Quiz on Dataset

How does historical bias affect chatbot performance?

• The chatbot uses vague labels for responses.

• It overrepresents certain demographics.

• It provides outdated or irrelevant advice.

• It misunderstands informal speech patterns.

Which dataset bias occurs when the training data includes vague labels?

• Sampling Bias

• Selection Bias

• Labelling Bias

• Linguistic Bias

Why is synthetic data valuable for training chatbots?

• It ensures diversity without exposing sensitive information.

• It always outperforms real-world data.

• It eliminates the need for feedback loops.

• It reduces model complexity.

What is the purpose of regular audits in chatbot training?

• To improve computational efficiency

• To update outdated data and fix label inaccuracies

• To reduce the size of training datasets

• To remove redundant features from models

Which bias results from over-representation of certain viewpoints in a dataset?

• Selection Bias

• Confirmation Bias

• Historical Bias

• Linguistic Bias

What is the ultimate goal of improving chatbot datasets?

• To ensure responses reflect stereotypes accurately

• To provide inclusive, fair, and respectful interactions

• To reduce storage requirements for training models

• To limit chatbot functionality to specific scenarios

What is the primary challenge of using synthetic data for chatbot training?

• It introduces privacy concerns.

• It cannot simulate rare user queries.

• It is difficult to generate in large quantities.

• It may lack the complexity of real-world interactions.

What is the role of benchmarking in chatbot training?

• To measure performance against a consistent standard

• To increase dataset diversity

• To prioritize specific demographics in training

• To reduce model complexity

Which of the following is NOT a role of datasets in chatbot training?

• Train algorithms to learn patterns

• Benchmark performance across models

• Prevent dataset biases from emerging

• Validate and test chatbot models

Which solution can help address dataset bias in chatbot training?

• Reducing dataset size

• Limiting feedback loops

• Using only synthetic data for training

• Regularly updating training data