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Answer :
In the context of a responsible AI framework, two ways in which accountability contributes to ethical decision-making in generative AI are -b) Allows for inspection of fairness and correctness and -d) Helps foster trust in the AI model's outputs.
Allows for inspection of fairness and correctness: With accountability measures in place, AI systems can be examined for their fairness and accuracy. This means that the outputs of generative AI can be assessed to ensure they do not perpetuate biases or inaccuracies.
By establishing clear accountability, stakeholders can investigate the decision-making processes of AI algorithms and address any disparities or errors that may arise. This accountability ensures that the AI operates within ethical standards and promotes equitable outcomes.
Helps foster trust in the AI model's outputs: Accountability is crucial in building trust among users and the public regarding the outputs generated by AI systems. When organizations are transparent about how their AI models work and are held answerable for their performance, users are more likely to trust that the AI systems are functioning responsibly and ethically.
Trust is essential for the adoption of AI technologies, as it encourages users to rely on AI-generated results in various applications, from personal assistance to medical diagnoses.
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