AI Principles are foundational to AI governance. They are also foundational to Responsible and Trustworthy AI. They should guide decision-making at all levels of your organization in ways that ensure everyone is leveraging the innovative potential of AI while at the same time protecting shareholder value from risk and failures.
AI Principles can inform your policies, governance structures and processes. It’s critical to publish your AI Principles to employees, third parties and other stakeholders. Sharing and training on these principles will help your organization govern the use of AI internally. Use examples to drive the intent behind a principle home. Answer the questions, ‘what is this’, ‘why have this? and ‘how do we do this’?
The terms "Responsible AI" and "Trustworthy AI" are two sides of the same coin, working together to ensure AI is beneficial and reliable. Both rely on existing regulations, rules and laws and standards that require privacy and resilience, but raise the bar, due to the astounding nature of the technology itself, and its’ ability to perform functions and provide insights at machine-speed, rather than human-speed.
When we talk about Responsible AI (RAI) and Trustworthy AI (TAI) we are referring to all aspects of creating, complexity, transparency, fairness, training and security of AI models and algorithms. We need these hyper-powered principles because AI is a new technology that beings into question the process of decision-making with lightning-speed tech. As a result, new concepts arise in both Responsible AI and Trustworthy AI that reflect the innovation and rapid evolution of the technology itself.
Here are examples of AI Principles that you can consider revising and adopting for your organization. Use a range of inputs when formulating your AI principles, including your organization’s goals, corporate values, culture, and governance, your AI goals, known AI risks of the technologies in scope for your organization, expectations of key stakeholders and AI regulations, rules, laws and standards.
By defining AI principles, your AI strategy will be understood, technologically sound, ethical, responsible, defensible and beneficial to both your organization and society. By incorporating these principles, you can create an AI governance framework that adapts to change, promotes responsible development, fosters trust, and ensures AI is used appropriately
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