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Responsible Innovation at the Frontier - Americans for Responsible Innovation

ARI’s blueprint for federal AI governance is designed to promote safe frontier AI development in America. The blueprint is built around three governance functions any federal proposal should incorporate.

AI Principles

A guiding framework for our responsible development and use of AI, alongside transparency and accountability in our AI development process.

Gov. Pritzker Signs Nation-Leading Artificial Intelligence Safety Law

Landmark bipartisan legislation creates the country's strongest AI accountability framework while supporting responsible innovation

Responsible AI Principles and Approach | Microsoft AI

Discover Microsoft AI tools, industry-specific governance solutions, and responsible AI practices to make smarter, more informed decisions about AI implementation.

As more Americans adopt AI tools, fewer say they can trust the results | TechCrunch

AI adoption is rising in the U.S., but trust remains low, with most Americans concerned about transparency, regulation, and the technology’s broader societal impact, according to a new Quinnipiac poll.

Frontier AI Regulation Blueprint

A high-level blueprint for domestic regulation of civilian advanced AI models

Responsible AI

Discover how AWS is committing to developing AI responsibly – to built trust, promote the safe development of AI, and act as a force for good.

Where AI Regulation Stands Today

The White House has released a National Artificial Intelligence Legislative Framework and new executive orders aiming to establish a single, nationwide standard for AI regulation...

Make America AI Ready: Strengths, Weaknesses, and Recommendations - CITP Blog

A free text-message course from the Department of Labor (DOL) and private partner Arist called, “Make America AI-Ready”, is a useful start on the journey to AI literacy for all Americans.

AI.Gov | President Trump's AI Strategy and Action Plan

Explore President Trump’s AI initiatives focused on innovation, infrastructure, international engagement, and youth education in artificial intelligence.

Built to benefit everyone

OpenAI’s recapitalization strengthens mission-focused governance, expanding resources to ensure AI benefits everyone while advancing innovation responsibly.

Debates On Frontier Artificial Intelligence Governance: The AI Triad

Analytical Paper Optional: All enrolled students have the option of completing a research paper of at least 20-25 pages, with faculty and peer review of a substantially complete draft. This paper can be used to satisfy the analytical paper requirement for J.D. students. Prerequisite: This course is intended for students intending to work in the […]

Pacing the Frontier | Gillian K. Hadfield

The Pacing the Frontier letter calls on the US government to support an international effort to build the technical and governance tools needed to protect our option to pace AI development. I and others have been working on the problem of how to build such infrastructure for ten years, including participating in dialogues on AI safety with Chinese academic colleagues during the past three. Here are my suggestions: 1. Don’t rely on off-the-shelf models like FINRA and the FDA which were built for 20th Century single-domain government expertise. They’re not fit for purpose. 2. Don’t act like no-one’s thought about the AI governance problem before. We’ve spent two years refining a regulatory markets design into working legislative language, for example, and it’s now in AI governance bills in five states and in Congress. 3. Don’t try to write an exhaustive set of rules for AGI first.  4. Pick a domain that can achieve widespread global consensus to start. Mine would be recursive self-improvement: models should not build models. Build the technology that verifies that. 5.  Focus relentlessly on building flexible verification infrastructure that is able to enforce whatever rules we can ultimately agree on.  6. Don’t assume we already know how to do this and governments can just write tests into law. Technology needs to be built and by the private sector. 7. Don’t wait for the infrastructure to emerge first. The components and people are there and the ecosystem can scale fast with the right incentives. 8. Incentivize large-scale investment in verification technology by building a governance structure and industry funding that creates a market for private verification organizations. 9. Use licensing and public oversight to ensure verifiers are independent of the frontier labs. 10. Protect sovereignty by enabling each government to license its own verifiers from a global market of verifiers recognized by other countries. 11. Leverage the incentive of global trade for models and model services by requiring verification for market access. 12. Just start. Sources in comments.

Developing Enterprise Frontier Safeguards with our customers

Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.

Irresponsible AI: big tech's influence on AI research and associated impacts

The accelerated development, deployment and adoption of artificial intelligence systems has been fuelled by the increasing presence of big tech in the AI field. This trend has been accompanied by growing ethical concerns and intensified societal and environmental impacts. This position paper argues that irresponsible AI development is strongly driven by big tech's influence and involvement in the field. First, we examine the growing and disproportionate influence of big tech in AI research and argue that its drive for scaling and general-purpose systems is fundamentally at odds with the responsible, ethical, and sustainable development of AI. Second, we review key current environmental and societal negative impacts of AI and trace their connections to big tech's influence. Third, we discuss the underlying economic forces driving big tech's actions. Finally, as a call to action, we invite AI researchers to counter big tech's influence in irresponsible AI development through strategies that build on the responsibility of implicated actors and collective action.

Irresponsible AI: big tech's influence on AI research and associated impacts

The accelerated development, deployment and adoption of artificial intelligence systems has been fuelled by the increasing presence of big tech in the AI field. This trend has been accompanied by growing ethical concerns and intensified societal and environmental impacts. This position paper argues that irresponsible AI development is strongly driven by big tech's influence and involvement in the field. First, we examine the growing and disproportionate influence of big tech in AI research and argue that its drive for scaling and general-purpose systems is fundamentally at odds with the responsible, ethical, and sustainable development of AI. Second, we review key current environmental and societal negative impacts of AI and trace their connections to big tech's influence. Third, we discuss the underlying economic forces driving big tech's actions. Finally, as a call to action, we invite AI researchers to counter big tech's influence in irresponsible AI development through strategies that build on the responsibility of implicated actors and collective action.