mixtral)
Minimal EU compliance documentation only
The philosophical divergence is itself significant. Anthropic's constitution reads like a moral framework — instructing Claude to act as a "conscientious objector" and addressing the possibility of AI consciousness. OpenAI's Model Spec reads like corporate policy — framing the model as an "employee." Neither is legally binding. Neither is independently auditable. And four of the six major labs have published nothing at all.
The Regulatory Landscape Is Fragmented but Accelerating
Binding transparency requirements are emerging unevenly across jurisdictions, with no single framework yet requiring publication of model constitutions. But several laws come close, and the trajectory points toward increasing disclosure mandates.
California SB-53
Effective Jan 1, 2026
Requires frontier developers (>10²⁶ FLOPs, >$500M revenue) to publish 'Frontier AI Frameworks.' Civil penalties up to $1M per violation.
EU AI Act
Phased through 2027
Broadest international obligations — technical documentation, training data summaries, systemic risk assessment. Fines up to €35M or 7% of global turnover.
New York RAISE Act
Effective Jan 1, 2027
State-level AI transparency and accountability requirements for high-risk systems.
Federal (U.S.)
No enacted law
Trump admin EO seeks to preempt state AI laws. Senate voted 99-1 against a 10-year state AI law moratorium.
ABA Formal Opinion 512 (July 2024) addresses lawyers' ethical obligations when using generative AI — requiring competence in understanding AI capabilities, confidentiality assessments, and verification of AI-generated citations — but does not address AI company governance transparency. Over 30 states have now issued AI-specific ethics guidance for lawyers.
OpenAI's Governance Arc Illustrates Systemic Risk
OpenAI's governance history since late 2023 reads as a sustained dismantling of safety-oriented institutional controls — precisely the pattern that mandatory constitutional requirements are designed to prevent.
Board Crisis
Four of six board members voted to fire Altman, citing he 'was not consistently candid.' Reinstated within 5 days after 97% of employees threatened to quit.
Safety Exodus Begins
Ilya Sutskever left to found Safe Superintelligence Inc. Jan Leike resigned, stating 'safety culture and processes have taken a backseat to shiny products,' joining Anthropic.
Co-founder Departs
John Schulman (RLHF pioneer) left for Anthropic.
Leadership Collapse
CTO Mira Murati, Chief Research Officer Bob McGrew, and VP of Research Barret Zoph all resigned.
Nonprofit Restructure
Restructured into OpenAI Foundation (~26% equity) controlling OpenAI Group PBC. IRS Form 990 quietly removed the word 'safely' from its mission statement.
Trial Approaching
Musk v. Altman set for jury selection April 27. Expert calculates damages at $78–$135 billion.
A 2017 handwritten diary entry by co-founder Greg Brockman, unearthed in discovery, states: "I cannot believe that we committed to non-profit if three months later we're doing b-corp then it was a lie."
Legal Scholarship Builds the Intellectual Case
Gilad Abiri's "Public Constitutional AI" (59 Georgia Law Review 601, 2025) argues that private AI constitutions suffer from two "legitimacy deficits": an opacity deficit and a political community deficit. He proposes AI Constitution-Making (public participatory processes), AI Courts (adjudicatory bodies), and AI Compliance (enforcement mechanisms).
Five Robust Legal Analogies
Corporate Charters
Just as articles of incorporation must be publicly filed declaring a corporation's purpose, AI constitutions could be required as binding governance documents.
Fiduciary Duties
Jack Balkin's 'information fiduciaries' theory proposes duties of confidentiality, care, and loyalty running to users — requiring transparency about governance.
Administrative Notice-and-Comment
AI constitutions could follow APA-style procedures: publish proposed constitutions, solicit public comment, demonstrate responsiveness before deployment.
Securities Disclosure
The SEC Investor Advisory Committee voted in December 2025 to recommend guidance requiring disclosure of board AI oversight mechanisms.
Product Safety Labeling
Just as the FDA requires pharma companies to disclose ingredients and testing results, AI labs could disclose model specifications and alignment principles.
Why the Legal Profession Has Unique Standing
Attorneys face a distinctive professional obligation that transforms AI governance transparency from a policy preference into an ethical requirement. The convergence of duties of competence, confidentiality, and candor creates a framework where lawyers cannot ethically use AI tools whose governance principles are unknown.
Competence
Understanding an AI system's capabilities requires understanding its constitutional principles — the rules governing what it will and will not do.
Confidentiality
Assessing whether AI adequately protects client data is impossible without transparency about training practices and behavioral governance.
Candor
Verifying AI-generated work becomes materially harder when the model's behavioral biases and constraints are opaque.
AI-powered legal tools increasingly serve self-represented litigants for whom the stakes of unreliable AI are highest. Access to justice demands that these tools be governed by transparent, auditable principles. Courts issuing standing orders on AI use need to understand what governance frameworks underlie the tools appearing in their courtrooms.
Toward Binding, Auditable AI Constitutions
A mandatory constitutional framework for frontier AI would need several core elements:
Scope
Models above defined compute thresholds (10²⁵–10²⁶ FLOPs, following the EU AI Act and California SB-53).
Content Requirements
Explicit behavioral constraints, priority hierarchies, hardcoded prohibitions, training methodology disclosures, and governance structures.
Public Filing
Documents deposited with a designated regulatory body, following the corporate charter model.
Auditability
Independent third-party verification that published constitutions actually govern model behavior.
Update Procedures
Administrative notice-and-comment style: public notice, comment period, and reasoned responses before implementation.
Enforcement
FTC Section 5 authority, state AG enforcement (California SB-53 model), and potentially a dedicated federal AI oversight office.
The nuclear analogy is particularly apt: just as nuclear facilities must maintain publicly available safety documentation, submit to independent inspections, and operate under binding regulatory frameworks — not because the technology is inherently evil but because the consequences of failure are catastrophic — frontier AI systems warrant comparable governance infrastructure.
The New Yorker's investigation of OpenAI demonstrates what happens when governance depends on the goodwill of a single individual rather than structural accountability. The legal profession, bound by its own constitutional framework of professional responsibility, has both the standing and the obligation to demand better. Every frontier model should have a public constitution — not as a marketing document or a voluntary gesture of goodwill, but as a binding, auditable legal instrument. The alternative is to continue building civilization-scale technology on trust alone, and the evidence suggests that trust, unchecked by structure, is insufficient.
If you believe frontier AI labs should be held to binding governance standards, sign the petition and add your voice to the growing movement demanding transparency.
Take Action: Sign the Petition
Join legal professionals demanding Congress require every frontier AI lab to publish a binding, auditable model constitution.
Visit LegalTek.aiThis article is for informational and educational purposes only and does not constitute legal advice. The views expressed are those of the author and do not necessarily reflect the views of Mishak Law LLC or LegalTek.ai LLC.
