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What does Transparency refer to in the context of responsible AI?
Secretive algorithms
Obscured model outcomes
Making known the purpose and limitations of a solution
Complex programming codes
The correct answer is: Making known the purpose and limitations of a solution
In the context of responsible AI, Transparency involves clearly communicating the purpose and limitations of an AI solution to stakeholders. This principle is crucial because it helps users understand how the AI operates, the reasoning behind its decisions, and the potential consequences of its outcomes. By ensuring that stakeholders are aware of what the AI can and cannot do, organizations foster trust and encourage informed decision-making. Transparency also plays a significant role in mitigating risks associated with AI applications, as users can better navigate the capabilities and boundaries of the technology. The other options do not align with the principle of Transparency in responsible AI. Secretive algorithms and obscured model outcomes suggest a lack of clarity and openness, which contradicts the essence of Transparency. Similarly, while complex programming codes might be a feature of AI systems, they do not address the need for clear communication about the solution’s purpose and limitations. Thus, focusing on making this information known is essential for responsible AI practices.