Homework Help: Questions and Answers: When should developers, data scientists, and other people who work with AI consider ethics?
a) At the end of the AI lifecycle
b) At the beginning of the AI lifecycle
c) Only when training the model
d) Throughout the AI lifecycle
Answer:
First, lets understand the AI Lifecycle:
- The AI lifecycle includes several stages such as problem definition, data collection, model training, evaluation, deployment, and monitoring.
- Ethical considerations can impact each stage differently, such as data privacy during data collection, fairness during model training, and accountability during deployment.
To solve this question, we need to consider the role of ethics in the development and deployment of AI systems. Here’s a step-by-step analysis:
Given Options: Step by Step Answering
a) Throughout the AI lifecycle
- This approach ensures that ethical considerations are integrated at every stage, helping to address and mitigate potential issues continuously.
b) At the end of the AI lifecycle
- Considering ethics only at the end can lead to overlooking potential issues during earlier stages, making it difficult or costly to address problems after they have occurred.
c) At the beginning of the AI lifecycle
- While it’s crucial to consider ethics from the start, ethical issues can also arise later in the process, requiring ongoing attention.
d) Only when training the model
- Ethical considerations during training are important (e.g., fairness and bias), but they are not the only time ethical issues can arise.
Final Answer:
Based on the above analysis, the correct answer is:
a) Throughout the AI lifecycle
Developers, data scientists, and others working with AI should consider ethics throughout the entire AI lifecycle, not just at the beginning, end, or during model training alone. Continuous ethical evaluation is crucial to create safe, fair, and responsible AI systems.
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