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Introduction to Generative AI Exam

Total questions: 49

Worksheet time: 20hrs 36mins

Name
Class
Date
1.

What is the purpose of using a few-shot learning approach in prompt engineering?

a)

To increase the processing time of the AI model.

b)

To train the AI model on a large dataset.

c)

To limit the capabilities of the AI model.

d)

To provide the AI model with a few examples of the desired output.

2.

What is the term for the ability of an AI model to understand and respond to human language in a natural and contextually relevant way?

a)

Natural language processing (NLP)

b)

Machine learning

c)

Computer vision

d)

Deep learning

3.

Which of the following is a common source of AI bias?

a)

Biased or incomplete training data.

b)

Advanced AI algorithms.

c)

Diverse and representative training data.

d)

High-quality training data.

4.

What is the role of negative examples in prompt engineering?

a)

To show the AI model what NOT to generate.

b)

To provide additional context for the AI model.

c)

To confuse the AI model.

d)

To increase the processing time of the AI model.

5.

What is AI bias?

a)

The intentional or unintentional manipulation of AI models through training data.

b)

The systematic and unfair treatment of certain groups by AI systems.

c)

The tendency of AI models to make mistakes.

d)

The inability of AI models to learn from data.

6.

What is a technique to detect AI hallucinations?

a)

Relying solely on the model's confidence scores.

b)

Evaluating the model's output on diverse datasets.

c)

Increasing the model's complexity.

d)

Using more training data.

7.

What is the term for the ability of an AI model to generate human-quality text, such as articles, poems, or scripts?

a)

Sentiment analysis

b)

Machine translation

c)

Text summarization

d)

Text generation

8.

How can we promote ethical AI development?

a)

Relying solely on technical solutions to address AI challenges.

b)

Prioritizing profit over ethical considerations.

c)

Encouraging collaboration between AI researchers and ethicists.

d)

Ignoring the potential negative impacts of AI.

9.

Which of the following is an example of a poorly constructed prompt?

a)

Write a sonnet about love and loss.

b)

Create a marketing slogan for a new energy drink.

c)

Tell me something about the weather.

d)

Generate a Python script to calculate factorial.

10.

What is the term for a specific set of instructions or guidelines given to an AI model to generate a desired output?

a)

Dataset

b)

Prompt

c)

Model

d)

Algorithm

11.

What is the role of human oversight in addressing AI bias and hallucinations?

a)

Human oversight is unnecessary in modern AI systems.

b)

Humans should be responsible for identifying and correcting biases and hallucinations.

c)

Humans should be completely removed from the AI development process.

d)

Humans should only be involved in the initial stages of AI development.

12.

How can you improve the specificity of a prompt?

a)

By avoiding the use of specific keywords.

b)

By limiting the length of the prompt.

c)

By providing more details and constraints.

d)

By using vague language.

13.

What is the purpose of using specific keywords in a prompt?

a)

To limit the AI model's creativity.

b)

To confuse the AI model.

c)

To provide context and direction for the AI model.

d)

To increase the processing time of the AI model.

14.

Which of the following is a technique for improving prompt clarity?

a)

Using vague language.

b)

Using clear and concise language.

c)

Avoiding the use of specific keywords.

d)

Providing contradictory instructions.

15.

What is the ultimate goal of addressing AI bias and hallucinations?

a)

Creating AI systems that are completely unbiased and error-free.

b)

Minimizing the role of humans in AI decision-making.

c)

Developing AI systems that are more intelligent than humans.

d)

Building AI systems that are fair, transparent, and beneficial to society.

16.

What is the process of refining and optimizing prompts to achieve the best possible results from an AI model?

a)

Model training

b)

Hyperparameter tuning

c)

Data cleaning

d)

Prompt engineering

17.

What are AI hallucinations?

a)

The ethical concerns surrounding the use of AI

b)

The process of training AI models on large datasets.

c)

The ability of AI models to generate creative content.

d)

The generation of false or misleading information by AI models.

18.

Which of the following is NOT a potential solution to mitigate AI hallucinations?

a)

Improving data quality and quantity.

b)

Developing techniques to identify and correct hallucinations.

c)

Increasing transparency and explainability of AI models.

d)

Using more complex models.

19.

What are some potential consequences of AI bias?

a)

Unfair treatment of individuals and groups.

b)

Increased accuracy and efficiency.

c)

Improved decision-making.

d)

Reduced reliance on human judgment.

20.

What is a large dataset of text and code used to train AI models?

a)

Corpus

b)

Algorithm

c)

Model

d)

Prompt

21.

How can AI bias be mitigated?

a)

By increasing the computational power of AI systems.

b)

By using more complex algorithms.

c)

By carefully curating and cleaning training data.

d)

By using larger datasets.

22.

