Københavns Universitet - Kurser

JJUA55261U Cancelled DigiLawyer: Training lawyers for the challenge of digitalisation

Volume 2023/2024

Digitisation has a transformative impact on society, including law and the legal profession. Firstly, lawyers, besides deep legal expertise, are also requested to have the ability to collaborate and communicate with other disciplines and professions linked to digitisation. They need to have an understanding of technology so they can effectively communicate with technical and computational experts. Furthermore, it is required to demonstrate the capability to identify new legal solutions to the many complex issues emerging from recent developments in information technology, data analytics, algorithmic thinking and security, politics and policy-making, media, etc. Secondly, the legal sources are digitised to an increasing extent. Legal research must ensure that tomorrow's lawyers, through training and education, master the new tools of data analysis and data mining to contribute to the development of the legal profession optimally.

These changes in the legal market demonstrate the need for a new generation of lawyers with a broader skill-set than traditional lawyers have. Future lawyers – DigiLawyers - who wish to actively contribute to changing society need to understand the basics of technology. They must be able to understand and process massive legal and socio-legal knowledge, data on the WWW, statistics or big data, and understand data analysis, to the extent that they can inform new legal strategies by gaining new insights that are not available from traditional legal research methods.

The DigiLawyer is defined then by:

1) their ability to adapt and meet clients' demands and to understand the necessities of the new players in the global digitalisation network (e.g. lawyers, firms, policy-makers, civil society, etc.);

2) their knowledge and skills to use various technologies, including digital legal platforms and big legal data analysis techniques;

3) their analytical capacity to innovate and integrate data analysis into legal thinking;

4) their capacity to understand the changing role of lawyers in an increasingly digitalised society and work environment.

Hence, when thinking about the new legal horizons and challenges of digitalisation, having deep knowledge of how it affects the law and how it can be used to the advantage of lawyers becomes paramount. The course expects to impact the legal training and education of the legal profession by providing a breadth of knowledge of relevant concepts, frameworks and pertinent techniques for collaboration with other disciplines concerned with digitalisation (e.g. IT firms, policy-makers, data analysis companies, media). In this regard, we stress the importance for lawyers to be able to communicate and collaborate across disciplines and professions affected by digitalisation.

For that purpose, this course will discuss new training tools: (1) for increasing the awareness of legal actors about the relevance of digitalisation for the legal profession, and (2) for transferring the knowledge and skills mentioned above to law students, lawyers and other legal actors (e.g. judges and civil servants).

Learning Outcome

Learning Outcomes

This course will contribute to the students' competence profile in the following terms.

A) In terms ofknowledge, the student will be able:

(1) To recognise and critically evaluate the advantages and challenges of the digitalisation of lawyers.

(2) To identify the most recent and relevant legal developments and implications of digitalisation for the legal industry and society;

(3) To understand the basic structures and logic of the Python programming language.

B) Within this framework, the students, in terms ofskills,will be able:

(1) To understand computational logic;

(2) To identify sources of legal data;

(3) To collect and synthesise legal information from digitalised sources (e.g. websites);

(4) To articulate and develop legal arguments using computational legal methods;

(5) To apply the legal design method;

(6) To work independently at a basic level with different computational legal techniques and collaborate with other peers in the development of these capabilities and skills in the framework of groups' presentations and discussions.

C) Finally, based on this knowledge and skills, the student will analyse, contrast and evaluate the advantages and difficulties of the digitalisation of the legal profession. As a result, the student will be able:

(1) To innovate and integrate computational tools into legal thinking;

(2) Be able to evaluate the strengths and weaknesses of their computational legal analysis.

(3) To improve students' understanding of the relevance of data and computational techniques for understanding the law, affecting their ability to adapt and meet clients' demands and to understand the necessities of the new players in the global digitalisation network (e.g. lawyers, firms, policy-makers, administration, civil society, etc.).

Literature

Alexandra Andhov, Computational Law, Karnov, 2022

Additional legal and technical literature will be assigned to each class.

It is illegal to share digital textbooks with each other without permission from the copyright holder.

Recommended Academic Qualifications

Proficient level in English

Teaching and learning methods

Students are expected to read the assigned texts and participate actively in class. The course uses innovative pedagogical techniques for training on computational logic, algorithmic thinking, legal design thinking and text mining to improve the learning process.

The following instructional strategies combine theoretical discussion with training sessions, such as:
a) Technology review – understanding the elements of each technology and its development over time;
b) Case law based learning: The lecturers will train students in using a variety of digital tools and techniques to not only aid in the reading of singular cases but to apply those tools for researching larger bodies of case law faster and more efficiently, as well as understanding the cases' larger context.
c) Methodological learning: The lecturer will train students to apply text-mining, web-scraping, network analysis and machine learning training sessions.
d) Group work - Student will discuss and analyse the challenges and new opportunities that bring to the legal profession;
e) Use of other relevant techniques and tools.

Remarks

As you know, if you have not adequately prepared for the class, you will not be able to participate at an acceptable level or get the maximum benefit from the course. There is a high probability that your lack of preparation will be reflected in your final grade for the course.

Workload