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CMU Dean Urges Transparency and Accountability in AI Systems in Senate Testimony

  • CMU Dean Ramayya Krishnan testified to a Senate subcommittee on the need for transparency and accountability in AI development and use.

  • Krishnan proposed 4 recommendations require federal agencies to use NIST's AI Risk Framework; require standardized documentation for AI systems; require model validation reports for high-stakes AI; require content labeling and detection standards.

  • Krishnan recommended investing in a "trust infrastructure" for AI like the Computer Emergency Response Team.

  • Krishnan said success depends on comprehensive K-12 and community college AI skills training.

  • Senators Cantwell, Blackburn, Cruz, and Hickenlooper participated in the hearing along with tech industry representatives.

cmu.edu
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### Summary The article discusses the rapid advancement and potential risks of artificial intelligence (AI) and proposes the idea of nationalizing certain aspects of AI under a governing body called the Humane AI Commission to ensure AI is aligned with human interests. ### Facts - AI is evolving rapidly and penetrating various aspects of American life, from image recognition to healthcare. - AI has the potential to bring both significant benefits and risks to society. - Transparency in AI is limited, and understanding how specific AI works is difficult. - Congress is becoming more aware of the importance of AI and its need for regulation. - The author proposes the creation of a governing body, the Humane AI Commission, that can control and steer AI technology to serve humanity's best interests. - The nationalization of advanced AI models could be considered, similar to the Atomic Energy Commission's control over nuclear reactors. - Various options, such as an AI pause or leaving AI development to the free market or current government agencies, have limitations in addressing the potential risks of AI. - The author suggests that the United States should take a bold executive leadership approach to develop a national AI plan and ensure global AI leadership with a focus on benevolence and human-controlled AI. ### đŸ€– AI Nationalization - The case to nationalize the “nuclear reactors” of AI — the world’s most advanced AI models — hinges on this question: Who do we want to control AI’s nuclear codes? Big Tech CEOs answering to a few billionaire shareholders, or the government of the United States, answering to its citizens? ### đŸ‘„ Humane AI Commission - The author proposes the creation of a Humane AI Commission, run by AI experts, to steer and control AI technology in alignment with human interests. ### ⚠ Risks of AI - AI's rapid advancement and lack of transparency pose risks such as unpredictable behavior, potential damage to power generation, financial markets, and public health, and the potential for AI to move beyond human control. ### ⚖ AI Regulation - The article calls for federal regulation of AI, but emphasizes the limitations of traditional regulation in addressing the fast-evolving nature of AI and the need for a larger-scale approach like nationalization.
A new poll conducted by the AI Policy Institute reveals that 72 percent of American voters want to slow down the development of AI, signaling a divergence between elite opinion and public opinion on the technology. Additionally, the poll shows that 82 percent of American voters do not trust AI companies to self-regulate. To address these concerns, the AI Now Institute has proposed a framework called "Zero Trust AI Governance," which calls for lawmakers to vigorously enforce existing laws, establish bold and easily administrable rules, and place the burden of proof on companies to demonstrate the safety of their AI systems.
Congress should prioritize maintaining bipartisan commitment to AI, generating global AI guardrails, and seeking out local perspectives in order to develop effective and responsible AI policies.
The UK government has been urged to introduce new legislation to regulate artificial intelligence (AI) in order to keep up with the European Union (EU) and the United States, as the EU advances with the AI Act and US policymakers publish frameworks for AI regulations. The government's current regulatory approach risks lagging behind the fast pace of AI development, according to a report by the science, innovation, and technology committee. The report highlights 12 governance challenges, including bias in AI systems and the production of deepfake material, that need to be addressed in order to guide the upcoming global AI safety summit at Bletchley Park.
Two senators, Richard Blumenthal and Josh Hawley, have released a bipartisan framework for AI legislation that includes requiring AI companies to apply for licensing and clarifying that a tech liability shield would not protect these companies from lawsuits.
Recent Capitol Hill activity, including proposed legislation and AI hearings, provides corporate leaders with greater clarity on the federal regulation of artificial intelligence, offering insight into potential licensing requirements, oversight, accountability, transparency, and consumer protections.
A bipartisan group of senators is expected to introduce legislation to create a government agency to regulate AI and require AI models to obtain a license before deployment, a move that some leading technology companies have supported; however, critics argue that licensing regimes and a new AI regulator could hinder innovation and concentrate power among existing players, similar to the undesirable economic consequences seen in Europe.
The Subcommittee on Cybersecurity, Information Technology, and Government Innovation discussed the federal government's use of artificial intelligence (AI) and emphasized the need for responsible governance, oversight, and accountability to mitigate risks and protect civil liberties and privacy rights.
Summary: To ensure ethical and responsible adoption of AI technology, organizations should establish an AI ethics advisor, stay updated on regulations, invest in AI training, and collaborate with an AI consortium.
The United Nations General Assembly has seen a significant increase in discussions surrounding artificial intelligence (AI) this year, as governments and industry leaders recognize the need for regulation and the potential risks and benefits of AI. The United Nations is set to launch an AI advisory board to address these issues and reach a common understanding of governance and minimize risks while maximizing opportunities for good.
Sen. Mark Warner, a U.S. Senator from Virginia, is urging Congress to take a less ambitious approach to regulating artificial intelligence (AI), suggesting that lawmakers should focus on narrowly focused issues rather than trying to address the full spectrum of AI risks with a single comprehensive law. Warner believes that tackling immediate concerns, such as AI-generated deepfakes, is a more realistic and effective approach to regulation. He also emphasizes the need for bipartisan agreement and action to demonstrate progress in the regulation of AI, especially given Congress's previous failures in addressing issues related to social media.
The responsibility of determining how generative AI innovations will be implemented across the economy lies with all individuals, from AI experts to finance professionals, who should have a baseline understanding of responsible AI and contribute to the decision-making process, according to experts. The National Institute for Standards and Technology has released an AI risk management framework to guide organizations in reducing discrimination, increasing transparency, and ensuring trustworthiness in AI systems. CEOs and executive committees must take responsibility for assessing the use of AI within their organizations, and strong governance is essential for successful implementation. Additionally, concerns about the impact of AI on the workforce can be addressed through training programs that focus on responsible AI practices.
Regulators should actively learn about algorithmic systems and evaluate them for compliance under existing statutory authority, utilizing tools such as transparency requirements, algorithmic investigations and audits, regulatory AI sandboxes, leveraging the AI assurance industry, and welcoming information from complaints and whistleblowers.