The Biden-Harris Administration should aim to make the United States a world leader in privacy-preserving machine learning (PPML), a collection of new artificial intelligence (AI) techniques capable of providing the benefits of machine learning while minimizing data-privacy concerns. By some estimates, improvements to the speed, accuracy, and scale of AI could augment global GDP by 14%, or $15.7 trillion, by 2030. Yet Americans fear that expansion of AI will have moderate to severe negative consequences. They are particularly concerned about the privacy implications of how companies and agencies use personal data to generate new developments. To assuage these concerns, this proposal recommends targeted initiatives for the Biden-Harris Administration to bring PPML techniques to maturity, including
- Investing in PPML research and development.
- Identifying compelling opportunities to apply PPML techniques at the federal level.
- Creating frameworks and technical standards to facilitate wider deployment of PPML techniques.
As Congress moves forward with the appropriations process, both the House and Senate have proposed various provisions related to artificial intelligence (AI) and machine learning (ML) across different spending bills.
The looming competition for global talent has brought forth a necessity to evaluate and update the policies concerning international visa holders in the United States.
Despite the hype, the uptake of geothermal energy is still relatively low, with only 0.4% of U.S. electricity generated by geothermal.
Responsible governance is crucial to harnessing the immense benefit promised by AI. Here are recommendations for advancing ethical, high-impact AI with thoughtful oversight.