Bespoke Digital Skills Programme for the Environment Agency (fully booked)
Date:
11/03/2026 - 18/03/2026
Organised by:
University of Southampton
Presenter:
Dr Naomi Tyrrell and Professor Leslie Carr
Level:
Entry (no or almost no prior knowledge)
Contact:
Laone Maphane
Lecturer in AI Skills and Research Methods
laone.maphane@soton.ac.uk
Venue: Online
Description:
Module 1 – Responsible AI and Ethics
Date: 11th March 2026 - 13:00 - 15:00
Trainer: Dr Naomi Tyrrell
Purpose
This session introduces participants to the ethical, legal, and social dimensions of using Artificial Intelligence (AI) and Large Language Models (LLMs) in environmental work. It focuses on building awareness of fairness, transparency, accountability, and public trust in AI driven decision-making. Through open discussion and case-based reflection, participants will explore how to apply responsible AI principles within the Environment Agency’s data and policy context.
Learning Objectives
- By the end of this module, participants will be able to:
- Identify common ethical risks in AI and LLM use (bias, privacy, opacity, misuse).
- Understand fairness, transparency, and explainability as key principles of responsible AI.
- Recognise the importance of data governance and accountability frameworks.
- Apply basic fairness and explainability checks when using AI tools.
- Reflect on how ethical AI practice aligns with public trust and regulatory standards.
Module 2 – AI and Large Language Models (LLMs) for Environmental Data
Date: 17th March 2026 - 10:00 - 12:00
Trainer: Prof Leslie Carr
Purpose
This module provides a clear and accessible overview of Artificial Intelligence (AI) and Large Language Models (LLMs) and how they can support the Environment Agency’s analytical and policy work. Participants will learn what AI and LLMs are, how they differ from traditional analytical tools, what kinds of data they can use, and how they are already transforming environmental science worldwide.
Learning Objectives
- By the end of this module, participants will be able to:
- Explain what AI, Machine Learning, and LLMs are and how they relate to one another.
- Distinguish between traditional analytical methods and AI-based approaches.
- Identify data types (numerical, spatial, image, and text) suitable for AI and LLM applications.
- Recognise use-cases of AI and LLMs in environmental monitoring, modelling, and communication.
- Understand the idea of the “black box” and the importance of explainability and ethics.
- Reflect on where LLMs could help within their own EA projects (e.g., coding, summarisation, or automation).
Module 3 – NLP for Survey and Text Data
Date: 18th March 2026 - 10:00 - 12:00
Trainer: Prof Leslie Carr
Purpose
This module introduces participants to Natural Language Processing (NLP) and demonstrates how it can be applied to environmental survey and text data. It focuses on using Large Language Models (LLMs) to automate tasks such as coding, summarisation, sentiment detection, and theme extraction. The session shows how these tools can support faster, more consistent qualitative analysis within the Environment Agency’s work.
Learning Objectives
- By the end of this module, participants will be able to:
- Understand the fundamentals of NLP and its relevance to environmental data.
- Apply NLP techniques to survey and textual datasets.
- Use LLMs to automate coding, summarisation, and classification.
- Evaluate NLP model performance using appropriate metrics.
- Communicate insights from text data clearly to both technical and non-technical audiences.
Cost:
Free of charge
Region:
South East
Keywords:
Research Ethics, Regulatory and Legal Aspects, AI and machine learning, Machine learning, NLP and text mining, Large Language Models (LLMs),
Related publications and presentations from our eprints archive:
Research Ethics
Regulatory and Legal Aspects
AI and machine learning
Machine learning
NLP and text mining