Course Catalogue

AI Ethics and Responsible Engineering Practice UESTC5025

  • Academic Session: 2026-27
  • School: School of Engineering
  • Credits: 10
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Semester 2
  • Available to Visiting Students: No
  • Collaborative Online International Learning: Yes
  • Curriculum For Life: No

Short Description

This course examines the ethical, social and regulatory challenges arising from the development and deployment of artificial intelligence in engineering contexts. Students will critically evaluate frameworks for responsible AI design, explore real-world case studies involving algorithmic bias, transparency, accountability and sustainability, and develop practical strategies for embedding ethical considerations into engineering practice. The course is designed for students on the MSc Electronics and Electrical Engineering with Business Management (UESTC) programme seeking to lead responsibly in an AI-driven world.

Timetable

Weekly 2-hour sessions over 12 weeks: 1-hour lecture followed by 1-hour seminar. Lectures introduce key concepts and theoretical frameworks; seminars involve case study discussions, group debates, and peer critique activities.

Requirements of Entry

None

Excluded Courses

None

Co-requisites

None

Assessment

Coursework essay (60%): a 3000-word ethics assessment paper for a specific AI application scenario, critically evaluating ethical risks and proposing responsible engineering strategies.

Class presentation (40%): in groups, students will prepare and deliver a 20-minute debate or presentation on a controversial AI ethics topic, demonstrating their ability to communicate and defend ethical positions.

Course Aims

This course aims to develop students' critical understanding of the ethical, social and regulatory dimensions of artificial intelligence, and to equip them with practical frameworks for embedding responsible and sustainable practices into engineering design, development and deployment.

Throughout the course, students will focus on:

1. Foundations of AI ethics, including key ethical theories and principles as they apply to the design and use of intelligent systems

2. Algorithmic fairness and bias, in which you will learn to identify, measure and mitigate bias in AI systems

3. Transparency, explainability and accountability in AI-driven decision-making

4. Regulatory and governance frameworks, including the EU AI Act and emerging global standards for responsible AI

5. Societal and environmental impacts of AI, examining sustainability, labour displacement and digital inequality

6. Privacy, data protection and surveillance, exploring the ethical boundaries of data collection and use

7. Responsible engineering practice, in which you will develop strategies for embedding ethical considerations into the full AI system lifecycle - from design through deployment and beyond

Intended Learning Outcomes of Course

By the end of this course, students will be able to:

1. Critically evaluate ethical theories and principles for AI

2. Identify, analyse and mitigate algorithmic bias

3. Assess transparency, explainability and accountability requirements

4. Apply regulatory frameworks (e.g. EU AI Act)

5. Analyse societal and environmental impacts of AI

6. Evaluate ethical boundaries of data collection and privacy

7. Develop responsible engineering strategies for the AI lifecycle

Minimum Requirement for Award of Credits

No exceptions