EO 14110 requires organizations to report data on the training and deployment of high-impact AI models. It includes provisions for risk assessment, content watermarking, and cybersecurity measures to ensure AI systems align with national security and ethical standards.

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Under Executive Order 14110 (EO 14110), organizations must implement several technical measures to manage and mitigate risks associated with advanced AI development:

• Reporting and Documentation:

  • Data Reporting: Organizations must provide comprehensive data on the training processes, datasets used, and deployment strategies of high-impact AI models to designated federal agencies.
  • Risk Assessments: Conduct thorough risk assessments to identify and address potential threats posed by AI systems, particularly those related to national security and public safety.

• Content Watermarking:

  • Traceability: Integrate watermarking technologies in AI-generated content to ensure traceability and authenticity.
  • Transparency: Watermarks aid in distinguishing AI-generated content from human-created content, enhancing transparency for users and regulators.

• Cybersecurity Measures:

  • Data Protection: Implement robust cybersecurity frameworks to safeguard AI training data and models from unauthorized access and adversarial attacks.
  • Secure Deployment: Ensure that AI systems are deployed in secure environments to prevent exploitation and misuse.

• Algorithmic Integrity:

  • Bias Mitigation: Develop and deploy algorithms that minimize biases, ensuring fair and equitable AI outcomes.
  • Transparency in Algorithms: Maintain transparency in algorithmic decision-making processes, allowing for scrutiny and accountability.

• Compliance with Ethical Standards:

  • Ethical AI Development: Adhere to ethical guidelines that govern the development and deployment of AI technologies, preventing misuse and ensuring alignment with societal values.
  • User Privacy: Protect user data and privacy in compliance with national data protection standards.

• Safety Protocols:

  • Training Protocols: Implement safety protocols during the training of large language models to prevent the introduction of harmful behaviors or outputs.
  • Monitoring and Evaluation: Continuously monitor AI systems post-deployment to evaluate their performance and impact, making necessary adjustments to maintain compliance.

• Regulatory Collaboration:

  • Data Sharing: Establish secure data-sharing mechanisms that enable federal agencies to audit and verify platform compliance with EO 14110 requirements.
  • Transparency Reporting: Develop systems to compile and regularly publish transparency reports detailing compliance efforts and AI system impacts.