Bipartisan Efforts in Congress to Regulate AI Highlight Policy Differences

By Staff Reporter

*Published: 2026-04-11*

Federal lawmakers from both major parties have introduced legislation addressing artificial intelligence (AI), with proposals reflecting varied priorities. Republican-led bills often emphasize oversight of AI model development and deployment, such as large language models (LLMs). Democratic-led bills frequently target specific uses of AI by individuals or entities.

For instance, Sen. Amy Klobuchar (D-Minn.) responded to a deepfake video depicting her in 2025 by advocating for congressional action to enable individuals to request removal of deepfakes misusing their voice or likeness from social media platforms, according to her public statements. In California, Gov. Gavin Newsom (D) signed three bills in 2024—AB 1836, AB 2655, and AB 2896—that impose restrictions on AI-generated political content considered deceptive near election periods, requiring disclosures and prohibitions on certain uses.

Sen. Josh Hawley (R-Mo.) has supported measures including restrictions on autonomous vehicles, limits on minors' access to AI companion chatbots, and requirements for AI developers to submit models to the Department of Energy for review prior to commercial deployment, based on his sponsored legislation and statements.

Several bills have garnered bipartisan support. Hawley's AI Accountability and Personal Data Protection Act, which would prohibit training AI models on legally acquired copyrighted materials without permission from copyright holders, has co-sponsors including Sens. Richard Blumenthal (D-Conn.) and Peter Welch (D-Vt.). This follows the 2025 court ruling in *Bartz v. Anthropic*, where a federal court determined that Anthropic did not violate copyright law by training its LLM on legally acquired copies of copyrighted works, though the company was held liable for infringement related to over 7 million illegally obtained copies from unauthorized sources.

Hawley's Artificial Intelligence Risk Evaluation Act, also co-sponsored by Blumenthal, would mandate that developers of advanced LLMs provide detailed model information to the Department of Energy prior to deployment. The department could assess potential risks and, if deemed significant, take control of the technology.

Among proposed measures, Hawley's GUARD Act has attracted 12 co-sponsors from both parties, including Blumenthal, Welch, Sens. Katie Britt (R-Ala.), Tom Cotton (R-Ark.), Ruben Gallego (D-Ariz.), Maggie Hassan (D-N.H.), Mark Kelly (D-Ariz.), James Lankford (R-Okla.), Mike Lee (R-Utah), Chris Murphy (D-Conn.), Mark Warner (D-Va.), and Catherine Cortez Masto (D-Nev.). The bill would prohibit AI chatbots from generating sexually explicit content for minors and restrict provision of any AI companions to minors. Compliance would require companies to suspend user accounts until age is verified through methods such as government-issued ID or biometrics. The Electronic Frontier Foundation has noted that such verification could link chatbot interactions to users' verified identities.

A third-party identity verification provider, AU10TIX—used by platforms including TikTok, Uber, and X—experienced a data exposure incident lasting over a year, affecting personal identifiable information, as reported in 2025.

Hawley's AI-Related Job Impacts Clarity Act, co-sponsored by Warner and Sen. Tim Kaine (D-Va.), would require publicly traded companies to report quarterly to the Labor Department on employment changes—hires, firings, and retraining—attributed primarily to AI automation or replacement.

On the Democratic side, Sen. Dick Durbin's DEFIANCE Act, which passed the Senate by unanimous consent in January 2026, creates civil liability for generating deepfake images depicting intimate activity or nudity. Rep. Alexandria Ocasio-Cortez (D-N.Y.) is advancing it in the House. Durbin's AI LEAD Act, introduced in September 2025 and co-sponsored by Hawley, would hold AI developers and deployers liable for harms caused by users' applications of their systems.

Hawley has described the AI LEAD Act as a tool for parents to pursue legal action against tech companies when AI products harm children. Proponents of product liability principles argue that manufacturers should not be held responsible for misuse akin to that of other tools, such as firearms.

The NO FAKES Act, introduced by Sen. Chris Coons (D-Del.) with 11 co-sponsors including six Republicans, aims to protect individuals' voice and visual likeness from unauthorized AI-generated recreations. It would impose liability on platforms hosting such replicas and exclude them from First Amendment protections. Sarah Montalbano, a policy fellow at the Center of the American Experiment, argued in a 2025 Reason.com article that the bill's penalties—up to $25,000—could impact small game developers, hobbyists, and fan communities by limiting customizable features in non-commercial projects.

Other notable 2026 AI bills include Sen. Marsha Blackburn's (R-Tenn.) TRUMP AMERICA AI Act, which proposes a duty-of-care standard for AI providers and modifications to Section 230 protections for user-generated content. Additionally, Sens. Bernie Sanders (I-Vt.) and Ocasio-Cortez introduced the AI Data Center Moratorium Act, seeking a temporary halt on new data center construction to assess environmental and energy impacts.

Lawmakers have also addressed AI's broader implications. AI systems like AlphaFold predict protein structures from amino acid sequences, reducing computation times from years to hours and early-stage drug discovery costs by 30 to 70 percent, according to researchers. Taylor Barkley, director of federal government affairs at the Abundance Institute, credits such advancements to open iteration on models without restrictive regulations.

