Members of a House panel have emphasized the critical importance of establishing national privacy laws as the foundation for regulating artificial intelligence (AI) in the United States. Their message carried a strong warning against allowing China to dictate global standards for data collection and use, highlighting concerns about privacy infringement and discriminatory practices.
The House Energy and Commerce Committee had previously introduced a bipartisan proposal known as the American Data Privacy and Protection Act; however, the bill faced criticism and failed to gain significant traction. This renewed call for national privacy laws stems from the rapid advancement of generative AI technologies, prompting a sense of urgency among Congress and industry leaders.
During a recent hearing, Rep. Cathy McMorris Rodgers, Chair of the House Energy and Commerce Committee, stressed the urgency for the U.S. to take the lead in addressing the challenges posed by AI. She emphasized the need to safeguard people’s information with a comprehensive national data privacy standard, ensuring that America, not China, shapes the future of AI development and deployment. Committee members and witnesses echoed these concerns, pointing out the lack of nationwide protections regarding data collection and use, which raises alarming issues for American citizens.
They underscored the necessity of preventing companies from misusing personal data and exacerbating discriminatory practices, highlighting the importance of a robust regulatory framework. Furthermore, experts highlighted the inadequacy of the current “notice and consent” paradigm, where users are asked to agree to privacy policies without a clear understanding of the implications. Witnesses emphasized the need for greater transparency in data usage, calling for incentives to encourage application developers to explain, in simple terms, how user data will be utilized. The discussion centered around the urgent requirement for the U.S. to lead in setting global standards, promoting innovation while respecting privacy, competition, and data minimization.
