Computer Ethics and GenA

Use AI as a support tool

not as a substitute for your own thinking, learning, and authorship.

What did this powerpoint talk about?

Honesty, Judgement, Accountability

Why ethics and GenAI belong in a CS course

Technical skill matters — but so do judgment, integrity, privacy, and responsibility.

Why ethics and GenAI belong in a CS

course includes...

Honesty, Fairness, Privacy, Accountability

Honesty

Say what work is yours, what

help you used, and what you

actually understand.

Fairness

Do not gain an unfair advantage

over classmates by outsourcing

the learning.

Privacy

Protect personal data, course

materials, proprietary code,

and other sensitive

information.

Accountability

You are responsible for every

line, claim, citation, and

submission with your name on

it.

In practice, this means:

✓Try the problem

yourself before asking

AI.

✓ Use AI to support

learning, not replace it.

✓ Check outputs for

errors and bias.

✓ Disclose or cite AI use

when required.

✓ Ask if a use case feels

unclear

Ethical computing is not an

extra topic;

it is part of being a

competent computer scientist.

What GenAI can help with

Allowed uses should make you a better learner, writer, programmer, and debugger — not

replace your role.

What GenAI can help...

✓ Brainstorming ideas or test cases before you start

coding.

✓ Explaining an error message, algorithm, or concept in

simpler language.

✓ Generating practice problems, flashcards, or study

guides for review.

✓ Improving readability: naming, comments, formatting,

or documentation.

✓ Comparing approaches after you have attempted the

work yourself.

DO Use AI to support understanding — and be ready to

explain every part of your final work.

What GenAI must not do for you

If the tool replaces your authorship, hides misconduct, or creates unfair advantage, it crosses

the line.

What GenAI must not do for you...

! Submitting AI-generated code, prose, or answers as if

they were entirely your own.

! Using AI during quizzes, exams, or restricted

assessments unless explicitly permitted.

! Pasting in private data, another student's work, or

proprietary / licensed course material.

! Fabricating citations, results, sources, experiments, or

references.

! Hiding your AI use when the assignment or instructor

requires disclosure.

Rule of thumb: if the AI is doing the learning, reasoning, or

authorship for you, do not submit it.

Use this workflow every time you use AI

ask, think, check,cite, own it

A simple decision process can keep your work

ethical, accurate, and course-compliant.

Best practice:

keep a short record of how you used AI prompts, what you accepted, and what you changed.

Traffic-light examples

green,yellow,red,red

Green

"Give me five extra test cases for my sorting

program."

AI supports practice and debugging; you still design, code, and

evaluate the solution

Yellow

Rewrite my explanation so it sounds more

polished."

This may be okay, but only if the ideas are yours and the

assignment allows editing help.

Red

"Solve the assignment and give me the final code

to submit."

Not okay. The tool is replacing your authorship and the learning

the task is meant to assess.

RED 2

Here is another student's code. Improve it for

me."

Not okay. This risks privacy, plagiarism, and misuse of someone

else's work.

Bottom line for students

If a use is not clearly allowed, do not guess — ask first.

Your personal checklist before

submitting:

✓I understand every part of the work.

✓ I tested the output and corrected

errors.

✓ I did not upload private or restricted

material.

✓ I disclosed AI help if the course

requires it.

✓ The final submission is genuinely

mine.

Remember

-AI can be a useful tutor, editor, explainer, or

brainstorming partner.

-It cannot become the real author of your

coursework.

-When in doubt, ask your instructor before

you submit.

What is one principle of the ACM Code of Ethics for Computer Scientists?

Contribute to society and human well-being.

What should computer scientists avoid when designing computing systems?

Harm.

What is expected of computer scientists in their professional work?

To be honest and trustworthy.

What should computer scientists respect according to the ACM Code of Ethics?

Privacy, intellectual property, and confidentiality.

What responsibility do computer scientists have regarding computing systems?

For the quality and impact of computing systems.

What can generative AI produce?

Incorrect or fabricated information.

What may AI-generated code include?

Non-existent libraries or incorrect APIs.

What can hallucinated code introduce?

Bugs or security vulnerabilities.

What must developers do with AI-generated outputs?

Review, test, and validate them.

AI Risk Stack

Human oversight, privacy risks, security vulnerabilities, hallucinations, bias & fairness

AI Hallucination Flow

Student prompt, AI Model Generates Code, Incorrect/Invented API, Student Does not Verify, Bug or vulnerability

Discussion: Ethical AI

Use in Programming

Should AI-generated code require

disclosure in coursework?

• How can developers verify AI-generated

solutions?

• What risks occur when students rely too

heavily on AI?

• How should industry regulate AI-assisted

software development?