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 understan d 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.

(LO1) Students will be able to identify and evaluate leading theories on the potential role for machine learning, artificial intelligence and other ‘disruptive’ technologies within the legal (LawTech) and FinTech sectors.

(LO2) Students will be able to 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) Students will be able to identify the main current legal and regulatory constraints on the development of legal services enhanced by machine learning and artificial intelligence.

(LO4) Students will be able to identify and evaluate selected critical and ethical arguments about the appropriate role of artificial intelligence in the legal (LawTech) and FinTech sectors.

(LO5) Students will be able to identify and synthesise contemporary policy and strategy statements from government, the legal professions, and from the courts.

(S1) Critical thinking.
Students will apply concepts of law to broader commercial challenges in both LawTech and FinTech.

(S2) Team work.
Students will work together in teams for the group presentation assessment.

(S3) Commercial awareness.
Students will study and analyse real-world examples and commercial case studies.

(S4) Digital literacy.
Students will develop skills in the field of applied LawTech within a broader FinTech framework.

(S5) Communication skills.
Students will develop their communication skills by working together to prepare for and deliver the group presentation assessment.

(S6) Ethical awareness.
Students will evaluate the ethical and legal challenges posed by new technologies within the context of legal and commercial practices.

2 hour lecture x 10 weeks
1 hour seminar x 5 weeks
125 hours self-directed learning

Lectures will be supported by pre- and post-lecture reading as directed by the module leader on the VLE.

Attendance will be recorded.

Seminars will largely be case study based and will focus on the application of theory studied during the preceding week’s lecture. Students will be expected to engage in pre-reading as well as post-lecture reading, as directed by the module leader on the VLE.

Attendance will be recorded.

Outside of the classroom, students will be expected to engage in wider reading in the form of journals, books and recordings as directed by the module leader. The framework/ scaffolding for such learning will be provided on the VLE by the module leader.

HiPy and other peer-to-peer learning platforms may be adopted where relevant in the pedagogic strategy of this module delivery.

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, e.g. the IBM Watson Assistant tool, but in future sessions students may cover alternative LegalTech including the IBM Discovery tool, NeotaLogic, or Kira Systems machine learning software. The precise application or process which students will focus on each year will vary according to technological developments in the legal sector;

Legal, regulatory and ethical constraints on the application of machine learning and artificia l intelligence in the legal sector;

Government, professional, and judicial strategies and policies for the development of AI enhanced legal services.