Dr Adam Wyner

Research Highlights

1. Strass, H., Wyner, A., & Diller, M. (2019). EMIL: Extracting Meaning from Inconsistent Language. International Journal of Approximate Reasoning, 112, 55-84.

   https://doi.org/10.1016/j.ijar.2019.04.010, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa50680
2. Liepiņa, R., Sartor, G., & Wyner, A. (2020). Arguing about causes in law: a semi-formal framework for causal arguments. Artificial Intelligence and Law, 28(1), 69-89.

   https://doi.org/10.1007/s10506-019-09246-z, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa49685

   http://dx.doi.org/10.1007/s10506-019-09246-z
3. Shulayeva, O., Siddharthan, A., & Wyner, A. (2017). Recognizing cited facts and principles in legal judgements. Artificial Intelligence and Law, 25(1), 107-126.

   https://doi.org/10.1007/s10506-017-9197-6, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa40674
4. Fawei, B., Pan, J., Kollingbaum, M., & Wyner, A. (2018). A Methodology for a Criminal Law and Procedure Ontology for Legal Question Answering. In Semantic Technology (pp. 198-214).

   https://doi.org/10.1007/978-3-030-04284-4_14, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa47953
5. Soares, R., Edelstein, E., Pan, J., & Wyner, A. (2018). Knowledge Driven Intelligent Survey Systems for Linguists. In Semantic Technology-18). Semantic Technology: 8th Joint International Conference, JIST 2018..

   https://doi.org/10.1007/978-3-030-04284-4_1, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa47954

All Research

• CS-261 Coding for Lawyers

  This module provides an introduction to Computer programming and coding principles, tailored to students from Law. Students will be able to apply those principles in practice to program development in Python and gain further insight in the typical design, structure and application of technical solutions. The module enables students majoring in Law to reach a level of skill in programming such that they will be able to apply their computing knowledge to their own subject.

• CSC325 Artificial Intelligence

  CSC325 is an introduction to Artificial Intelligence, focusing primarily on reasoning and problem-solving as a search for a solution rather than on statistical techniques for classification. The course may cover topics from amongst: search techniques; knowledge representation and expert systems; planning; scheduling; qualitative reasoning; language processing with grammar rules; and meta-programming.

• CSCM23 Designing-in Trust, Understanding and Negotiation

  This module explores state-of-the-art methods and concepts to assist responsible design and development of technology with the aim of creating reliable and trusted systems. The content of this module will be delivered by expert lecturers and practitioners in the areas of trusted computation, bias and explainability in automated decision making and decision support, ethical considerations for AI, argumentation and negotiation, as well as formal methods, such as verification of critical systems.

• CSLM81 Computational Thinking

  Computational Thinking is a problem solving paradigm aimed at constructing and evaluating solutions to problems which a computer - be it human or mechanical - can carry out effectively. The module provides an introduction to Computational Thinking and Computer Programming, tailored to students from Law. Students will be able to apply problem solving principles to program development in Python. They will gain insight into the typical design, structure and application of technical solutions within a legal context.

• LAAD01 LegalTech Project

  Students will seek to develop a technological solution to a legal services challenge in commercial law or access to justice settings. Students will be able to use any software application or program language. Supervision will be provided in accordance with the procedures set out in the LLM LegalTech Handbook. Students should refer to the Handbook for information on supervision.

• LAAM19 Artificial Intelligence and Law - Principles

  The module is an introduction to some of the principles and techniques of Artificial Intelligence as applied to legal information such as legislation, case law, and contracts. Students will learn some of the key elements of AI including logic, knowledge representation, natural language processing, and machine learning. Students will gain theoretical knowledge about AI systems to understand how they are used to analyse, represent, and process legal information.

• LAAM35 Artificial Intelligence and Law - Applications

  The module introduces the students to IT technologies that may be concretely employed in the current LegalTech market. Special attention will be devoted to Semantic Web technologies for the legal domain, such as LegalDocML and RDF/OWL. These technologies have recently gained attention both in academia, industry, and standardization bodies. IT technologies based on semantics represent the path to explainability, which has been deemed by many as a desirable feature of next-generation AI technologies, in particular for LegalTech applications. The module also aims to encourage students to identify new use cases, which could be interesting for the current LegalTech industry and which could even set the ground for a future start-up project plan. External speakers from industry or academia will be invited to give talks related to the topics of this module.