DigiLawyer: Training lawyers for the challenge of digitalisation

Course content

Digitization is having a transformative impact on many aspects of society including law and the legal profession. Firstly, lawyers, besides a deep legal expertise, are also requested to have the ability to collaborate and communicate with other disciplines and professions linked to digitization. It is furthermore required to demonstrate the capability to identify new legal solutions to the many and complex issues emerging from new developments in information technology, data analytics and security, politics and policy-making, media, etc. Secondly, the legal sources are digitalized to an increasing extent and legal research must work to ensure that tomorrow's lawyers, through training and education, master the new tools of data analysis (e.g. statistics, machine learning, among others) to optimally contribute to the development of the legal profession.
These changes in the legal market demonstrate the need of a new generation of lawyers with more non-legal skills associated to the analysis of digital data, the so-called, DigiLawyer. This lawyer must now be able to understand and process massive legal and socio-legal knowledge, data on the WWW, statistics or big data, and perform 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) his/her ability to adapt and meet clients demands and to understand the necessities of the new players in the digitalization global network (e.g. lawyers, firms, policy-makers, civil society, etc.).
2) his/her knowledge and skills to use digital legal platforms and big legal data analysis techniques.
3) his/her analytical capacity to innovate and integrate data analysis into legal thinking.
4) his/her 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 digitalization, having a deep knowledge on how it affects the law and how it can be use in the advantage of lawyers becomes paramount. The course expects to have an impact on the legal training and education of the legal profession by providing a breadth of knowledge of relevant concepts, framework and techniques relevant for collaboration with other professions concerned with digitalization (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 digitalization.
For that purpose, this course will discuss new training tools: (1) for increasing the awareness of legal actors about the relevance of digitalization 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

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


A) In terms of knowledge, the student will be able:
(1) To recognize and critically evaluate the advantages and challenges of the digitalization of lawyers.
(2) To identify the most recent and relevant legal developments and implications of digitalization.
(3) To use Python programming languages independently in order to acquire additional skills for data storage, analysis and visualization

 

B) Within this framework, the students in terms of skills will be able:
(1) To identify sources of legal data;
(2) To understand the structure of quantitative data.
(3) To Formulate codebook entries that prepare the collection and coding of data.
(4) To collect and synthesize legal information from digitalised sources (e.g. websites);
(5) To articulate and develop legal arguments using computational legal methods;
(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 upon this knowledge and skills, the student will analyse, contrast and evaluate the advantages and difficulties of the digitalization of the legal profession. As a result the student will be able:
(1) To innovate and integrate data analysis 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 digital data and techniques for understanding the law, affecting his/her ability to adapt and meet clients demands and to understand the necessities of the new players in the digitalization global network (e.g. lawyers, firms, policy-makers, administration, civil society, etc.).

Students are expected to read the texts and participate actively in class. To improve the learning process, the course uses innovative pedagogical techniques for training on text mining and computational analysis. The following instructional strategies combine theoretical discussion with training sessions, such as:

a) 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. The lecturers will bring expertise from a number of different jurisdictions so students will have a comparative approach to using digital tools to understand case law and preparing students for a global career.
b) Methodological learning: The lecturer will train students in the application of text-mining, web-scraping, network analysis and machine learning training session.
c) Group work - Student will discuss and analyze the challenges and new opportunities that bring to the legal profession.
d) Use of online

Proficient level in English

Written
Oral
Individual
Collective
Continuous feedback during the course of the semester
Feedback by final exam (In addition to the grade)
Peer feedback (Students give each other feedback)
ECTS
15 ECTS
Type of assessment
Written assignment
Individual written assignment
Marking scale
7-point grading scale
Censorship form
No external censorship

Single subject courses (day)

  • Category
  • Hours
  • Seminar
  • 56
  • Preparation
  • 356,5
  • English
  • 412,5