JJUA55288U Legal Tech Laboratory

Volume 2021/2022
Content

The legal profession in Denmark and across the world is changing at a pace never experienced before, and in ways, most lawyers would have found hard to predict just a couple of years back. The Covid-19 pandemic has accelerated even more rapidly every industry’s path to digitize, and the notoriously conservative legal industry is no exception. Legal firms and their clients are demanding more innovation; many of them have introduced new legal tech strategies or innovation departments in a bid to improve efficiency and lower their costs. Many start-ups are seeing the opportunity to participate in these trends to help law firms, corporate legal departments, as well as consumers to take advantage of technology.

 

The course offers and array of experiences that will better prepare students for both traditional and non-traditional legal employment. Traditional employers increasingly need lawyers who not only have the traditional legal knowledge and skills, but who are also familiar with innovative processes and technologies. Undersanding the significance of technology and business acumen to successful delivery of legal services is vital. Due to the needs of the new global and complex marketplace, successful legal professionals must be creative problem solvers, leaders with a high risk tolerance and business mindset that can use technology, collaboration, leadership, and communication skills.

 

Legal Tech Laboratory is a course for law students who wish to create innovative solutions to problems at the intersection of law, business and technology, while developing the skills essential to all professionals today. This course first provides students with hands-on learning with variety of technology tools,  ranging from basic Microsoft Office, through Community Lawyer or electronic discovery to blockchain tool. Subsequently, students are to design and develop their own business case, a solutions or even a prototype to a real problem sponsored by a corporate legal department, law firm, an NGO or a public agency. The aim of the course is for the students to not only understand the technology and become familiar with it, but also to utilize it in order to solve legal problems. Additionally, the course will offer a series of guest lectures by computer scientists, who will showcase use of specific tools and provide students with the understanding to further utilization of these tools in their future practice.

Learning Outcome

Knowledge:

  • Students will understand various technological tools that are used and applied in legal practice;
  • Students will be able to recognize the possibilities and limitations of various technologies that are utilized in legal analysis, including artificial intelligence, natural language processing or machine learning;
  • Students will
     

Skills:

  • Legal skills: problem-based approach to specific real life problems;
  • Design thinking: conceptualize legal problems and design possible solutions;
  • Technological skills: students will work directly with specific technology;
  • Argumentation and presentations: students will need to substantiate their specific solution and present their idea;
  • Critical thinking: students will need to review the value of specific technological solutions and assess the legal and regulatory consequences of using specific technology;
  • Teamwork and problem solving;


Competences:

  • Working with new technology, including legal tech;
  • Will be able to develop a legal design and solution for a legal problem;
  • Competence to handle repeatable commercial transactions and contract management functions;
  • Conceptualize various legal problems and provide insight into various technological solutions and use of automation.
Literature
  • Alex Pentland, A Perspective on Legal Algorithms, MIT Computational Law Report, 2019, 10p;
  • Wolfgang Alschner, Sense and Similarity: Automating Legal Text Comparison in Computational Legal Studies (ed. Ryan Whalen, EE Publishing, 2020), 20p;
  • Kevin D. Ashley, Introducting AI & Law and its Role in Future Legal Practice in Artificial Intelligence and Legal Analytics (CUP, 2017) 34p;
  • Michael Jeffery, What Would an Integrated Development Environment for Law look like? MIT Computational Law Report, 2020, 22p;
  • Nina Varsava, Computational Legal Studies, Sigital Humanities, and Textual Analysis, in Computational Legal Studies (ed. Ryan Whalen, EE Publishing, 2020), 22p;
  • Hischal Mainali et al. Automated Classification of Modes of Moral Reasoning in Judicial Decisions in Computational Legal Studies (ed. Ryan Whalen, EE Publishing, 2020), 22p;
  • Gianluigi Riva, The Potential and Limitations of Computational Law for Data Protection, MIT Computational Law Report, 2020, 17p;
  • Kevin D. Ashley, Computational Models of Legal Argument in Future Legal Practice in Artificial Intelligence and Legal Analytics (CUP, 2017) 39p;
  • Paul Crowder, Is Legal Cognition Computational? (When will DeepVehicle replace Judge Hercules?) in Computational Legal Studies (ed. Ryan Whalen, EE Publishing, 2020) 23 p;
  • Kevin D, Ashley, Cognitive Computing Legal Apps in Future Legal Practice in Artificial Intelligence and Legal Anyltics (CUP, 2017) 42p;
Students will work in groups on designing solutions for specific practical problems. The course in the first several looks will develop the necessary knowledge, which students will subsequently apply within the specific cases. For the exam, students are asked to individually or in groups, describe the legal problem and the solution that they designed and provide an analysis on their solution and its limitations within a specific legal system or practice. Thus, students’ learning will be enhanced with
The course will run with the support of DIKU.
  • Category
  • Hours
  • Preparation
  • 178,25
  • Seminar
  • 28
  • Total
  • 206,25
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)
Credit
7,5 ECTS
Type of assessment
Written assignment
Individual written assignment
Aid
All aids allowed
Marking scale
7-point grading scale
Censorship form
No external censorship
Exam period

hand-in date: January 12, 2022

Re-exam

hand-in date: February 18, 2022