**Full Disclosure** I have not verified all of the source links contained, proceed accordingly.
Model: ChatGPT 5.6 Sol
Effort: (Medium)
Harness: Codex
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The honest verdict is: there are a few material advances in making model-maker power more visible and contestable, but little evidence that model makers are transferring meaningful governing or economic power to the people affected by their systems.
A useful ladder is:
- Rhetoric: “AI should benefit everyone.”
- Legibility: publish system cards, policies, evaluations, and limitations.
- External scrutiny: allow independent testing and incident reporting.
- Accountability: impose enforceable duties, penalties, whistleblower protection, and appeal.
- Power sharing: affected people receive binding votes, vetoes, ownership, compensation, or control over deployment.
The industry has made visible progress around levels 2 and 3. Regulation is beginning to create level 4. Level 5 is largely absent.
What appears materially real
External evaluation exists. OpenAI, Anthropic, and Google DeepMind have provided advanced models to the UK AI Security Institute for safety testing. That gives a government body some independent measurement capacity rather than requiring the public to accept company claims. But access remains substantially cooperative, and the Institute explicitly says it does not certify models as safe. UK AI Security Institute
Some disclosure is becoming legally enforceable. California’s SB 53 requires large frontier developers to publish safety frameworks, establishes critical-incident reporting and whistleblower protections, and permits civil penalties for noncompliance. That is genuine power accounting because the rules create evidence and consequences outside company discretion. California governor’s SB 53 summary
European oversight is becoming consequential. Anthropic, Google, OpenAI, Microsoft, Mistral, and others signed the EU’s General-Purpose AI Code of Practice. The code is voluntary as an implementation mechanism, but it helps satisfy underlying AI Act obligations; European Commission enforcement powers, including fines, begin applying in August 2026. European Commission
Anthropic created a body with actual corporate authority. Its Long-Term Benefit Trust can select members of Anthropic’s board. That is more than an advisory ethics panel: it places a nonstandard stakeholder inside the corporate governance machinery. The Trust appointed a director in 2025, demonstrating that the mechanism is operative. Anthropic LTBT, board appointment
OpenAI’s nonprofit retains formal control of its public-benefit corporation. That can place mission above conventional shareholder primacy in ways an ordinary corporation cannot. But it concentrates interpretive authority in the Foundation rather than distributing it democratically. OpenAI structure
These are real institutional changes. They should not be dismissed as nothing.
What remains mostly experimental or symbolic
OpenAI funded ten “democratic inputs” experiments, and Anthropic trained an experimental model using principles gathered from roughly 1,000 Americans. These are useful demonstrations that public preferences can technically influence model behavior. OpenAI democratic-input program, Anthropic Collective Constitutional AI
But OpenAI explicitly said its initial outcomes were not binding. The public was invited to advise, not given jurisdiction. Anthropic and its partner still chose the questions, moderation rules, translation method, and implementation boundary. Participation occurred inside a container whose ultimate authority remained with the company.
Likewise, Anthropic’s Trust is structurally meaningful but not broadly democratic. Its trustees are not elected by workers, users, artists whose work entered training data, displaced communities, or the general public. It is closer to elite fiduciary stewardship than popular power sharing.
The strongest counterevidence
Industry transparency has recently worsened. Stanford’s 2026 AI Index reports that the average Foundation Model Transparency Index score fell from 58 in 2024 to 40 in 2025, while reporting on responsible-AI benchmarks remained sparse. Stanford AI Index 2026
The 2026 International AI Safety Report finds that more developers now publish frontier safety frameworks, system cards, and risk-management disclosures. But many arrangements remain voluntary, practices vary widely, and the real-world effectiveness of safeguards is still uncertain. International AI Safety Report 2026
That combination matters:
Economic power is the weakest area
There is growing measurement. Anthropic has an Economic Futures Program offering research grants and public labor-market data. OpenAI has published job-transition frameworks and repeatedly says AI’s benefits and power should be broadly distributed. Anthropic Economic Futures, OpenAI’s stated plan
But measurement is not redistribution.
I do not see strong evidence that major model makers have yet committed to mechanisms such as:
- worker or public ownership of frontier infrastructure;
- binding revenue or productivity dividends;
- compensation governed by creators and data subjects;
- worker vetoes over workplace AI deployment;
- guaranteed support for displaced workers;
- public control over deployment in essential services;
- individual rights to explanation, appeal, and human reconsideration across jurisdictions;
- affected-community seats with binding corporate authority.
The companies are studying displacement, providing tools and training, recommending policy, and funding research. Those actions can be useful. They do not give a person materially greater bargaining power if AI eliminates their job, their data contributes to a commercial system, or an automated decision harms them.
Bottom line
There is evidence of an emerging safety-accounting regime:
- name certain risks;
- test models;
- disclose procedures;
- report major incidents;
- protect some internal dissent;
- permit limited government scrutiny.
There is much less evidence of a social power-accounting regime:
- identify who captures the gains;
- identify who absorbs the losses;
- give affected people enforceable rights;
- provide refusal and appeal;
- transfer decision rights and economic ownership;
- make harms costly to the institutions producing them.
So I would not say nothing is happening. Some institutional footholds are real, especially where law creates consequences. But I also would not accept “benefits all humanity” or “broadly distributed power” as demonstrated outcomes. At present, they remain aspirations expressed by organizations that continue to decide for themselves what those phrases mean.
The clearest test is simple:
For most consequential questions, the answer is still: the company decides, unless a government successfully constrains it.
