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AI should actively promote well-being and prevent harm. This principle implies that AI should be designed with the intention to bring about positive change and enhance the quality of life.

AI should make decisions without biases, providing equitable outcomes for all stakeholders. Implications involve the need to address historical data biases and ensuring that AI doesn't perpetuate or exacerbate inequality.

Humans should have the autonomy to make decisions about and intervene in AI systems. Implications range from ethical design that empowers users to the risk of undermining human decision-making with overly autonomous AI.

Stakeholders of AI, including developers and businesses, should be accountable for the impacts of AI systems. This includes mechanisms for redress and escalation when AI systems cause harm.

AI should respect and protect individual privacy rights. Implications include the need for secure data practices and transparency about data usage, as well as potential conflicts with data-driven AI applications.

AI systems should be transparent, with clear explanations of the algorithms, data inputs, and decision-making processes. Implications include the ability of users to understand and trust AI decisions, and challenges in proprietary or complex AI systems.

Developers and operators should be responsible for the ethical deployment and use of AI. This includes accountability for misuse, and the need to correct harmful outcomes. Implications include legal and ethical considerations for AI-related actions.