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AI and Machine Learning Quiz

Total questions: 20

Worksheet time: 10mins

Name
Class
Date
1.

Which approach creates tomorrow’s playlist by learning what you skip and like?

a)

Manual curation

b)

Rule-based programming

c)

Machine learning

d)

Random shuffle

2.

Why might a purely rule-based chatbot struggle with new slang?

a)

It forgets old rules

b)

It has no internet access

c)

It cannot update rules on its own

d)

It runs too slowly

3.

Machine learning is best described as a system that …

a)

Sends email automatically

b)

Stores large files

c)

Learns patterns from data

d)

Plays videos in HD

4.

Deploying AI “on the edge” usually means running the model …

a)

In a distant cloud server

b)

Directly on a local device

c)

In a data warehouse

d)

On a backup tape drive

5.

Which device is MOST likely to use edge AI for quick, private predictions?

a)

Desktop PC at school

b)

Smartwatch fitness tracker

c)

Company mainframe

d)

Large gaming console

6.

A hiring AI could become biased if its training data …

a)

Is balanced across groups

b)

Contains past biased decisions

c)

Comes from many countries

d)

Is updated every month

7.

Overfitting happens when a model …

a)

Learns training data too exactly

b)

Has too few layers

c)

Runs on battery power

d)

Uses edge deployment

8.

The MAIN goal of data privacy in AI is to …

a)

Reduce battery drain

b)

Keep personal information safe

c)

Speed up training time

d)

Increase screen resolution

9.

A rule-based system is BEST when …

a)

Rules rarely change

b)

Data is huge and messy

c)

Patterns shift daily

d)

Output must be creative

10.

Machine-learning systems excel when …

a)

There are fixed, simple rules

b)

Tasks require adapting to new data

c)

Memory use must be tiny

d)

Results never change

11.

Which is a potential DESIGN risk in AI?

a)

Low Wi-Fi speed

b)

Biased training samples

c)

High screen brightness

d)

Missing user manual

12.

To keep up with slang, an ML chatbot should …

a)

Freeze its model

b)

Collect fresh conversational data

c)

Disable language detection

d)

Switch to grayscale mode

13.

A key benefit of edge AI for smartphones is …

a)

24-hour battery life

b)

Lower network latency

c)

Brighter screen colors

d)

Cheaper phone cases

14.

Larger, more varied training data usually …

a)

Increases overfitting

b)

Reduces generalization

c)

Improves model robustness

d)

Deletes old weights

15.

Which signal often shows a model is overfitting?

a)

High accuracy on new data

b)

Low loss on training, high loss on test data

c)

Fast loading time

d)

Small file size

16.

Choosing a “fixed rule” playlist each morning MOST closely matches …

a)

Rule-based AI

b)

Reinforcement learning

c)

Unsupervised clustering

d)

Neural pruning

17.

Sending every camera frame to the cloud for face detection mainly risks …

a)

More bias

b)

Higher latency and privacy loss

c)

GPU overheating

d)

Sharper images

18.

When sketching “bias sneaks in,” the arrows from data set to predictions highlight …

a)

Missing values

b)

Skewed representation

c)

Compression ratios

d)

Pixel density

19.

Which regulation topic is MOST related to AI data privacy?

a)

Net neutrality

b)

GPS accuracy

c)

User consent for data use

d)

Screen refresh rate

20.

A strong answer on the exit ticket must include all EXCEPT …

a)

Correct choice (rule-based or ML)

b)

Two supporting reasons

c)

Perfect drawing of a robot

d)

Proper grammar and spelling