What is the benefit of using a hierarchical prompt structure?

a)

It limits the creativity of the AI model.

b)

It increases the processing time of the AI model.

c)

It makes prompts more difficult to understand.

d)

It helps break down complex tasks into smaller, more manageable steps.

23.

Why is it important to test and iterate on prompts?

a)

To identify and fix errors in the prompt.

b)

To ensure that the AI model always generates the same output.

c)

To limit the capabilities of the AI model.

d)

To make the prompt more complex.

24.

Which of the following is NOT a key principle of effective prompt engineering?

a)

Ambiguity

b)

Conciseness

c)

Clarity

d)

Specificity

25.

What is the primary goal of prompt engineering?

a)

To limit the capabilities of AI models.

b)

To trick AI models into generating specific outputs.

c)

To optimize prompts for maximum efficiency and effectiveness.

d)

To create complex and convoluted prompts.

26.

A face-to-face meeting between the employer and the applicant

a)

lunch date

b)

interview

c)

resume

d)

employment

27.

Which of these do you NOT include on a resume?

a)

education background

b)

work experience

c)

attitude

d)

qualifications

28.
Who should not be asked to be a reference? 
a)
Relatives
b)
Teacher
c)
Coach
d)
Youth Pastor
29.
Do you need to get permission before you use a person's name as a reference?
a)
Yes
b)
NO
30.

Resumes should be at least three pages long.

a)

True

b)

False

31.
Your resume should be...
a)
Full of information and unorganized 
b)
Easy to read
32.

What counts as experiences?

a)

Paid or unpaid employment

b)

Volunteering

c)

Internships

d)

All of the above

33.

Which category does NOT belong on your resume?

a)

Objective

b)

Work experience

c)

Awards

d)

Games you like to play

34.

What are hard skills?

a)

Skills that are gained through formal training, education or on the job

b)

Skills that you work hard to attain

c)

Skills that are hard to obtain

d)

skills that are hard

35.

What are soft skills?

a)

very light skills

b)

skills you don't use often

c)

a mix of social interpersonal skills and character traits that jobs require

d)

reflect your personality

36.

How can AI be used to detect plagiarism in academic writing?

a)

By analyzing the font style used in the document

b)

By checking the paper's publication date

c)

By counting the number of words in the text

d)

By analyzing text for similarities with existing sources, comparing sentence structures, word choices, and writing style, and training machine learning algorithms on a dataset of known plagiarized content.

37.

Can AI completely eliminate plagiarism in academic settings?

a)

No

b)

Not sure

c)

Yes

d)

Maybe

38.

How does AI compare to human experts in detecting plagiarism?

a)

AI can be more efficient in detecting plagiarism by analyzing large datasets quickly, but human experts may have a better understanding of context and nuances.

b)

AI has a better understanding of context and nuances than human experts

c)

Human experts are faster at analyzing large datasets compared to AI

d)

AI is less efficient than human experts in detecting plagiarism

39.
When Do I Need Permission to Copy?
a)
all the time 
b)
never
c)
sometimes
d)
whenever you feel like it
40.

What is the purpose of using a few-shot learning approach in prompt engineering?

a)

To increase the processing time of the AI model.

b)

To train the AI model on a large dataset.

c)

To limit the capabilities of the AI model.

d)

To provide the AI model with a few examples of the desired output.

41.

How does artificial intelligence learn?

a)

By sleeping

b)

By analyzing data

c)

By eating food

d)

By playing games

42.

Generative AI is like a ____.

a)

Creative robot

b)

Sleeping cat

c)

Flying bird

d)

Running dog

43.

AI is a computer program that is able to do things that often require ____.

a)

Human intelligence

b)

Animal instincts

c)

Plant growth

d)

Machine parts

44.

Which of the following best describes AI bias?

a)

The inability of AI to function without human intervention

b)

The tendency of AI to make decisions based on the data it was trained on

c)

The use of AI to improve data security

d)

The ability of AI to operate independently

45.

What distinguishes ChatGPT from traditional chatbots?

a)

ChatGPT uses pre-defined responses.

b)

ChatGPT relies solely on rule-based algorithms.

c)

ChatGPT can generate responses based on context and learned patterns.

d)

ChatGPT has a limited vocabulary.

46.

What is one limitation of ChatGPT's current version?

a)

Inability to understand sarcasm

b)

Limited vocabulary

c)

Slow response time

d)

Inaccuracy in predicting future events

47.

Why is it important to use AI responsibly?

a)

To make more money

b)

To protect privacy and security

c)

To watch more TV

d)

To eat more ice cream

48.

What is AI short for?

a)

Airplane

b)

Artificial Intelligence

c)

Animal Instinct

d)

Action Items

49.

What is a 'hallucination' in the context of AI?

a)

A dream about AI

b)

A type of computer virus

c)

An error where AI generates false information

d)

A new AI program