Latest action: Forwarded by Subcommittee to Full Committee by Voice Vote.
Referred to one or more standing committees for review, hearings, and possible markup.
Specific committees not parsed from action data.
The committee may hold hearings, amend the bill, or let it die without action.
Next: Reported
Full chamber floor — Speaker / Majority Leader controls scheduling
Establishes federal policies supporting open-source artificial intelligence development and leadership.
The problem
The U.S. faces competition in AI development. Open-source AI could democratize technology access and reduce dependence on large corporations.
The proposal
The bill creates federal frameworks, funding, and policies to promote open-source AI research, development, and adoption across government and industry.
The impact
Tech companies, researchers, startups, and federal agencies gain new AI resources. Large tech firms may face increased competition from distributed development.
Open-source AI reduces control by large tech companies. Smaller businesses and researchers can compete fairly. This drives innovation and lowers barriers to entry.
Federal support for open-source AI strengthens American competitiveness globally. The U.S. can lead in collaborative AI development. This supports long-term technological advantage.
Open-source code allows public review of AI systems. This increases security and reduces hidden biases. Government agencies can audit code effectiveness.
Startups gain access to advanced AI tools without expensive licensing. Federal funding and resources lower startup costs. This creates jobs and economic growth.
Open-source code is publicly visible, potentially exposing vulnerabilities. Adversaries can identify security flaws to exploit. This may threaten critical infrastructure and national defense.
Companies investing in proprietary AI may lose competitive advantage. Open-source alternatives reduce market demand for private solutions. Investor returns and R&D funding may decline.
Federal funding and infrastructure investment requires taxpayer money. Creating standards and support systems is expensive. Ongoing maintenance and updates cost additional resources.
Open-source projects lack centralized oversight and testing standards. Poorly designed AI systems could spread widely. Users may struggle to verify code quality and safety.
Generated by AI from the bill text. Not a prediction and not legal or policy advice. The percentage is the model's own rating of each item — self-reported, and not a measure of how accurate it is.
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Individual contributions, grouped by employer · FEC
Where their individual donors work · 2026 cycle
Money from people who work there, not from the company. Not tied to this bill.
Itemized individual contributions via FEC, grouped by the employer each contributor self-reported. Companies and unions cannot contribute to federal candidates from their treasuries, so these totals are money from people who work at an employer — never from the organization itself. They are campaign contributions covering a full election cycle and are not connected to this bill.
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