Course Outline

Contents

• Course Details
• Course Summary
• Assumed Knowledge
• Learning Outcomes
• Teaching Strategies
• Student Conduct
• Assessment
• Course Schedule
• Resources for Students
• Course Evaluation and Development

Course Details

Course Code	COMP4920
Course Title	Ethics in computer science
Convenor	Sebastian Sequoiah-Grayson
Admin	Philip Quadrio Adam Smallhorn
Classes	Lectures : Mondays 14:00 - 16:00 - Keith Burrows Theatre (K-J14-G5). Wednesdays 14:00 - 16:00 - Keith Burrows Theatre (K-J14-G5).
Consultations	Thursdays in Room 212 in K17 - (Seb's office): 15:30 - 17:30. Please email Seb or Philip Quadio (admin) about anything and everything - Seb: ssg@cse.unsw.edu.au, Philip: p.quadrio@unsw.edu.au.
Units of Credit	6
Course Website	http://cse.unsw.edu.au/~cs4920/24T1/
Handbook Entry	http://www.handbook.unsw.edu.au/undergraduate/courses/current/COMP4920.html
Student Reps	Please email the stureps if you have any concerns with this course that you think might require student representation. They will pass these concerns on anonymously to the relevant people in order to to get the issues resolved - stureps@cse.unsw.edu.au. NOTE - Please do not email the stureps for course-admin issues. For course-admin issues, email admins Philip Quadrio or Adam Smallhorn directly at p.quadrio@unsw.edu.au, a.smallhorn@unsw.edu.au.

Course Summary

In this course we will explore ethical issues for computer science, widely conceived. We will examine in detail the nature of ethical claims/moral judgements themselves, and how it is that our beliefs about their nature can affect our understanding of the ethical issues relating to computer science that we will examined far. We will learn about ethical arguments, and how to construct and evaluate them. We will cover utilitarian, deontological, and virtue ethics, and run test cases past real-world computer science cases. We will learn to engage critically with research ethics, as well as the relationship between ethical responsibility and AI frameworks and innovation. There will be considerable discussion of "ethics washing" - the pretence of ethical reasoning by those in positions of power for the purpose of avoiding regulation, As well as explore the related issues of trust, accountability, and privacy in our current online, informationalised world. We will explore equity, bias and fairness in algorithmic and dataset design, as well as the ethics of AI more broadly. We will also explore the ethical ramifications of transparency and explainability - along with their attendant relationships with power, as they relate to computer science in general.

PLEASE COME TO THE IN-PERSON LECTURES...THERE WILL BE SNACKS : )

NOTE - TUTORIALS START IN WEEK 1

Assumed Knowledge

There is no assumed knowledge, but you will need a strong sense of adventure and a willingness to engage with a lot of challenging, open-ended material!

Learning Outcomes

After completing this course, students will be able to:

* articulate the major normative and meta-ethical theories that underpin real, research-level moral debates in both academic and professional contexts.

* define and employ ethical values, principles, and practices for responsible research and innovation of technological and computing advances.

* build, articulate, and justify their own moral arguments - as well as how to analyse moral judgements and moral arguments in general.

* be aware of the ethical issues and pitfalls in their own professional practice of developing novel technologies, including AI (e.g. fairness, transparency, accountability), and learn about existing efforts to mitigate these issues.

* openly and robustly discuss ethical dilemmas around specific technological case studies.

Teaching Strategies

• Lectures ... introduce concepts, show examples
• Tutorials ... reinforce concepts and provide additional examples - TUTORIALS START IN WEEK 1.

Student Conduct (please do read the plagiarism material)

Be excellent to each other.

Be excellent to yourselves.

Also the following is wordy, but important - The Student Code of Conduct ( Information , Policy ) sets out what the University expects from students as members of the UNSW community. As well as the learning, teaching and research environment, the University aims to provide an environment that enables students to achieve their full potential and to provide an experience consistent with the University's values and guiding principles. A condition of enrolment is that students inform themselves of the University's rules and policies affecting them, and conduct themselves accordingly.

In particular, students have the responsibility to observe standards of equity and respect in dealing with every member of the University community. This applies to all activities on UNSW premises and all external activities related to study and research. This includes behaviour in person as well as behaviour on social media, for example Facebook groups set up for the purpose of discussing UNSW courses or course work. Behaviour that is considered in breach of the Student Code Policy as discriminatory, sexually inappropriate, bullying, harassing, invading another's privacy or causing any person to fear for their personal safety is serious misconduct and can lead to severe penalties, including suspension or exclusion from UNSW.

If you have any concerns, you may raise them with your lecturer, or approach the School Ethics Officer , Grievance Officer , or one of the student representatives.

