ºÚ¹Ï³ÔÁÏÍø

Internal

LW1AI: Ethical GenAI for Law

ºÚ¹Ï³ÔÁÏÍø

LW1AI: Ethical GenAI for Law

Module code: LW1AI

Module provider: School of Law

Credits: 20

Level: 4

When you’ll be taught: Semester 2

Module convenor: Dr Basak Bak , email: basak.baktezgel@reading.ac.uk

Module co-convenor: Ms Sharon Sinclair-Graham, email: sharon.sinclair-graham@reading.ac.uk

Additional teaching staff 1: Dr Melanie Stockton-Brown, email: m.w.stockton-brown@reading.ac.uk

Pre-requisite module(s):

Co-requisite module(s):

Pre-requisite or Co-requisite module(s):

Module(s) excluded:

Placement information: No placement specified

Academic year: 2025/6

Available to visiting students: Yes

Talis reading list: No

Last updated: 3 April 2025

Overview

Module aims and purpose

The module aims to equip students with the skills to use generative AI (GenAI) responsibly and efficiently in legal education and the profession. It further aims to teach them the PREP EDIT framework for law, which helps determine when using GenAI is appropriate and when it is not. Throughout the module, students learn a variety of topics to gain a holistic understanding of the risks and opportunities associated with using GenAI. Topics include technical aspects, such as writing effective prompts, as well as legal frameworks, such as protecting personal data and copyright.

Module learning outcomes

By the end of the module, students are expected to:

  1. Analyse and critically evaluate GenAI-generated content.
  2. Demonstrate the ability to engineer efficient prompts through a hands-on approach.
  3. Develop a deeper interest in the applications of GenAI in legal education and the profession.
  4. Identify the risks and limitations of GenAI tools.
  5. Demonstrate digital literacy skills relevant to employability.
  6. Identify appropriate AI tools for various legal tasks.
  7. Leverage GenAI to solve problems effectively.

Module content

The module will cover a range of topics, including:

  • Prompt Engineering and Critical Thinking
  • Fairness and Bias in AI Systems
  • Data Protection and Intellectual Property
  • The Future of AI in the Legal Profession

Structure

Teaching and learning methods

Teaching in this module is designed to provide students with a variety of resources to support their learning. The main elements include:

-A list of required and recommended readings, accompanied by notes and questions to guide class discussions and reflection.

-20 hours of lectures to introduce key concepts and frameworks.

-10 hours of scheduled workshops and 5 hours of tutorials, allowing for in-depth discussions of the topics.

-Two pieces of assessed coursework to develop students' skills and knowledge.

Whole-class participation is expected throughout the module.

Study hours

At least 37 hours of scheduled teaching and learning activities will be delivered in person, with the remaining hours for scheduled and self-scheduled teaching and learning activities delivered either in person or online. You will receive further details about how these hours will be delivered before the start of the module.


 Scheduled teaching and learning activities  Semester 1  Semester 2 Ìý³§³Ü³¾³¾±ð°ù
Lectures 20
Seminars
Tutorials 5
Project Supervision
Demonstrations
Practical classes and workshops 10
Supervised time in studio / workshop
Scheduled revision sessions
Feedback meetings with staff
Fieldwork
External visits
Work-based learning


 Self-scheduled teaching and learning activities  Semester 1  Semester 2 Ìý³§³Ü³¾³¾±ð°ù
Directed viewing of video materials/screencasts
Participation in discussion boards/other discussions
Feedback meetings with staff
Other 13
Other (details)


 Placement and study abroad  Semester 1  Semester 2 Ìý³§³Ü³¾³¾±ð°ù
Placement
Study abroad

Please note that the hours listed above are for guidance purposes only.

 Independent study hours  Semester 1  Semester 2 Ìý³§³Ü³¾³¾±ð°ù
Independent study hours 152

Please note the independent study hours above are notional numbers of hours; each student will approach studying in different ways. We would advise you to reflect on your learning and the number of hours you are allocating to these tasks.

Semester 1 The hours in this column may include hours during the Christmas holiday period.

Semester 2 The hours in this column may include hours during the Easter holiday period.

Summer The hours in this column will take place during the summer holidays and may be at the start and/or end of the module.

Assessment

Requirements for a pass

Students need to achieve an overall module mark of 40% to pass this module.

Summative assessment

Type of assessment Detail of assessment % contribution towards module mark Size of assessment Submission date Additional information
Oral assessment Podcast (Recorded Individual Presentation) 40 5 minutes long
Portfolio or Journal Research Development Portfolio 60 Maximum 12 pages, no less than 9 pages

Penalties for late submission of summative assessment

The Support Centres will apply the following penalties for work submitted late:

Assessments with numerical marks

  • where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of three working days;
  • the mark awarded due to the imposition of the penalty shall not fall below the threshold pass mark, namely 40% in the case of modules at Levels 4-6 (i.e. undergraduate modules for Parts 1-3) and 50% in the case of Level 7 modules offered as part of an Integrated Masters or taught postgraduate degree programme;
  • where the piece of work is awarded a mark below the threshold pass mark prior to any penalty being imposed, and is submitted up to three working days after the original deadline (or any formally agreed extension to the deadline), no penalty shall be imposed;
  • where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

Assessments marked Pass/Fail

  • where the piece of work is submitted within three working days of the deadline (or any formally agreed extension of the deadline): no penalty will be applied;
  • where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension of the deadline): a grade of Fail will be awarded.

The University policy statement on penalties for late submission can be found at: /cqsd/-/media/project/functions/cqsd/documents/qap/penaltiesforlatesubmission.pdf

You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Formative assessment

Formative assessment is any task or activity which creates feedback (or feedforward) for you about your learning, but which does not contribute towards your overall module mark.

In-class self-assessment and self-reflection for the preparation of the podcast assessment, alongside a session on academic misconduct as a scaffolding activity.

Reassessment

Type of reassessment Detail of reassessment % contribution towards module mark Size of reassessment Submission date Additional information
Oral reassessment Podcast (Recorded Individual Presentation) 40 5 minutes long During the University resit period
Portfolio or Journal Research Development Portfolio 60 Maximum 12 pages, no less than 9 pages During the University resit period

Additional costs

Item Additional information Cost
Computers and devices with a particular specification
Printing and binding
Required textbooks
Specialist clothing, footwear, or headgear
Specialist equipment or materials
Travel, accommodation, and subsistence

THE INFORMATION CONTAINED IN THIS MODULE DESCRIPTION DOES NOT FORM ANY PART OF A STUDENT’S CONTRACT.

Things to do now