Law School Module Details
The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module.
Title Artificial Intelligence and the Future of Legal Services
Code LAW383
Coordinator Mr JJ Marshall
Law
J.Marshall@liverpool.ac.uk
Year CATS Level Semester CATS Value
Session 2022-23 Level 6 FHEQ First Semester 15

Aims

This module aims to:
• Provide students with hands-on experience of a contemporary LegalTech application or process so that they can develop a practical understanding of the opportunities and risks of using technology to deliver or enhance legal services.
• Help students to discover how looking at the way technology has transformed other sectors outside of law (e.g. FinTech, media, medicine) can help us to understand, predict or even design new types of legal practice and new types of ‘lawyer’.
• Demonstrate how established legal concepts and ways of working with legal problems are disrupted by machines with ‘artificial intelligence’.
• Raise students’ awareness of the commercial significance of artificial intelligence in an increasingly global, competitive and technology-driven legal services marketplace.
• Provide law students with sufficient knowledge and experience of artificial intelligence and machine learning to understand the capacity of those technologies to support legal services, as well as the accompanying risks which regulators are concerned with.
• Develop a disruptive, innovative mind-set in students that will enhance their employability within the new legal marketplace.

Learning Outcomes

(LO1) Identify and evaluate leading theories on the potential role for machine learning, artificial intelligence and other ‘disruptive’ technologies within the legal sector.

(LO2) Understand the concepts of ‘machine learning’ and ‘artificial intelligence’ and evaluate the extent to which those concepts can be applied to legal analysis, legal reasoning, and legal decision-making.

(LO3) Identify and evaluate a range of contemporary critical, ethical, and legal arguments concerning the appropriate role of artificial intelligence in the legal sector.

(LO4) Identify and synthesise contemporary policy and strategy statements from government, the legal professions, and from the courts concerning innovation and the use of technology in the justice system .

(S1) Critical thinking

(S2) Team work

(S3) Commercial Awareness

(S4) Digital literacy

(S5) Presentation

Syllabus
 

Specific content will vary year-by-year and will respond to emerging developments in the field of technology, artificial intelligence and the law. General topics will include:

• Contemporary theoretical discourses on legal innovation, ‘access to justice’, and the role of technology and innovation within a competitive global legal sector.
• Fundamentals of machine learning and artificial intelligence in the context of legal services and legal decision-making.
• Understanding a contemporary LegalTech software application or process. This may include legal-tech applications from IBM, Neota Logic, Kira Systems and others, and the precise application or process which students will focus on each year will vary according to technological developments in the legal sector and the availability of partners from relevant LegalTech firms.
• Legal, regulatory and ethical constraints on the application of machine learnin g and artificial intelligence in the legal sector.
• Government, professional, and judicial strategies and policies for the development of AI enhanced legal services.

Teaching and Learning Strategies

Module Delivery

Students will be assigned to project teams at the beginning of the course. Within those teams, students will progressively develop a solution to their assessed project brief, and a suitable online digital collaboration space (Microsoft Teams) will be provided for each project team. Students will be supported in this work by a combination of short, recorded lectures delivered through the virtual learning environment, seminars, and computer lab classes. Seminars will be used to develop students’ understanding of underlying scientific, policy and theoretical elements of the course and to engage student teams in discussions concerning key project decisions. Computer lab classes will be used to train students in specific digital literacy skills and to familiarise them with the key software packages that will be used in this course. Students will also be invited to participate in scheduled interactive sessions with key industry/academic partners connected to the field of artificial intelligence and law.

-E lecture material will be asynchronous

Teaching Schedule
  Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
Study Hours   12

       12

38

6

6

 74
Timetable (if known)   120 mins X 1 totaling 12
  		      120 mins X 1 totaling 6
120 mins X 1 totaling 6
  		 
Private Study 76
TOTAL HOURS 150

Assessment
EXAM Duration Timing
(Semester)		 % of
final
mark		 Resit/resubmission
opportunity		 Penalty for late
submission		 Notes
             
CONTINUOUS Duration Timing
(Semester)		 % of
final
mark		 Resit/resubmission
opportunity		 Penalty for late
submission		 Notes
1. Project Presentation (50%) The presentation component will use bespoke assessment criteria.  25    50       
2. Reflective essay (50%) (2000 words) This component will use the standard L6 assessment criteria.  0    50       

Recommended Texts
Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module.

Other Staff Teaching on this Module
 

Modules for which this module is a pre-requisite:
 

Pre-requisites before taking this module (other modules and/or general educational/academic requirements):
LAW242 LAND LAW 

Co-requisite modules:
 

Programme(s) (including Year of Study) to which this module is available on a required basis:
 

Programme(s) (including Year of Study) to which this module is available on an optional basis:
 

Additional Programme Information