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Module

CSC8801 : AI Fundamentals and Responsible Innovation (Inactive)

  • Inactive for Year: 2025/26
  • Module Leader(s): Dr Tejal Shah
  • Co-Module Leader: Dr Dan Nesbitt
  • Owning School: Computing
  • Teaching Location: Newcastle City Campus
Semesters

Your programme is made up of credits, the total differs on programme to programme.

Semester 1 Credit Value: 10
ECTS Credits: 5.0
European Credit Transfer System

Aims

This module aims to provide a comprehensive introduction to AI through a dual approach of theoretical understanding and practical awareness. Students will gain a foundational understanding of core AI concepts that form the building blocks of AI systems and their applications in real-world AI-driven solutions. Students will also learn about the guiding principles for responsible, safe, and ethical usage/applications of AI technologies. Viewed from the critical lens of responsibility in innovation, students will learn to navigate ethical dilemmas, legal dimensions, and social issues including environmental impacts of AI technologies. By engaging with standardised frameworks, students will learn to apply the core AI principles in practice.

Outline Of Syllabus

Following is a broad overview of topics:
• Introduction to AI: what is intelligence, what is AI, history and evolution of AI
• AI terminology and types of AI
• AI core concepts (building blocks of AI): ML, big data, NLP, computer vision, knowledgebased systems, autonomous systems
• Introduction to Generative AI and prompt engineering
• AI principles (UK Government and OECD) and frameworks (RRI) for responsible innovation
• Ethical considerations of AI technologies including data privacy and bias
• The future of AI – generative AI, AGI, superintelligence

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Guided Independent StudyAssessment preparation and completion130:0030:00Group work on assessment
Scheduled Learning And Teaching ActivitiesLecture42:008:00PiP lectures on core concepts
Guided Independent StudyDirected research and reading101:0010:00A flipped classroom approach, students will undertake research/activity individually and asynchronously
Scheduled Learning And Teaching ActivitiesSmall group teaching42:008:00Group seminars (PiP) discussing use cases, primarily focused on Responsible AI including ethics, regulations, and social impact; interactive activities with AI tools
Guided Independent StudyStudent-led group activity101:0010:00Directed group work by students without staff present
Scheduled Learning And Teaching ActivitiesDrop-in/surgery41:004:001 hour synchronous, online drop-in sessions for follow-up/questions
Guided Independent StudyIndependent study130:0030:00Independent study on course content
Total100:00
Teaching Rationale And Relationship

The teaching methods combine traditional lectures with group seminars based on case studies so that students
can explore the topics covered in both a theoretical and real-world context. The core concepts will be delivered
through traditional lectures whereas the rapidly evolving and contextual topics of ethics and law will be discussed during group seminars where students will have a chance to discuss, shared ideas, and work on activities/case studies.

Lecture material maybe be pre-recorded and students have the opportunity to watch the videos ahead of the
lecture (flipped classroom). Lecture follow up will consist of Q&A about the lecture material.

Assessment Methods

The format of resits will be determined by the Board of Examiners

Other Assessment
Description Semester When Set Percentage Comment
Report1A100Group coursework covering Semester 1 taught material.
Formative Assessments

Formative Assessment is an assessment which develops your skills in being assessed, allows for you to receive feedback, and prepares you for being assessed. However, it does not count to your final mark.

Description Semester When Set Comment
Written exercise1MQuiz questions for students to review their learning and understanding of the taught content.
Assessment Rationale And Relationship

The report will test the students’ understanding of the core concepts of AI and how to develop/use AI in a responsible manner through ethical, legal, and social lenses. Given the breadth of the topic, students will work in groups for the assessment to benefit from peer learning and different perspectives. The quiz questions will enable students to reflect and review their own learning.

Reading Lists

Timetable