More than 150 parents urged Governor Kathy Hochul to sign the New York RAISE Act without changes, escalating a high-stakes fight over how open models are governed. The bill would impose safety plans and disclosure duties on large AI developers, and the outcome could ripple across open-source projects maintained by small teams.
Moreover, The letter arrived as Hochul reportedly floated a near-total rewrite that industry groups favor. According to new reporting, the bill passed both chambers in June, yet last-minute revisions could shift compliance burdens and timelines. Because many open-model efforts ship weights and code publicly, even narrow tweaks may affect release practices and community norms.
New York RAISE Act implications for open models
Furthermore, The proposal requires developers of large models to prepare safety plans and report significant incidents. These steps aim to reduce foreseeable misuse and document mitigations. In principle, open communities already share evaluations, benchmarks, and known limitations. Nevertheless, a statutory mandate changes the stakes, since legal exposure can follow missed disclosures or unclear accountability.
Therefore, Open projects vary widely in governance. Some live under nonprofit umbrellas, while others rely on lab grants or volunteer maintainers. Therefore, a uniform reporting rule could strain small contributors who lack legal counsel. Larger foundations may adjust more easily. In practice, many groups will need standardized templates for risk statements, eval summaries, and model card updates. Companies adopt New York RAISE Act to improve efficiency.
NY RAISE bill What the bill requires
Consequently, Although text may evolve, the bill’s core ideas are consistent. Developers must document hazards, outline mitigations, and record significant safety incidents. Additionally, they should report how models were evaluated and where red-team testing fell short. These requirements push toward reproducible, transparent workflows. Consequently, maintainers will likely add pre-release checklists, versioned safety notes, and clear triage routes for user reports.
As a result, If New York sets the bar, other states could mirror its template. That prospect matters because model builders often publish globally on the same timelines. Coordinated compliance could reduce confusion. Yet fragmented state rules can create duplicated reporting and complex jurisdiction questions.
New York AI bill Tech pushback and the AI Alliance
In addition, Major AI companies and allied groups argue the bill is unworkable. The AI Alliance, which counts Meta, IBM, Intel, Oracle, Snowflake, Uber, AMD, Databricks, and Hugging Face among its members, raised deep concerns about feasibility and scope. After a summer of hearings, companies pressed lawmakers to lighten disclosures and limit liability. As pressure mounted, parents organized to defend the bill’s core guardrails, calling them minimalist but essential. The latest letter urging an unaltered signature can be read in reporting from The Verge. Experts track New York RAISE Act trends closely.
Additionally, Industry critics warn that paperwork-heavy rules will slow releases and stifle local innovation. Supporters counter that transparent safety plans can prevent foreseeable harm and raise baselines across the board. Because open developers share artifacts widely, they risk being held to commercial standards without commercial resources. That tension sits at the heart of the current debate.
Why open-source developers are concerned
For example, Open communities often work iteratively in public. Therefore, incident reporting can feel continuous rather than episodic. A crash in a demo, a jailbreak prompt, or a new prompt injection becomes a tracked issue. If the law defines incidents narrowly, teams may manage. If definitions broaden, maintainers could face ongoing compliance work that exceeds volunteer capacity.
For instance, Licensing and release cadence also matter. Many open models ship research checkpoints first, then safer fine-tunes. As a result, disclosures must keep pace with each iteration and downstream fork. Clear version identifiers and changelogs will help auditors connect a report to a specific artifact. Furthermore, public bug trackers could double as incident ledgers, but only if the law accepts that practice and provides safe harbor for good-faith fixes. New York RAISE Act transforms operations.
Meanwhile, Funding is another pressure point. Smaller labs will need counsel, policy templates, and automation for compliance. Grants may start to include earmarked funds for safety documentation. Additionally, package registries and model hubs could integrate attestation fields, letting maintainers include safety plan links during upload. Those platform features would create consistent metadata that regulators can parse.
The broader trend toward licensed IP
In contrast, Commercial alliances are shifting content access toward licensed pipelines. For example, a new licensing pact between OpenAI and Disney will bring hundreds of characters and assets into Sora and ChatGPT, with curated Sora videos planned for Disney+. That deal, reported by Engadget, underscores a move toward controlled distribution and curated outputs. Open developers cannot access those assets under similar terms.
On the other hand, As closed ecosystems expand, open projects rely more on public datasets, synthetic corpora, and community red-teaming. Therefore, governance rules that demand robust documentation will intersect with uneven access to evaluation resources. Fair compliance should recognize that disparity. Otherwise, rules may entrench large incumbents and sideline public-interest research. Industry leaders leverage New York RAISE Act.
Lessons from adjacent accountability fights
Notably, Supply chain accountability debates in hardware foreshadow the scrutiny now reaching model pipelines. Recent lawsuits filed in Texas accuse top US chip firms of neglecting controls that allowed components to reach Russian and Iranian weapons systems. The complaints, covered by Ars Technica, allege firms relied on thin assurances from intermediaries. While the facts differ, the parallel is clear. Policymakers seek auditable processes that can withstand real-world misuse.
In particular, AI governance is on the same path. Documented mitigations, traceable releases, and prompt remediation will become routine expectations. Consequently, open projects benefit from adopting lightweight but rigorous processes now.
What happens next for New York and beyond
Hochul’s decision will set the immediate direction. If she signs the bill unchanged, agencies will draft guidance and timelines. If she pushes a rewrite, negotiations will restart and may water down reporting thresholds. Either way, developers should prepare practical playbooks. Teams can map risks, prewrite incident templates, and assign clear owners for disclosures. Companies adopt New York RAISE Act to improve efficiency.
Model hubs and research institutions can also help. In addition, they can host shared documentation frameworks and validation tools. Community norms around model cards and eval sheets already exist. Standardized formats and automated checks will reduce overhead and support consistent compliance across forks and derivatives.
For the open-source AI ecosystem, the stakes are high but manageable. Transparent processes can improve trust without halting research. With right-sized rules, New York can raise safety baselines and protect small builders. The coming weeks will reveal whether the final text reaches that balance, or whether another round of revisions sends the debate back to square one. Until then, open-model maintainers will watch closely, because the next release may be their first real test under a new regulatory regime. More details at open model transparency rules.