The openness regarding a system's design, data, and algorithms.

The openness regarding a system's design, data, and algorithms.

• A. Explainability
• B. Transparency
• C. Interpretability
• D. Equal Opportunity

Answer: (B)

This is about transparency—the openness of a system about how it is built, what data it uses, and how the algorithms operate. When a system is transparent, stakeholders can see the design choices, the sources and handling of data, preprocessing steps, model architecture, training procedures, versioning, and decision rules. This visibility supports accountability, trust, and the ability to scrutinize potential biases or misuses, and it helps others reproduce results. Explainability focuses on understanding why a specific decision was made, usually providing reasons for a single outcome rather than revealing the entire design and data pipeline. Interpretability aims to make a model's behavior understandable to humans, often by simplifying or translating how inputs map to outputs, but it centers on comprehension of decisions rather than the broader openness of the system. Equal Opportunity concerns fairness in outcomes across different groups, addressing bias and equity rather than how openly the system's internals are shared.

This is about transparency—the openness of a system about how it is built, what data it uses, and how the algorithms operate. When a system is transparent, stakeholders can see the design choices, the sources and handling of data, preprocessing steps, model architecture, training procedures, versioning, and decision rules. This visibility supports accountability, trust, and the ability to scrutinize potential biases or misuses, and it helps others reproduce results.

Explainability focuses on understanding why a specific decision was made, usually providing reasons for a single outcome rather than revealing the entire design and data pipeline. Interpretability aims to make a model's behavior understandable to humans, often by simplifying or translating how inputs map to outputs, but it centers on comprehension of decisions rather than the broader openness of the system. Equal Opportunity concerns fairness in outcomes across different groups, addressing bias and equity rather than how openly the system's internals are shared.