- UCAS course code
- HHH6
- UCAS institution code
- M20
Course unit details:
AI: robot overlord, replacement, or colleague?
Unit code | UCIL20122 |
---|---|
Credit rating | 10 |
Unit level | Level 2 |
Teaching period(s) | Semester 2 |
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 |
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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 | |
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Lectures | 15 |
Seminars | 10 |
Independent study hours | |
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Independent study | 75 |
Teaching staff
Staff member | Role |
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Andrew Brass | Unit coordinator |
Caroline Jay | Unit coordinator |
Iliada Eleftheriou | Unit coordinator |