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As part of its growing initiative to vet AI technologies, the U.S. Government now includes Google’s DeepMind and Microsoft in stress testing programs alongside OpenAI and Anthropic, aiming to preemptively detect potential risks in emerging AI models.
The U.S. government is ramping up its efforts to ensure that artificial intelligence (AI) models are safe and secure before they hit the market. On Tuesday, the Trump administration announced an expansion of a program that grants U.S. government scientists access to unreleased AI models from leading tech companies like Google’s DeepMind and xAI, as well as Microsoft. This move builds on existing collaborations with OpenAI and Anthropic, which have been voluntarily working with the U.S. Center for AI Standards and Innovation (CAISI) to conduct risk assessments.
The goal is clear: to identify and mitigate potential risks associated with advanced AI models before they can be exploited by malicious actors or adversaries. This initiative underscores the growing concern over the ethical and security implications of AI, particularly as these technologies become more sophisticated and integrated into critical systems.
U.S. government scientists are focusing on "demonstrable risks," such as the potential for advanced models to be used in cyberattacks against American infrastructure. According to the CAISI website, they also aim to prevent U.S. adversaries from using AI to develop chemical or biological weapons or to corrupt the data used to train American AI models.
OpenAI, the company behind ChatGPT, is already working with the group to test GPT-5.5-Cyber, a variant of its latest model designed specifically for defensive cybersecurity work. Chris Lehane, head of global affairs at OpenAI, highlighted this collaboration in a LinkedIn post on Tuesday, emphasizing the importance of these tests in ensuring the safety and reliability of AI systems.

Microsoft is also joining the effort. The company will collaborate with government scientists to build shared datasets and workflows that can be used to assess advanced AI models. While Microsoft did not specify which models it will test, the company's statement underscores its commitment to responsible AI development.
The expansion of this program reflects a broader trend in AI regulation, where governments are increasingly stepping in to ensure that these powerful technologies do not pose significant risks to public safety and national security. By working closely with leading tech companies, the U.S. government can gain valuable insights into the capabilities and vulnerabilities of AI models before they are released to the public.
This collaborative approach is crucial for several reasons. First, it helps to build trust between the tech industry and regulatory bodies, fostering a more transparent and accountable environment. Second, it allows for the early identification and mitigation of potential risks, which can prevent harmful consequences down the line. Finally, it sets a precedent for international cooperation in AI governance, which is essential as these technologies continue to evolve and spread globally.
In an era where AI is becoming increasingly integral to our daily lives, from healthcare to transportation, ensuring its safety and ethical use is not just a technical challenge but a moral imperative. The U.S. government's proactive stance on AI regulation is a step in the right direction, but it will require ongoing vigilance and collaboration to fully address the complex challenges that lie ahead.
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Original Sources
What we know about US stress tests of Google, xAI and Microsoft AI models
↗ https://www.reuters.com/legal/litigation/what-we-know-about-us-stress-tests-google-xai-microsoft-ai-models-2026-05-05
About the author
Amara's entry point into AI was an epidemiology role at a London research hospital, where she spent five years studying how digital health tools reached — or conspicuously failed to reach — underserved communities. Watching early algorithmic systems in healthcare quietly entrench existing inequalities, she redirected her career toward the systemic consequences of AI at scale. She covers AI through an unflinching lens: who benefits, who bears the cost, and what evidence actually says versus what the press release claims. Her writing is calm and precise, but she doesn't mistake balance for neutrality.
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