Google, following on the heels of OpenAI, published a policy proposal in response to the Trump Administration’s call for a national “AI Action Plan.” The tech giant endorsed weak copyright restrictions on AI training, as well as “balanced” export controls that “protect national security while enabling U.S. exports and global business operations.”
“The U.S. needs to pursue an active international economic policy to advocate for American values and support AI innovation internationally,” Google wrote in the document. “For too long, AI policymaking has paid disproportionate attention to the risks, often ignoring the costs that misguided regulation can have on innovation, national competitiveness, and scientific leadership — a dynamic that is beginning to shift under the new Administration.”
One of Google’s more controversial recommendations pertains to the use of IP-protected material.
Google argues that “fair use and text-and-data mining exceptions” are “critical” to AI development and AI-related scientific innovation. Like OpenAI, the company seeks to codify the right for it and rivals to train on publicly available data — including copyrighted data— largely without restriction.
“These exceptions allow for the use of copyrighted, publicly available material for AI training without significantly impacting rightsholders,” Google wrote, “and avoid often highly unpredictable, imbalanced, and lengthy negotiations with data holders during model development or scientific experimentation.”
Google, which has trained a number of models on publicly available, copyrighted data, is battling lawsuits with data owners who accuse the company of failing to notify and compensate them before doing so. U.S. courts have yet to decide whether fair use doctrine effectively shields AI developers from IP litigation.
In its proposal, Google also takes issue with export controls imposed under the Biden Admininstration, which it says “may undermine economic competitiveness goals” by “imposing disproportionate burdens on U.S. cloud service providers.” That contrasts with statements from Google competitors like Microsoft, which in January said that it was “confident” it could “comply fully” with the rules.
Importantly, the export rules carve out exemptions for trusted companies seeking large clusters of advanced AI chips.
Elsewhere in its proposal, Google calls for “long-term, sustained” investments in foundational domestic R&D, pushing back against recent federal efforts to reduce spending and eliminate grant awards. The company said the government should release data sets that might be helpful for commercial AI training, and allocate funding to “early-market R&D” while ensuring computing and models are “widely available” to scientists and institutions.
Pointing to the chaotic regulatory environment created by the U.S.’ patchwork of state AI laws, Google urged the government to pass federal legislation on AI, including a unified privacy and security framework. Just over two months into 2025, the number of pending AI bills in the U.S. has grown to 781, according to an online tracking tool.
Google cautions the U.S. government against imposing what it perceives to be onerous obligations around AI systems, like usage liability obligations. In many cases, Google argues, the developer of a model “has little to no visibility or control” over how a model is being used by a developer and thus shouldn’t bear responsibility for misuse.
“Even in cases where a developer provides a model directly to deployers, deployers will often be best placed to understand the risks of downstream uses, implement effective risk management, and conduct post-market
monitoring and logging,” Google wrote.
Google also called disclosure requirements like those being contemplated by the EU “overly broad,” and said the U.S. government should oppose transparency rules that require “divulging trade secrets, allow competitors to duplicate products, or compromise national security by providing a roadmap to adversaries on how to circumvent protections or jailbreak models.”
