Transparency in AI refers to making AI decisions understandable and accountable to users and stakeholders.
It involves explaining how AI models make decisions and ensuring that users can question or challenge AI outcomes.
Option A (Incorrect): While establishing an ethical and unbiased culture is essential for responsible AI development, it does not directly contribute to AI transparency. Transparency requires clear communication and user engagement.
Option B (Incorrect): Communicating AI goals and objectives is helpful but insufficient on its own.
Transparency also includes revealing AI decision-making processes and allowing user oversight.
Option C (Correct): Allowing users to give feedback regarding AI inferences ensures transparency by making AI decision-making accountable. Users can report errors, biases, or misunderstandings, helping improve AI fairness and reliability.