AI Regulation Changes: Trump's Plans Post-Election Victory

Wednesday, 6 November 2024, 21:18

AI regulation is set to change dramatically as Trump plans to dismantle Biden's safeguards. After winning the 2024 US presidential election, Donald Trump aims to repeal the 2023 order, impacting large language models and machine learning policies. This shift will redefine how the US government oversees AI technology moving forward.
Arstechnica
AI Regulation Changes: Trump's Plans Post-Election Victory

AI Regulation Changes Following Trump's Election

Trump plans to repeal Biden's 2023 order and levy tariffs on GPU imports. Early Wednesday morning, Donald Trump became the presumptive winner of the 2024 US presidential election, setting the stage for dramatic changes to federal AI policy when he takes office early next year. Among them, Trump has stated he plans to dismantle President Biden's AI Executive Order from October 2023 immediately upon taking office.

Impact of Biden's AI Executive Order

Biden's order established wide-ranging oversight of AI development. Among its core provisions, the order established the US AI Safety Institute (AISI) and laid out requirements for companies to submit reports about AI training methodologies and security measures, including vulnerability testing data.

  • Oversight Body: US AI Safety Institute (AISI)
  • Reporting Requirements: Companies to report on AI training methods
  • Development Guidance: NIST to create guidelines for fixing AI model flaws

Criticism from Trump's Supporters

Trump supporters in the US government have criticized the measures. In March, Representative Nancy Mace (R-S.C.) warned that reporting requirements could discourage innovation and prevent developments like ChatGPT. Senator Ted Cruz (R-Texas) characterized NIST's AI safety standards as an attempt to control speech through woke safety requirements.


This article was prepared using information from open sources in accordance with the principles of Ethical Policy. The editorial team is not responsible for absolute accuracy, as it relies on data from the sources referenced.


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