The advancement of AI is rapidly transforming multiple sectors, from healthcare to finance. However, with this progress comes an increasing demand for regulation to ensure the safe and ethical development of AI technologies. Lawmakers at both the federal and state levels are actively pursuing legislation to address the ethical challenges, risks, and potential of AI.
The Landscape of AI
Presidential Candidates’ Views on AI
As the 2024 US presidential election approaches, AI policy has become a key issue. Both candidates acknowledge AI’s potential, but their approaches to regulation are different.
- Vice President Kamala Harris has been vocal about the risks associated with AI, particularly its potential to harm vulnerable populations. She has advocated for policies emphasizing consumer protection, algorithmic fairness, and safeguarding civil rights. Harris has also supported the Blueprint for an AI Bill of Rights, which outlines transparency, privacy protection, and non-discrimination in AI systems.
- Former President Donald Trump has taken a more innovation-focused approach. While he recognizes the risks associated with AI, particularly in relation to misinformation and deepfakes, he has expressed skepticism about overregulating the industry. His first administration emphasized fostering AI innovation through research and development incentives, and his platform for 2024 pledges to roll back what he views as burdensome AI regulations
Congress & AI
Federal AI legislation is still in its formative stages. Despite the growth of AI in business and government, comprehensive federal regulation has yet to be passed. However, several bills are at play.
- Executive Order on AI (2023): The Biden Administration’s 2023 Executive Order on AI set critical guidelines for how federal agencies should incorporate AI. It emphasizes the protection of personal data, transparency in AI decision-making, and non-discrimination by AI systems. This order is a foundational step towards comprehensive AI regulation.
- Future of AI Innovation Act (4178): This bipartisan bill aims to enhance AI transparency, reliability, and innovation by establishing the US AI Safety Institute at the National Institute of Standards & Technology. The institute is responsible for promoting the development of voluntary standards and creating testbeds for AI research. This bill reflects Congress’ recognition of the need to manage AI risks while ensuring the U.S. remains a global leader in AI.
- CREATE AI Act ( 2714) (HR 5077): The CREATE AI Act would authorize the National AI Research Resource (NAIRR), a cloud resource designed to democratize access to AI tools and infrastructure for researchers across the country. NAIRR is poised to accelerate AI education and research, preparing the next generation of AI professionals while ensuring national competitiveness.
- AI Advancement and Reliability Act (HR 9497): This Act focuses on developing frameworks to ensure the safe and secure deployment of AI technologies. It encourages transparency and accountability from AI developers, requiring rigorous testing to prevent unintended negative outcomes like algorithmic bias.
Based on the bills introduced by Congress, AI legislative action in 2025 will likely focus on five key areas: transparency, accountability, safety, education, and anti-discrimination.
- Transparency and Accountability: Both federal and state lawmakers are increasingly focusing on transparency in AI systems, especially concerning the data used to train these systems and how AI decisions are made. Proposed laws, such as the AI Disclosure Act of 2023, require AI-generated outputs to be clearly labeled to distinguish them from human-made content.
- Safety and Trust: Initiatives like the Validation and Evaluation for Trustworthy AI (VET AI) Act direct NIST to work with various stakeholders to develop certification processes for AI systems. This would ensure that AI systems undergo rigorous external evaluations before deployment.
- Education and Workforce Development: Bills such as the Workforce for AI Trust Act and the NSF AI Education Act emphasize the importance of training a multidisciplinary workforce. These efforts aim to ensure that the US workforce is prepared to handle AI responsibly and safely.
- Anti-Discrimination and Ethical AI: Another emerging trend is the focus on preventing AI systems from exacerbating biases. Many proposed laws require developers to test AI for discriminatory practices and to maintain transparency in how AI models are used in decision-making.
State-Level AI Legislation
In the absence of sweeping federal legislation, individual states have taken the lead in regulating AI. As of 2024, over 40 states have introduced legislation addressing various aspects of AI, particularly in sectors like healthcare, education, and consumer protection.
- California: California leads the nation with its progressive AI legislation. Bills like the Generative AI Transparency Act (AB 2013) require AI developers to disclose the datasets used to train AI models, aiming to increase transparency in generative AI technologies. Moreover, the California AI Transparency Act (SB 942) mandates that AI-generated content must carry labels, preventing deceptive practices.
- Colorado: Colorado’s AI laws are one of the most comprehensive in the country. The state requires developers of high-risk AI systems to use reasonable care to prevent algorithmic bias and discrimination.
- Other States: States like Florida, Utah, and Washington have introduced legislation promoting AI education and workforce development. For example, Florida has given grants to integrate AI tools into educational programs, while Washington supports AI start-ups through state-funded incubators
US and China AI Race
The U.S.-China AI competition has escalated in recent years, transforming from a trade dispute into a strategic contest that could shape global power dynamics. The US currently holds the lead in generative AI, backed by its innovative private sector and superior talent pool. However, China’s state-backed AI initiatives and heavy investment in research and development signal its intention to close the gap. AI has become a critical strategic asset for national security, economic growth, and geopolitical influence. Both the US and China recognize the transformative potential of AI, not only in commerce and innovation but also in military applications. For instance, AI-enhanced technologies, such as drones used in the Ukraine conflict, have underscored the role of AI in modern warfare. The US leads in AI innovation primarily due to its superior computing infrastructure, capital investments, and access to advanced AI chips, such as those produced by Nvidia. American firms like OpenAI and Meta continue to push the boundaries of generative AI. However, China’s centralized, state-backed approach to AI development allows it to maintain long-term strategic investments in AI research, which could enable it to catch up to or even surpass the US in certain AI domains.
However, this competition is not without risks. Taiwan’s strategic importance as a semiconductor hub makes it a potential flashpoint in U.S.-China relations. Any disruption in Taiwan, whether from geopolitical tensions or supply chain issues, could have profound effects on AI development globally. As AI becomes more integrated into national security strategies, the stability of Taiwan’s semiconductor industry becomes increasingly vital for the US. Moreover, China’s efforts to reduce its dependency on foreign semiconductors by investing in domestic AI chip production, such as through companies like SMIC and Huawei, are ongoing. However, their technology remains years behind that of TSMC, with China still struggling to achieve consistent yields in advanced chip production. These challenges suggest that while China may be advancing in AI research, its ability to manufacture the necessary hardware remains a significant limitation.
The race for AI dominance will likely intensify in the coming years, with both nations seeking to secure their positions. For the US, continued leadership will depend on maintaining access to Taiwan’s advanced semiconductors, tightening export controls, and fostering AI innovation through private-sector partnerships. For China, overcoming its manufacturing deficiencies will be critical to narrowing the AI gap. However, with the current sanctions and Taiwan’s continued dominance in chip production, the US seems poised to retain its lead in the near term