Module code: MANM574

Module Overview

This module offers an introduction to the use of AI in society, work, media and communication, government and policy. It puts people - as opposed to technology - at the centre of AI, and highlights core considerations in planning for AI applications as a response to issues and considerations in the society. This is done by exploring varied positions of users and stakeholders in relation to AI, examining the suitability of AI and associated tools and methods to the productivity/progress/propagation in society. In this module we discuss the opportunities, but also the challenges, risks, threats and ethical implications involved in the use of AI in society.

Module provider

SOL - Computer Science and Elec Eng

Module Leader

HERAVI Bahareh (SBS)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 7

Module cap (Maximum number of students): N/A

Overall student workload

Independent Learning Hours: 102

Tutorial Hours: 4

Guided Learning: 33

Captured Content: 11

Module Availability

Semester 2

Prerequisites / Co-requisites


Module content

Indicative content includes:
AI in society. 
AI bias and algorithmic accountability.
AI at work.
AI and policy.
AI and authority.
AI and media.

Assessment pattern

Assessment type Unit of assessment Weighting
Coursework Proposal for final essay 30
Coursework Final critical essay 70

Alternative Assessment


Assessment Strategy

The assessment strategy for this module is designed to provide students with the opportunity to demonstrate subject-specific knowledge and a critical understanding of the use of AI in the society inline with the learning outcomes.
The summative assessment for this module consists of an abstract proposal for the final project/essay and a final critical project/essay. The topics and details will be provided during the term.
Formative assessment and feedback will be in the form of question and answer during tutorials and discussion forums.

Module aims

  • The aim of this module is to equip students with the knowledge, skills and ability to critically understand and address issues in the use of AI in society. The use of AI will be explored in both a restorative and progressive context.

Learning outcomes

Attributes Developed
001 Demonstrate an understanding of the role of AI in society. CT
002 Describe and critically evaluate opportunities and risks that data and computational tools and methods bring to society, work, media, and policymaking. KCPT
003 Recognise and articulate ethical implications in the use of AI in society. KC
004 Be able to conceptually codify elements of a societal issue for the purpose of matching AI powered resolutions. KP

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

Methods of Teaching / Learning

The learning and teaching strategy promotes critical thinking, problem-solving and active engagement. The mode of delivery is online and will include captured content and tutorials, along with guided learning and independent learning.

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list
Upon accessing the reading list, please search for the module using the module code: MANM574

Other information

This module explores dynamic and fast changing topics. As such, the reading list is dynamic and the most appropriate and up-to-date readings will be provided during the semester.
We are committed to developing graduates with strengths in Employability, Digital Capabilities, Global and Cultural Capabilities, Sustainability, and Resourcefulness and Resilience. This module is designed to allow students to develop knowledge, skills, and capabilities in the following areas:
Employability: The module aims to develop critical understanding and skills that are highly significant in the workplace for an AI specialist, with a view to supporting design choices that are grounded in the societal needs, people-centred and well-informed. 
Global and cultural capabilities: The module addresses issues around the assumptions that underpin people-centred approaches in various domains concerning AI, and allows students to gain global and cultural awareness to design AI systems that are accessible and inclusive. Students are prepared to understand the importance of critical thinking and to think about the consequences of their choices with respect to AI design and development.
Digital capabilities: This module places a special focus on the relationship between societal needs and opportunities, and technology. Students develop critical thinking skill needed for effective development and use of technology in society.
Resourcefulness and resilience: Students are encouraged to see themselves as engaged in a process of continual development of their theoretical understanding and, through class discussions, to help one another to develop in their ability to explore ideas in a respectful, open and supportive environment.
Sustainability: Students will be equipped with the knowledge, tools and motivation needed to support and enact positive change in relation to the implementation of AI in society in a range of contexts.

Programmes this module appears in

Programme Semester Classification Qualifying conditions
People-Centred Artificial Intelligence (Online) MSc 2 Compulsory A weighted aggregate mark of 50% is required to pass the module

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2025/6 academic year.