MEng Electrical and Electronic Engineering

Year of entry: 2024

Course unit details:
AI: robot overlord, replacement, or colleague?

Course unit fact file
Unit code UCIL20122
Credit rating 10
Unit level Level 2
Teaching period(s) Semester 2
Offered by Division of Informatics, Imaging and Data Sciences
Available as a free choice unit? Yes

Overview

Artificial intelligence (AI), the ability of machines to learn from data, make decisions and perform actions, is now creeping into every aspect of our lives. This unit explores the mechanisms, implications and ethics of an environment where AI plays an increasingly important role.

  • We will consider the science behind the headlines to help you develop an informed opinion regarding the complexities of the use of AI in society
  • We will discuss the conceptual frameworks behind AI methodologies and the sources of the data on which they operate
  • We will provide an introduction to computational thinking. What sort of problems can AI realistically be expected to help with?
  • There will be an in depth analysis of a series of case studies highlighting the use of AI in work and society
  • You will work alongside students from a wide range of disciplines, to understand the benefits and opportunities AI offers now, and how this might change in the future

If you are interested in the ways in which AI impacts on society, but have not had the opportunity to study it, this is the unit for you. The unit does not assume any background knowledge.

This online unit, delivered via Blackboard, is made up of online modules that are released at intervals. The unit is highly interactive and adopts a blend of approaches including video inputs and case studies.

Pre/co-requisites

UCIL units are designed to be accessible to undergraduate students from all disciplines.

UCIL units are credit-bearing and it is not possible to audit UCIL units or take them for additional/extra credits. You must enrol following the standard procedure for your School when adding units outside of your home School.

If you are not sure if you are able to enrol on UCIL units you should contact your School Undergraduate office. You may wish to contact your programme director if your programme does not currently allow you to take a UCIL unit.

You can also contact the UCIL office if you have any questions.

Aims

This unit will demystify AI, explaining how it works, and demonstrating its limitations. Its overarching aim is to equip Manchester graduates from all disciplines with an understanding of the impact this technology currently has, the way this is likely to change in the future and, crucially, the ability to grasp the opportunities it brings, whatever your chosen career.

Learning outcomes

On successful completion of the unit, you will be able to:

  • Describe and review the basic concepts underlying AI and Machine Learning
  • Identify and debate the impact of AI on society both now and in the future, and from diverse, interdisciplinary and non-technical viewpoints
  • Employ computational thinking approaches to formulate a problem in such a way that a computer can tackle it
  • Critically evaluate AI applications in an innovative and socially responsible way towards ensuring that technology is used in the future to improve the way we work and live
  • Collaborate within a team to analyse and evaluate a case study

Syllabus

Examples of topics covered:

  • Can you get a machine to learn? Finding out what AI can do (and more importantly, what it can't do)
  • Can AI help your business grow? Using big data to target your ecommerce activity
  • Do humans or machines make better drivers? The importance of 'systems thinking' in the human-technology relationship
  • What is the impact of AI on our legal system? Can robots make fair and ethical decisions?
  • Can robots care? The use of robots in social care

Teaching and learning methods

The module is delivered entirely online via Blackboard, although introductory sessions will be organised to help introduce students to the topic and the way in which it will run.

Employability skills

Analytical skills
Essay and group work require research and analysis of information.
Group/team working
Group work element in assessment.
Project management
Problem solving
Research
Written communication

Assessment methods

Method Weight
Other 20%
Written assignment (inc essay) 50%
Project output (not diss/n) 30%

1. Essay (50%)

2. Group case study (30%)

3. Project (20%)

Feedback methods

  • Formative feedback will be provided by tutors on the online group work
  • Summative assessment will be provided through peer-assessment of the group work
  • Formative feedback will be provided on a draft of the essay before submission

Study hours

Scheduled activity hours
Lectures 15
Seminars 10
Independent study hours
Independent study 75

Teaching staff

Staff member Role
Andrew Brass Unit coordinator
Caroline Jay Unit coordinator
Iliada Eleftheriou Unit coordinator

Return to course details