Topic 1 Question 71
2 つ選択An accounting firm wants to implement a large language model (LLM) to automate document processing. The firm must proceed responsibly to avoid potential harms. What should the firm do when developing and deploying the LLM?
Include fairness metrics for model evaluation.
Adjust the temperature parameter of the model.
Modify the training data to mitigate bias.
Avoid overfitting on the training data.
Apply prompt engineering techniques.
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コメント(5)
- 正解だと思う選択肢: AC
A. Include fairness metrics for model evaluation: Fairness metrics help ensure that the model is not biased against any particular group. This is especially important in fields like accounting, where any biases in automated decisions could lead to unethical outcomes. Fairness metrics provide insight into how well the model treats all data groups equally.
C. Modify the training data to mitigate bias: Adjusting the training data to address any identified biases is crucial for developing responsible AI applications. This can involve balancing the dataset or removing biased samples, ensuring the model generalizes fairly across different data types and groups.
👍 3jove2024/11/10 - 正解だと思う選択肢: BE
A. no need for fairness metrics as the use case is for document processing C. modifying the training data means there is a re-training of the model. not needed for this use case D. there is no re-training needed for this case. avoiding overfitting is also not needed
👍 1KawtarZ2025/01/07 - 正解だと思う選択肢: AC
A: Include fairness metrics for model evaluation Critical for responsible AI implementation Helps identify discriminatory patterns Ensures equitable treatment across different groups Allows for continuous monitoring of fairness Essential for an accounting firm handling sensitive financial data
C: Modify the training data to mitigate bias Addresses bias at the source Ensures representative training data Helps prevent discriminatory outcomes Critical for fair treatment of all clients Fundamental to responsible AI development
👍 1dspd2025/01/29
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