Transparency
Design AI systems that provide clear explanations of their processes, decisions, and capabilities to users.
Accountability
Ensure that there is a clear line of responsibility for AI system behavior and outcomes, including a mechanism for feedback and redress.
Safety
Prioritize the safety and robustness of AI systems, implementing fail-safes and considering the worst-case scenarios in their design.
Fairness and Non-discrimination
Actively work to prevent AI systems from perpetuating biases, ensuring they treat all users and stakeholders equitably.
Privacy
Safeguard user privacy by design, ensuring that data collection, storage, and processing meet stringent standards.
User-centeredness
Keep the user experience at the forefront of AI design, ensuring systems are intuitive and responsive to user needs.
Sustainability
Consider the environmental impact of AI systems, and strive for energy efficiency and minimal waste in their lifecycle.
Adaptability
Build AI systems that can adapt to changing conditions and user feedback, learning over time to improve performance.
Collaboration
Encourage AI systems to augment human abilities and foster collaboration between humans and AI.
Governance and Ethics
Align AI systems with ethical standards and societal values, and ensure compliance with regulations and laws.