SUSTAINABILITY AND ARTIFICIAL INTELLIGENCE - 2025/6

Module Overview

This module explores the application of Artificial Intelligence (AI) to environment and sustainability challenges, showing the potential of AI to help create solutions for sustainable development and drive meaningful change. AI can help address global challenges and support meeting the UN¿s Sustainable Development Goals through facilitating understanding of complex systems and optimising resource use. The module provides an introduction to AI, covering both theoretical concepts and practical applications in sustainability. The module examines the inter-relationship between AI, media and sustainability. Students will engage with accessible AI tools and platforms to develop AI-driven solutions for sustainability challenges.

Module provider

Centre for Environment & Sustainability

Module Leader

ANDRIES Ana (Sust & CEE)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 5

Module cap (Maximum number of students): 250

Module Availability

Semester 1

Prerequisites / Co-requisites

N/A

Module content

Sustainability of AI:
-Principles of AI ¿ understanding Natural Language Processing models, Machine Learning, fuzzy logic, neural networks, supervised and unsupervised machine learning, and Generative AI models.
-Powering AI ¿ the energy demands and carbon emissions of AI
-Ethics and social justice of AI
-AI, sustainability and the media
-Governance of AI including risk management

AI for Sustainability:
-AI and the SDGs
-Environmental monitoring and data analysis
-AI applied to climate change modelling and prediction
-Emerging AI technologies and applications

AI tools supporting academic learning and academic research and sustainability:
-AI supported literature reviews
-AI data analysis with tools such as Azure AI studio
-AI supported social media content production (video editing, text editing, etc.)
-Introduction to Python for AI applications

Assessment pattern

Alternative Assessment

The production of AI edited documentary video assignment would be an inidividual piece, rather than a group work piece. 

Assessment Strategy

The assessment strategy is designed to provide students with the opportunity to demonstrate their ability to use some accessible AI tools to support the exploration of sustainability issues and analysis (Learning objectives L01 to L04). The summative assessment for this module consists of: -Review of an AI generated article (30%) - Production of AI edited documentary video (group work) (40%) -Reflective essay (30%) Formative assessment and feedback: Students receive verbal feedback during lectures. There are also weekly seminar sessions during which key topics relating to sustainability and AI will be discussed together by the class, with students receiving informal feedback on the input into these discussions. There will also be discussion in class on current news items relating to AI and sustainability, with students receiving informal feedback on their ideas by their peers and the instructor. During the computer workshops students will receive informal feedback on the production of their documentary videos and other AI related tasks.

Module aims

• ¿ To help students develop an understanding of how AI operates and its impacts on society, economy and the environment.
• ¿ To help students develop skills to support academic and social media content generation using accessible AI tools.
• ¿ To help students develop a broad understanding of the global and UK media in relation to sustainability and AI.
• ¿ To understand the application of AI in different communication methods.

Learning outcomes

Methods of Teaching / Learning

The learning and teaching strategy seeks to develop students¿ understanding the interrelationship between sustainability and AI. Lecture material will introduce core concepts, theories and ideas, while in the weekly seminars students will explore and develop their understanding of these concepts and theories via examples and sustainability related case studies. Seminars will make use of classroom-based discussions and group work. There will hands-on workshops with computers to learn how to use some key AI tools and complete a group work project aided by AI.

The learning and teaching methods include:
- Lectures and class discussions (11 hours)
- Captured content (11 hours)
- Seminars (11 hours)
- Computer workshop (8 hours)

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

https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: ENG2139

Other information

The Centre for Environment and Sustainability is committed to developing graduates with strengths in Employability, Digital Capabilities, Global and Cultural Capabilities, Sustainability and Resourcefulness and Resilience, in line with the Surrey Curriculum Framework. This module is designed to allow students to develop knowledge, skills and capabilities in the following areas: Sustainability: Professionals need a good understanding of how to make effective use of AI tools to support analysis of data and decision making to support sustainability. Digital capabilities: This module will help students develop skills to enable them to effectively navigate an AI driven world and critically apply AI in their professional context. Employability: Increasingly jobs require professional to be able to effectively use AI tools to enhance the speed and quality of their work while using these tools ethically and legally.

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.