Guiding principles for the use of AI in government

The government is committed to ensuring the effective and ethical use of AI. The following actions are aligned with the Digital Nations Shared Approach to AI, and reflect shared core values and principles:

  1. Promoting openness about how, why, and when AI is used;
  2. Prioritizing the needs of individuals and communities, including Indigenous peoples, and considering the institutional and public benefits of AI;
  3. Assessing and mitigating the risks of AI to legal rights and democratic norms early in the lifecycle of AI systems and following their launch;
  4. Ensuring training or other input data used by AI systems is lawfully collected, used, and disclosed, taking account of applicable privacy and intellectual property rights;
  5. Evaluating the outputs of AI systems, including generative tools, to minimize biases and inaccuracies, and enabling users to distinguish between AI and human outputs;
  6. Publishing legal or ethical impact assessments, source code, training data, independent audits or reviews, or other relevant documentation about AI systems, while protecting privacy, government and national security, and intellectual property;
  7. Explaining automated decisions to people impacted by them and providing them with opportunities to contest decisions and seek remedies, which could involve human review, where applicable;
  8. Encouraging the creation of controlled test environments to foster responsible research and innovation;
  9. Establishing oversight mechanisms for AI systems to ensure accountability and foster effective monitoring and governance throughout the lifecycle;
  10. Assessing and mitigating the environmental impacts of the training and use of AI systems, and where appropriate opting for zero-emissions systems;
  11. Providing training to civil servants developing or using AI so that they understand legal, ethical, and operational issues, including privacy and security, and are equipped to adopt AI systems responsibly; and
  12. Creating processes for inclusive and meaningful public engagement on AI policies or projects with a view to raising awareness, building trust, and addressing digital divides.

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