Understanding the AI Race

The global landscape for artificial intelligence is rapidly evolving. Nations are recognizing the profound impact AI can have on economic growth, national security, and technological advancement.

The United states and China are at the forefront of this development, with each country investing heavily in research and implementation. This

How did Trump’s “America First” approach to AI differ from administrations prioritizing global collaboration and open research?

Trump’s AI Strategy: A Race for technological Dominance

The Shifting Sands of US AI Policy Under Trump

Donald Trump’s approach to Artificial Intelligence (AI) has been characterized by a focus on national security, economic competitiveness, and a skepticism towards international collaboration. Unlike administrations prioritizing open research and global standards, Trump’s AI strategy, largely unveiled through executive orders and statements during his presidency (2017-2021) and continuing to influence policy discussions in 2025, leans heavily towards a “America first” paradigm. This has significant implications for the future of AI progress, deployment, and regulation. Key areas of focus include bolstering US leadership in artificial intelligence, machine learning, and deep learning technologies.

Executive Orders and the Prioritization of AI

Several executive orders defined the initial framework of Trump’s AI policy.

Executive Order 13859 (Maintaining American leadership in Artificial Intelligence): This 2019 order directed federal agencies to prioritize AI research and development, focusing on areas like national security, healthcare, and transportation. It also emphasized the importance of attracting and retaining AI talent within the US.

Restrictions on AI Exports: Concerns over national security led to increased scrutiny and restrictions on the export of AI-related technologies to countries like China. This aimed to prevent the transfer of sensitive technologies that could be used to enhance military capabilities or surveillance systems.

AI in Government: The governance pushed for greater adoption of AI within government operations, aiming to improve efficiency and effectiveness across various agencies. this included exploring applications in areas like fraud detection, cybersecurity, and border security.

These actions signaled a clear intent to position the US as a dominant force in the AI arms race, prioritizing technological advantage over collaborative progress.

Defense Spending: Significant increases in defense spending fueled AI research within the Department of defense (DoD), particularly in areas like autonomous weapons systems and AI-powered intelligence gathering. The DoD’s Project Maven, for example, focused on using AI to analyze drone footage, sparking ethical debates about the use of AI in warfare.

NSF and NIH Funding: Funding for basic AI research through agencies like the National Science Foundation (NSF) and the National Institutes of Health (NIH) experienced more modest growth, raising concerns among some researchers about the prioritization of applied research over fundamental scientific revelation.

emphasis on “Patriotic” AI: There was a subtle but noticeable shift towards funding projects aligned with national security interests, sometimes described as “patriotic AI,” potentially influencing the direction of research and innovation.

The China Factor: AI Competition and National Security

The escalating geopolitical competition with China has been a central driver of Trump’s AI strategy. The administration viewed China as a significant threat to US technological leadership in AI, citing concerns about intellectual property theft, state-sponsored cyberattacks, and the potential for china to surpass the US in AI capabilities.

Investment Restrictions: The Committee on Foreign Investment in the United States (CFIUS) tightened its review of foreign investments in US AI companies, particularly those with ties to China.

Export Controls: Expanded export controls aimed to limit China’s access to advanced AI technologies,including semiconductors and software.

Talent Acquisition: Efforts were made to prevent the recruitment of US AI talent by Chinese companies and institutions.

This focus on AI competition with China has shaped the US AI landscape,fostering a sense of urgency and driving increased investment in AI research and development.

Limited Federal Regulation: There was a reluctance to impose strict regulations on AI development and deployment, with the argument that excessive regulation could stifle innovation.

Focus on Voluntary Standards: The administration encouraged the development of voluntary standards and best practices for AI ethics and safety, relying on industry stakeholders to address potential risks.

Concerns About Bias and Fairness: Critics argued that the lack of regulation could exacerbate existing biases in AI systems, leading to discriminatory outcomes in areas like criminal justice, healthcare, and employment. The debate surrounding algorithmic bias intensified.

The Legacy and Future of Trump’s AI Strategy (2025)

Even post-presidency, Trump’s influence on US AI policy remains significant. The emphasis on national security, the skepticism towards international collaboration, and the focus on economic competitiveness continue to shape the debate.

Continued Export Controls: Expect continued, and potentially expanded, export controls on AI technologies to China and other countries deemed strategic rivals.

Increased Defense Spending: Further increases in defense spending are likely to fuel AI research within the DoD,particularly in