Learn how to assess AI system transparency and explainability by analyzing neural network diagrams. Gain insights into bias, robustness, and transparency in AI models.
Table of Contents
Question
Which of the following options would be true for the AI system shown in the following graphic?
A. The AI system is biased.
B. The AI system is very robust.
C. The AI system is transparent.
D. The AI system has very little explainability.
Answer
The AI system shown in the graphic would be considered to have very little explainability (Option D).
Explanation
It can be very difficult to understand exactly how the recommendations produced by an AI system are arrived at. This picture illustrates a system with very low explainability.
The diagram depicts a neural network with several hidden layers (P2, P4, P5) between the input layer and output layer. In such deep learning models with multiple hidden layers, it becomes challenging to understand and explain how the system arrives at its outputs based on the given inputs. The complex interconnections and transformations that occur within the hidden layers create a “black box” effect, making it difficult to interpret the model’s decision-making process.
While the system’s architecture is visible, the lack of clarity around how the hidden layers process and transform the data limits the overall explainability. Explainability refers to the ability to understand and interpret the reasoning behind an AI system’s predictions or decisions.
The other options can be ruled out:
A. Bias cannot be determined solely from the network diagram without additional context about the training data and performance across different subgroups.
B. Robustness, which relates to an AI system’s ability to perform consistently under various conditions or inputs, cannot be inferred from the diagram alone.
C. Transparency, in the context of AI, usually refers to the openness and accessibility of information about the system’s design, data, and decision-making process. While the diagram provides some visibility into the architecture, it does not necessarily imply a high level of transparency.
In summary, based on the limited information provided by the neural network diagram, the AI system appears to have very little explainability due to the presence of multiple hidden layers that obscure the reasoning behind its outputs.
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