Which benefits might persuade a developer to choose a transparent and explainable machine learning model? (Select two)

Which benefits might persuade a developer to choose a transparent and explainable machine learning model? (Select two)
A . They foster trust and confidence in model predictions
B . They enhance security by concealing model logic
C . They simplify the integration process with other systems
D . They facilitate easier debugging and optimization
E . They require less computational power and storage

View Answer

Answer: A, D

Explanation:

Correct options:

They facilitate easier debugging and optimization

Transparent models allow developers to understand how inputs are transformed into outputs, making it easier to identify and correct errors or inefficiencies in the model. This capability is crucial for optimizing the model’s performance and ensuring it behaves as expected.

They foster trust and confidence in model predictions

When stakeholders can understand the decision-making process of a model, it builds trust in its predictions. Transparency is key in high-stakes scenarios, such as healthcare or finance, where understanding the rationale behind predictions is critical for acceptance and trust.

Incorrect options:

They require less computational power and storage – The computational and storage requirements of a model depend on its complexity and the amount of data it processes, not necessarily on its transparency. Both transparent and opaque models can vary widely in their resource needs.

They enhance security by concealing model logic – Opaque models, not transparent ones, are typically associated with enhanced security through obscurity. Transparent models, by definition, reveal their internal workings, which can be less secure if the logic itself needs to be protected.

They simplify the integration process with other systems – The ease of integrating a model with other systems is more related to the architecture and compatibility of the model with existing systems rather than its transparency. Transparent models do not inherently simplify integration processes.

References:

https://docs.aws.amazon.com/whitepapers/latest/model-explainability-aws-ai-ml/interpretability-versus-explainability.html

https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-model-explainability.html