Plagiarism is defined as using the words or ideas of others and presenting them as your own. UNSW and CSE treat plagiarism as academic misconduct, which means that it carries penalties as severe as being excluded from further study at UNSW. There are several on-line sources to help you understand what plagiarism is and how it is dealt with at UNSW:

• Plagiarism and Academic Integrity
• UNSW Plagiarism Procedure

Make sure that you read and understand these. Ignorance is not accepted as an excuse for plagiarism. In particular, you are also responsible that your assignment files are not accessible by anyone but you by setting the correct permissions in your CSE directory and code repository, if using. Note also that plagiarism includes paying or asking another person to do a piece of work for you and then submitting it as your own work.

UNSW has an ongoing commitment to fostering a culture of learning informed by academic integrity. All UNSW staff and students have a responsibility to adhere to this principle of academic integrity. Plagiarism undermines academic integrity and is not tolerated at UNSW. Plagiarism at UNSW is defined as using the words or ideas of others and passing them off as your own.

If you haven't done so yet, please take the time to read the full text of

• UNSW's policy regarding academic honesty and plagiarism

The pages below describe the policies and procedures in more detail:

• Student Code Policy
• Student Misconduct Procedure
• Plagiarism Policy Statement
• Plagiarism Procedure

You should also read the following page which describes your rights and responsibilities in the CSE context:

• Essential Advice for CSE Students

Auf...okay that was pretty long. Are you still reading this? Good. The next bit is about assessments and the course schedule....

Assessment

Item	Topics	Due	Marks
Essay 1	Weeks 1-3	Week 4 - Monday March 4, 18:00.	20%
Essay 2	Weeks 1-5	Week 7 - Monday March 25, 18:00.	30%
Group presentation	Weeks 1-10	Weeks 9 and 10 in tutorials. (marked collectively)	20%
Group report	Weeks 1-10	Week 11 - Friday April 26, 18:00. (marked individually)	30%

Course Schedule

Week	Lectures	Tutes		Assignments	Lecturer
1	Monday - Overview and Utilitarianism Wednesday - Deontological Ethics and Virtue Ethics	Week 1's lecture content			Seb and Inky both days
2	Monday - Meta-ethics Wednesday - Extractivism and Ethics Washing	Week 2's lecture content			Seb and Inky both days
3	Monday - Ethics in Computing and Research Integrity Wednesday - Leadership, and Professionalism + Academic Writing	Week 3's lecture content			Flora Salim on Monday Seb and Inky on Wednesday
4	Monday - Trust, Automation, and Value Sensitive Design Wednesday - Cybersecurity ethics: research and practice	Week 4's lecture content		Essay 1 due, Monday March 4, 18:00.	Flora Salim on Monday Seb and Inky on Wednesday
5	Monday - Accountability, fairness, and transparency: from humans to machines Wednesday - AI bias and fairness	Week 5's lecture content			Seb and Inky on Monday Flora Salim on Wednesday
6	FLEX WEEK	FLEX WEEK		FLEX WEEK	FLEX WEEK
7	Monday - Transparency and XAI Wednesday - Fairness and algorithms	Week 7's lecture content		Essay 2 due - Monday March 25, 18:00.	Flora Salim on Monday Haris Aziz and Xinhang Lu on Wednesday
8	Monday - NO LECTURE - Easter Monday Holiday Wednesday - Assertion, agency, and artificial general intelligence	Week 8's lecture content			Emanuel Viebahn on Wednesday
9	Monday - Foundations models and time-series data Wednesday - Human centred design and smart cities	Week 9's lecture content + GROUP PRESENTATIONS		Tutorial presentations	Hao Xue on Monday Erika Whillas on Wednesday
10	Monday - What is at stake with AI and creative work? Wednesday - Course summary	Week 10's lecture content + GROUP PRESENTATIONS		Tutorial presentations	Oliver Bown on Monday Seb and Inky on Wednesday
11				Group Report (based upon Group Presentations) due - Friday April 26, 18:00.
12	Good luck with your exams!

Resources for Students

Please see Course Work>Lectures>Readings in the menu bar up there on the left for your weekly readings :)

Course Evaluation and Development

This course is evaluated each session using the MyExperience system.

This course is being redesigned continually! Firstly, the entire content and structure, from the lectures and tutorials, to the assessments, was new for Term 3, 2022, and Flora and I (Seb) have been refining it constantly since then. It was a big adventure, a little bit of work, and a whole lot of fun.

Everyone's feedback at the end of 2022 and across 2023 meant the world, and we really do mean this :) There were pages and pages of fantastic suggestions, and we have tried to implement as many of them as we can.

For just some examples.... We have a new new options for the essay due in Week 4. This will be marked quickly with lots of feedback so that you can use it to inform your approach to the second essay due in Week 7 (which has new options also). Also, the specs for the group presentation and group report are being overhauled completely. Plus the group presentation will now be marked collectively, with the group report being marked individually (this is the inverse of 2022). Most excitingly of all, there were lots of really super suggestions for topics and content across 2023. We are weaving some of the best ones into the course, as well as rearranging the structure somewhat.

Remember - we need you! Thanks for reading all of this - see you in the lectures :)