AI Fundamentals & Academic Integrity Quiz

1. True or False: AI systems are always objective and free from bias.

True

False

2. Which principle is most important when deploying AI systems in academic institutions?

Ensuring fairness, transparency, and accountability to users

Maximizing profit from the AI system

Keeping all AI operations completely secret

Using the most expensive technology available

Submit

4. What does explainability in AI refer to?

The ability to understand and interpret AI model decisions

The speed at which an AI system processes data

The cost of developing an AI system

The number of users an AI system can serve

5. True or False: AI systems can make decisions without any human input or oversight.

True

False

6. What is the primary goal of regularization in machine learning?

To prevent overfitting and improve generalization

To increase model complexity

To make data entry faster

To eliminate the need for training data

7. Which metric measures the proportion of correct predictions made by a model?

Accuracy

Precision

Recall

F1-score

Submit

9. What is the primary purpose of data preprocessing in machine learning?

To clean and prepare raw data for model training

To delete all irrelevant data permanently

To increase the size of datasets artificially

To encrypt sensitive information

10. Which of the following is a responsible way to use AI tools in academic work?

Use AI as a research aid while properly disclosing its role in your work

Submit AI-generated content as your own original work

Use AI to generate entire essays without reading them

Hide all use of AI tools from your instructor

11. What is artificial intelligence primarily defined as?

Computer systems designed to perform tasks requiring human-like intelligence

Any software program that automates business processes

A branch of mathematics focused on statistical analysis

The process of manually coding all computer instructions

12. What does transparency in AI systems mean?

Users can understand how an AI system makes decisions

AI systems must be made freely available online

All AI systems must use the same algorithm

AI systems cannot use any data from the internet

13. What is a key ethical concern when training AI models on biased data?

The model may perpetuate or amplify existing biases in predictions

The model will run slower on computers

The data will become too large to store

The model will refuse to make any predictions

Submit

15. What is overfitting in machine learning?

A model performing well on training data but poorly on new data

A model that learns general patterns effectively

Using too little data for training

A model that is too simple to learn patterns

16. Which term describes an AI model's ability to perform well on new, unseen data?

Generalization

Overfitting

Bias

Variance

17. What does unsupervised learning aim to do?

Find hidden patterns in unlabeled data

Classify data into predetermined categories

Predict specific numerical values

Create new data from scratch

18. In supervised learning, what is required for training a model?

Labeled data with correct input-output pairs

Unlabeled data with no predefined outcomes

Only computer processing power

A team of programmers writing code

19. What is a neural network inspired by?

The structure and function of biological brain neurons

Computer circuit boards and electrical systems

Mathematical equations from calculus

Traditional database management systems

20. Which of the following best describes machine learning?

A subset of AI where systems learn patterns from data without explicit programming

A technique for manually entering data into computers

The ability to program computers in multiple languages

A method of organizing files on a hard drive

AI Fundamentals Academic Integrity and AI Use Quiz

1. True or False: AI systems are always objective and free from bias.

2.

What first name or nickname would you like us to use?

2. Which principle is most important when deploying AI systems in academic institutions?

3. When using AI tools for research, proper______ requires documenting all AI-generated content and its source.

4. What does explainability in AI refer to?

5. True or False: AI systems can make decisions without any human input or oversight.

6. What is the primary goal of regularization in machine learning?

7. Which metric measures the proportion of correct predictions made by a model?

8. A confusion matrix in machine learning is primarily used to____.

9. What is the primary purpose of data preprocessing in machine learning?

10. Which of the following is a responsible way to use AI tools in academic work?

11. What is artificial intelligence primarily defined as?

12. What does transparency in AI systems mean?

13. What is a key ethical concern when training AI models on biased data?

14. In academic integrity, using AI to complete assignments without attribution is considered____.

15. What is overfitting in machine learning?

16. Which term describes an AI model's ability to perform well on new, unseen data?

17. What does unsupervised learning aim to do?

18. In supervised learning, what is required for training a model?

19. What is a neural network inspired by?

20. Which of the following best describes machine learning?