OpenAI appears preparing to introduce a significant new hurdle for developers wanting access to its most powerful future AI models via API: a potential requirement for organizations to undergo identity verification using government-issued IDs.
Details emerging from an OpenAI support page last week describe a “Verified Organization” process, framed by the company as a necessary step to counter misuse and promote responsible AI deployment. OpenAI suggests this targets a “small minority” intentionally violating its usage policies, aiming to “mitigate unsafe use of AI while continuing to make advanced models available to the broader developer community.”
This verification links an authorized individual’s personal government ID to their organization’s API use, with the stipulation that each ID can only validate one organization every 90 days, and eligibility isn’t guaranteed for all applicants, raising questions about the specific criteria.
The proposed system is already generating discussion among developers online. Concerns center on the added operational friction, the privacy considerations of submitting government identification, the potential exclusion of users in regions outside OpenAI’s list of supported API countries, and broader skepticism about whether the primary motivation is purely safety or also encompasses user tracking and enhanced control over its platform access, especially given past actions like the API block in China or investigations into alleged data misuse by DeepSeek and others.
New Models Could Trigger New Controls
This potential verification layer surfaces just as OpenAI prepares for what sources suggest is an imminent release of new AI models – the very systems likely to fall under this stricter access rule, perhaps underscoring the timing of the policy reveal. New launches could happen as soon as this week, including GPT-4.1 as an update to its multimodal model GPT-4o, along with specialized reasoning models designated o3, o4-mini, and o4-mini-high.
OpenAI’s model rollout strategy aligns with a significant strategic adjustment confirmed by CEO Sam Altman on April 4th. Announcing a “Change of plans,” Altman prioritized the release of the o3 and o4-mini models “probably in a couple of weeks,” while pushing the debut of the much-anticipated GPT-5 back by “a few months.”
He indicated a desire to “decouple reasoning models and chat/completion models” and tweeted enthusiasm for o3’s internal performance, suggesting the GPT-5 delay would allow the company “to make GPT-5 much better than we originally though[t].” This reversed a plan from February 2025 to potentially fold o3’s abilities into GPT-5.
The need for distinct reasoning models was apparent even after the late February launch of GPT-4.5, which OpenAI’s own system card acknowledged fell short of specialized models on certain logic-intensive benchmarks, despite Altman describing it as feeling like talking to a thoughtful person rather than a reasoning powerhouse.
Safety Questions Shadow Rapid Releases
The arrival of these more powerful systems, particularly the reasoning models previewed with strong benchmark scores but potentially high compute costs, provides context for increased access control. However, OpenAI’s stated safety rationale for the ID verification contrasts sharply with reports that the safety evaluation periods for these very models have been drastically shortened.
OpenAI’s operations allegedly reduced safety testing timelines for models like o3 from months down to sometimes less than a week, driven by intense competitive pressures. This acceleration has reportedly alarmed some involved in the evaluation process.
Specific testing methodologies are also under fire. Critics point to a lack of published results for misuse potential testing using fine-tuning – further training on specialized data to probe for dangerous emergent capabilities – on the newest, most capable models like o1 or o3-mini.
Former OpenAI safety researcher Steven Adler, who detailed views in a blog post, argued this could lead labs to underestimate dangers, telling the Financial Times, “Not doing such tests could mean OpenAI and the other AI companies are underestimating the worst risks of their models.” Concerns were also raised about testing intermediate model versions, or checkpoints, instead of the final code shipped to the public. “It is bad practice to release a model which is different from the one you evaluated,” a former technical staff member mentioned to the FT.
OpenAI’s head of safety systems, Johannes Heidecke, countered these points, asserting, “We have a good balance of how fast we move and how thorough we are,” attributing speed to automation and stating tested checkpoints were “basically identical” to final releases.
Internal Tensions and Industry Backdrop
This apparent friction between development velocity and safety caution isn’t new territory for OpenAI. Internal disagreements were underscored by the May 2024 departure of Jan Leike, then co-lead of the long-term risk-focused Superalignment team, who publicly stated that “safety culture and processes have taken a backseat to shiny products.”
Adding another dimension to the company’s internal dynamics, former OpenAI employees filed an amicus brief on April 11th supporting Elon Musk’s lawsuit against the company. The brief argues OpenAI’s shift toward a capped-profit structure deviates from its founding non-profit mission, potentially impacting safety commitments and resource allocation.
The potential ID verification policy unfolds as competitors make varied public gestures toward safety and transparency, such as Anthropic detailing an interpretability framework (though the company also quietly removed some prior voluntary safety pledges) and Google DeepMind proposing a global AGI safety structure. This occurs against a backdrop of nascent regulation like the EU’s AI Act, ongoing discoveries of model vulnerabilities and jailbreaking techniques, and OpenAI’s own acknowledged capacity constraints which could potentially affect service stability during new rollouts.
