While the use of traditional technologies and processing of information has always provided controllers with the
capability to do real harm in society, the move into the digital space has exacerbated this potential for harm in
new and unexpected or unanticipated ways. Hence professionals in this area need to be familiar with tools to
identify and address these potential harms.
Digital ethics deals with the impact of digital Information and Communication Technologies (ICT) on individuals,
our societies and the environment at large. It covers a wide spectrum of societal and ethical impacts including
issues such as data governance, privacy and personal data, Artificial Intelligence (AI), algorithmic decision-making
and pervasive technologies.
The prevalence of reporting ethics scandals in the tech sector has increased substantially. Unethical businesses
are losing favour with consumers with a variety of evidence highlighting how consumers stop buying from brands
they deem to be unethical. This module will look at ethics and its applicability to technology in areas such as artificial
intelligence, data science, robotics, algorithms and usability.
This module addresses a number of objectives:
(a) To educate learners on the ethical challenges inherent in rapidly developing technologies.
(b) To provide learners who are employed as lecturers with the knowledge and confidence to be able to
incorporate ethics into the design of their learning and learning activities.
(c) To provide learners who are employed as professionals in the Information and Communications
technology industry with the knowledge to lead and disseminate in the area of ethics in technology.
The module is intended to motivate learners to critically assess technologies from the perspective of the major
ethical frameworks. Learners who successfully complete the module will be prepared to enhance their own
practice and guide others in the development of ethical practices in the design, implementation and use of digital
technology.
Introduction to Ethics:
• Major ethical frameworks and their application to digital or computer ethics• Range of ethical theories, approaches, and perspectives• Argumentation and Rational Thinking• Introduction to ethics in technology.
Main laws regulating technology:
• Legal ethics• GDPR• EU legislation• Data Protection legislation.• Regulation of artificial intelligence
Professional Ethics & General Code of Ethics:
• Corporate Governance & Regulations• Human Resources, Finance• Professional boundaries• Professional negligence• Professional responsibility• Examples of Codes of Ethics
Ethical Frameworks:
• Software Engineering Code of Ethics and Professional Practice (ACM/IEEE-CS)• Computer Ethics Institute (CEI) 10 commandments• ACM Code of Ethics and Conduct• Ethical guidelines for Trustworthy AI• BCS Codes of Conduct and Practice• Electronic Frontier Foundation• Responsible AI
Data Ethics:
• Bias in Data• Confidence in Data (Dataset size)• Visualisation biasing• Data privacy• Statistical biasing• Unacknowledged data collection (GPS tracking, microphone, and camera activation without the user’sconsent)• Undertaking a Data Protection Impact Assessment (DPIA)
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.
Usability Ethics:
• Dark Patterns• Accessibility• Universal Design• Globalisation• Internationalisation• Localisation ethical challenges• Technophobia.
Robot Ethics:
• Driverless Cars• Drones• Internet of Things• Home Assistants (Suri, etc.).
Student Ethics:
• Plagiarism• Email and Social Media use and abuse• Integrity, Confidentiality, Accountability• Conflicts of Interest• Fundraising.
Research Ethics and Data Collection:
• Informed Consent• Right to withdraw• Safeguarding users• Data Management e.g., anonymisation/Pseudonymisation• Terms and Conditions
Introduction to Teaching:
Models of Learning, Instructional Design, and Assessment practices.
Further Details:
It is envisioned that this module will be delivered in a range of different contexts, and specifically the content has
been designed with two specific approaches in mind:
1. Traditional Classroom Delivery (Full Semester): This approach will mean that the module is delivered
in one semester in a classroom. Contact hours will be 3 hours per week which will be used to cover both
theoretical content and practical sessions, with a two hour lecture and one hour lab.
2. Blended Delivery (Full Semester): This approach will mean that the module is delivered over one
semester, with the majority of the teaching content being delivered on-line (with three weeks of lectures and labs
being delivered in the classroom).
| Module Content & Assessment | |
|---|---|
| Assessment Breakdown | % |
| Other Assessment(s) | 100 |