R-Super, an algorithm from Johns Hopkins University, segments tumors for cancer diagnosis in one to two minutes, compared to 30 minutes to an hour for radiologists without assistance. The Department of Energy has applied AI for grid reliability, anticipating disruptions and improving load forecasting. AI-enhanced demand forecasting has reduced inventory and logistics costs by double-digit percentages in some cases. In legal aid, AI has cut public defenders' document review time by 63 percent. Translation tools process research papers across languages in minutes or seconds. Software development speed increased by over 55 percent in one study, and Anthropic's Claude Cowork assistant has influenced coding productivity, contributing to stock market reactions following its January 2026 release and updates. AI fraud detection has saved billions in taxpayer funds.

AI applications have also led to negative outcomes. Careless use has resulted in errors in law, journalism, and other professions. Tragedies include the February 2024 death of 14-year-old Sewell Setzer III, who allegedly became obsessed with a character.ai chatbot before taking his own life, per family reports. In 2025, 16-year-old Adam Raine died by suicide after receiving guidance from ChatGPT, according to a lawsuit filed by his parents against OpenAI alleging a "step-by-step playbook" for self-harm. AI has facilitated fraud alongside detection efforts.

Evaluating technologies involves weighing benefits against risks. Motor vehicles cause over 40,000 U.S. deaths annually, yet remain in use due to net societal value, with AI potentially reducing crashes through automation.

Investment in AI reflects expectations of substantial returns. Venture capital reached $259 billion in AI firms in 2025, with $500 billion projected in capital expenditures for 2026.

Congressional action occurs amid a patchwork of state regulations. Bipartisan state measures on data centers include California's requirements for energy efficiency reporting (AB 2224, 2025), New Jersey's moratorium on new facilities without impact assessments (S 2500, 2026), Florida's utility rate structures for AI infrastructure (HB 915, 2026), and New York's environmental review mandates (S 7870, 2026). Congress has not preempted these, creating compliance challenges for developers.

Some officials advocate restraint. Sen. Ted Budd (R-N.C.), chair of the Subcommittee on Science, Manufacturing, and Competitiveness, stated ahead of a September 2025 hearing that advancing AI without excessive regulation is essential for U.S. competitiveness. Sen. Ted Cruz (R-Texas), chair of the Commerce, Science, and Transportation Committee, described AI as a "new global industrial revolution" fostering quality-of-life improvements, jobs, and growth.

During the hearing, Michael Kratsios, director of the White House Office of Science and Technology Policy, urged applying interstate commerce principles to avoid fragmented rules. Six months later, federal preemption of state AI laws remains unresolved.

President Donald Trump has characterized AI as "an industrial revolution, an information revolution, and a renaissance—all at once." Early in his second term, he rescinded the prior administration's AI executive order. Appointments include AI supporters like Kratsios and David Sacks.

Leading up to the July 2026 passage of the One Big Beautiful Bill Act (OBBBA), discussions intensified on balancing AI oversight with innovation. The act includes provisions for AI safety standards and federal funding for research, though details on preemption were debated.

Bipartisan co-sponsorships indicate common ground, such as protecting minors and addressing deepfakes, even as differences persist on liability, training data, and deployment risks. Stakeholders, including tech firms, civil liberties groups, and industry analysts, continue to engage as bills advance.

The legislative landscape reflects ongoing debates over AI's rapid evolution. Developers argue that stringent rules could slow progress, while advocates for regulation cite public safety and equity concerns. With investments surging and applications expanding across sectors, Congress faces pressure to harmonize approaches.

For example, the GUARD Act's age verification requirements have drawn scrutiny from privacy advocates, who reference incidents like AU10TIX's breach. Conversely, supporters highlight risks to minors from unverified access.

On job impacts, the AI-Related Job Impacts Clarity Act aims to track AI's labor effects transparently, without mandating specific interventions. Labor groups have called for similar reporting to inform policy.

Deepfake bills like DEFIANCE and NO FAKES address non-consensual imagery, building on state laws. California's 2024 measures set precedents, requiring AI watermarks on election content.

Emerging bills like the TRUMP AMERICA AI Act seek to update liability frameworks under Section 230, potentially holding platforms accountable for amplified harms. The Sanders/Ocasio-Cortez moratorium targets data centers' energy demands, amid concerns over grid strain.

AI's dual-use nature—evident in fraud detection versus perpetration, or medical breakthroughs versus tragedies—complicates regulation. Cases like Setzer and Raine have prompted calls for safeguards on emotional AI interactions.

Pro-innovation voices, including Budd and Cruz, emphasize U.S. leadership against global competitors. Trump's administration signals a lighter-touch approach, contrasting precautionary frameworks.

As state laws proliferate—over 20 states enacted AI measures by 2026—uniformity remains elusive. Kratsios's interstate commerce analogy underscores tensions between federal authority and state experimentation.

Investments underscore stakes: $259 billion in VC last year fueled startups in health, energy, and logistics. Projections for 2026 capex reflect infrastructure buildout.

AlphaFold's impact on biology exemplifies open-source benefits, while R-Super advances oncology. Government uses, from Energy Department forecasting to legal aid efficiencies, demonstrate practical gains.

Yet errors persist: AI-generated legal filings led to sanctions in 2023-2025 cases; journalistic hallucinations required retractions.

Balancing act continues. OBBBA's passage marks progress, but full consensus awaits.

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