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AI and Deepfakes Quiz

Total questions: 40

Worksheet time: 2hrs 40mins

Name
Class
Date
1.

What are the primary fields explored in AI applications?

a)

Computer Vision

b)

Unsupervised Learning

c)

Generative AI

d)

Natural Language Processing

e)

Robotics and Automation

2.

What is the role of AI in speech processing?

a)

AI recognizes, understands, and generates speech

b)

AI only recognizes speech

c)

AI generates text from speech

d)

AI translates speech to text

3.

Name two AI applications in healthcare.

4 lines
4.

What is a recommendation system?

a)

An AI system providing personalized content suggestions

b)

A system for managing user data

c)

A tool for analyzing market trends

d)

A method for improving customer service

5.

What AI technologies are used in Amazon's warehouse robots?

4 lines
6.

How does AI contribute to addressing the climate crisis?

4 lines
7.

What are the key ethical considerations in AI?

4 lines
8.

What AI system is used in facial recognition for hotel check-ins by Baidu?

4 lines
9.

What technology powers deepfakes?

a)

Generative Adversarial Networks (GANs)

b)

Convolutional Neural Networks (CNNs)

c)

Recurrent Neural Networks (RNNs)

d)

Support Vector Machines (SVMs)

10.

Name one creative use of deepfakes.

4 lines
11.

What is the primary ethical issue with deepfakes?

a)

Misinformation and fraud

b)

Privacy invasion

c)

Data theft

d)

Lack of consent

12.

How can deepfakes be detected?

4 lines
13.

What are two common tools for creating deepfakes?

4 lines
14.

How can GANs enhance the entertainment industry?

4 lines
15.

What are two benefits of deepfakes in education?

4 lines
16.

What is a creative ethical application of deepfakes?

4 lines
17.

Define Generative AI.

a)

AI that generates new content like text, images, or audio

b)

AI that analyzes existing content

c)

AI that translates languages

d)

AI that recognizes patterns

18.

What is the discriminator's role in GANs?

4 lines
19.

Give an example of Generative AI in entertainment.

4 lines
20.

What ethical challenges does Generative AI face?

4 lines
21.

What are the two main types of generative models?

4 lines
22.

What is a notable application of CycleGAN?

4 lines
23.

Name a healthcare application of generative AI.

4 lines
24.

What does a generator in GANs do?

4 lines
25.

What does NLU stand for?

a)

Natural Language Understanding

b)

Natural Language Usage

c)

Natural Language Unification

d)

Natural Language Utility

26.

Name one real-world application of chatbots in healthcare.

4 lines
27.

What is lexical analysis in NLP?

4 lines
28.

What are the main components of NLU?

4 lines
29.

How does syntactic analysis differ from semantic analysis in NLP?

4 lines
30.

What is pragmatic analysis in NLP?

4 lines
31.

What is an ethical consideration when using chatbots in customer service?

4 lines
32.

What makes human language challenging for NLP?

4 lines
33.

What is the purpose of the testing dataset in model evaluation?

a)

To evaluate performance on unseen data

b)

To train the model

c)

To validate the model

d)

To tune hyperparameters

34.

How is accuracy calculated in a confusion matrix?

4 lines
35.

What does TPR stand for, and what is its formula?

4 lines
36.

What is an ROC curve used for?

4 lines
37.

What is overfitting, and how is it avoided in model evaluation?

4 lines
38.

What is precision in the context of a confusion matrix?

4 lines
39.

What challenge does unbalanced data pose in model evaluation?

4 lines
40.

What is the significance of the area under an ROC curve (AUC)?

4 lines