Course syllabus - Digital Ethics for Teachers in Higher Education

Objectives

There is an increasing need for the inclusion of ethical aspects in computer science courses, which means that teachers need the knowledge, skills and tools to teach them. In this course, we will explore how to teach the subject, by providing a general overview of ethical technology and teaching theories, followed by an in-depth exploration of specific ethical case studies. 

The aim of this course is to: 

1. Motivate the students to examine technologies from the perspective of ethics 
2. Provide the students with the knowledge and skills to teach ethical content in CS courses.
3. Critically assess technologies to examine their ethical implications.

Learning outcomes

After completing the course, the student should be able to: 

1. Demonstrate a clear understanding of the common principles and models of ethics, and how they relate to a variety of technologies.  
2. Critically assess and evaluate existing ethical case studies.  
3. Review and assess relevant literature, incorporating legislation, policy, directives, academic journals and industry standards as they relate to ethical technologies.  
4. Select and employ the use of different teaching approaches for a specific ethics content. 
5. Compare and contrast different ethical dilemmas. 
6. Relate topics such as gender, race, nationality, ethnic group, and age to the study of ethics in technology.

Course content

Introduction to Ethics: The Principle of Respect for autonomy, The Principle of Beneficence, The Principle of nonmaleficence, The Principle of justice. Ethical philosophers (Socrates, Epictetus, Jeremy Bentham, John Stuart Mill, Immanuel Kant, and Norbert Wiener). 

Data Ethics: Bias in Data (racism, sexism, etc.), Confidence in Data (Dataset size), Visualisation biasing, Statistical biasing, unacknowledged data collection (GPS tracking, microphone, and camera activation without the user's consent), GDPR and Data Protection legislation. 

Algorithmic Ethics: Bias in algorithms (racism, sexism, etc.), Lack of explainability of some algorithms, value-based development, Software Testing as an ethical imperative, computer security as an ethical imperative, Selective Censorship of WWW content. Personalisation of WWW content. 

Robot Ethics: Driverless Cars, Drones, Internet of Things, Home Assistants (Suri, etc.). 

Usability Ethics: Dark Patterns, Accessibility, Universal Design, Globalisation, Internationalisation, and Localisation ethical challenges, Technphobia. 

Ethical Hacking: Cybercrime, Legal responsibility, computer security, technological and tools.

Student Ethics: Plagiarism, email and Social Media use and abuse, Integrity, Confidentiality, Accountability, Conflicts of Interest, Fundraising.  

Ethical Frameworks: Software Engineering Code of Ethics and Professional Practice (ACM/IEEE-CS), Computer Ethics Institute (CEI) 10 commandments, BCS Codes of Conduct and Practice, Electronic Frontier Foundation. 

Informed Consent: Ethical Research, Terms and Conditions, Right to withdraw, anonymity. 

Case Studies: Cambridge Analytica and Facebook, National Newspapers of Ireland 2012 Threat, Driverless car fatalities. Computer Security failures, Computer Testing failures, Green IT, Doxxing.

Specific requirements

Computer Science teacher in higher education.

Examination

Seminarium (SEM), Active participation in seminars, 3 credits, examining the learning outcomes 1, 5 and 6, marks Fail (U) or Pass (G). 
Project (PRO1), An assignment that is presented with a report and a demonstration of the project, 2 credits, examines the learning outcomes 2, 3 and 4, marks Fail (U) or Pass (G).

A student who has a certificate from MDU regarding a disability has the opportunity to submit a request for supportive measures during written examinations or other forms of examination, in accordance with the Rules and Regulations for Examinations at First-cycle and Second-cycle Level at Mälardalen University (2020/1655). It is the examiner who takes decisions on any supportive measures, based on what kind of certificate is issued, and in that case which measures are to be applied.

Suspicions of attempting to deceive in examinations (cheating) are reported to the Vice-Chancellor, in accordance with the Higher Education Ordinance, and are examined by the University’s Disciplinary Board. If the Disciplinary Board considers the student to be guilty of a disciplinary offence, the Board will take a decision on disciplinary action, which will be a warning or suspension.

Grade

Pass, Fail