Module code: LAWM174

Module Overview

This module introduces the students to the key ethical and regulatory issues associated with artificial intelligence, as well as to the methods of analysis of those issues used in ethics and in law. The focus of the module is on the current state of the art in the applications of artificial intelligence (in particular: of machine learning), with smaller emphasis on hypothetical future developments. The module makes use of the case study method to introduce students to ethical and regulatory (legal) questions through discussion of relevant major incidents from recent years. The module helps students develop their thinking on how to translate abstract ethical (and regulatory) requirements of fairness, explainability or privacy into engineering and business practice.

Module provider

SOL - Computer Science and Elec Eng

Module Leader

BARCZENTEWICZ Mikolaj (Schl of Law)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 7

Module cap (Maximum number of students): N/A

Overall student workload

Independent Learning Hours: 102

Tutorial Hours: 4

Guided Learning: 33

Captured Content: 11

Module Availability

Semester 1

Prerequisites / Co-requisites


Module content

Indicative content includes the following:

  • Cases studies of major incidents illustrating ethical and regulatory problems in the field of artificial intelligence.

  • How different ethical frameworks can be applied to think about the uses of artificial intelligence.

  • Approaches to understanding the ethical (and regulatory) requirements of fairness, explainability and privacy (and how to translate them into technical specifications).

Assessment pattern

Assessment type Unit of assessment Weighting
Online Scheduled Summative Class Test First in-semester test (1 hour) 15
Online Scheduled Summative Class Test Second in-semester test (1 hour) 20
Examination Online Final Examination Online (4 hours within 24 hour window) 65

Alternative Assessment


Assessment Strategy

The assessment strategy for this module is designed to provide students with the opportunity to demonstrate achievement of module learning outcomes in respect of knowledge gained, critical/analytical ability and skills acquired. The assessment addresses all learning outcomes listed above. 
Thus, the summative assessment for this module consists of:

  • Two in-semester online tests (addressing learning outcomes: 1, 3, 4).

  • A final online examination (addressing learning outcomes: 1, 2, 3, 4).

All assessments will combine Multiple-Choice Questions with other types of questions, likely to include True/False, Ordering, and Short/Longer Answers as appropriate.
Formative assessment and feedback:
For the module, students will receive formative assessment/feedback in the following ways:

  • Formative online test, of a similar format as in-semester online tests.

  • Individual and general feedback provided to students, including automated feedback on answers provided to the formative online tests.

  • Other formative exercises may be set in or outside class.

Module aims

  • Provide students with an understanding of the key ethical and regulatory issues associated with artificial intelligence.
  • Enable students to apply the methods of reasoning and analysis of those issues used in ethics and in law.
  • Expose students to the challenges of interdisciplinary thinking about artificial intelligence.

Learning outcomes

Attributes Developed
001 Demonstrate an understanding of the basic ethical and regulatory issues associated with artificial intelligence. KC
002 Formulate and communicate their views of those issues in an interdisciplinary environment. CPT
003 Critically analyse statements on ethical and regulatory requirements associated with artificial intelligence. KCPT
004 Use and critically engage with academic sources related to ethics and regulation of artificial intelligence. KCPT

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

Methods of Teaching / Learning

Tutorials and guided learning will expose students to the complexities of each topic, evaluating and examining key theories in more depth and through the application of knowledge to real and hypothetical scenarios. The teaching strategy is also designed to encourage independent study and research. Students will be provided with preliminary reading references but will be expected to undertake additional research into each topic under their own steam. During tutorials, students will be expected to demonstrate their ability to apply that research to discuss given ethical and regulatory problems, to demonstrate self-direction and originality in tackling and proposing solutions to such problems, and to evaluate critically current research and advanced scholarship in relevant areas. 
The learning and teaching methods include: tutorials, guided learning (including participation in the module’s discussion forums), independent learning.
The module delivery is supplemented by guidance provided via the online module area.

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list
Upon accessing the reading list, please search for the module using the module code: LAWM174

Other information

We are committed to developing graduates with strengths in Employability, Digital Capabilities, Global and Cultural Capabilities, Sustainability, and Resourcefulness and Resilience. This module is designed to allow students to develop knowledge, skills, and capabilities in the following areas:
Employability: The knowledge, understanding, qualities and skills that are developed through module tutorials, guided learning, independent learning and assessments, provide students with the opportunity to develop important transferable skills required for future employment and professional identity, such as adaptability, resilience, written communication skills, and time-management skills. 
Digital capabilities: This module places a special focus on the relationship between ethics, law, and technology. Students develop skills in using technology for legal analysis, which is necessary in the field of ethics and regulation of artificial intelligence. Students develop analytical skills to solve complex problems, developing an understanding of both the theoretical and practical implications of technology on the regulation of artificial intelligence.
Global and cultural capabilities: This module allows students to gain global and cultural awareness, such as the different approaches to artificial intelligence regulation across major jurisdictions (the EU, the U.S., China). Students acquire an insight into the global social, legal and economic implications of AI technologies. 
Sustainability: Students examine whether AI technology systems create a sufficiently robust, ethical and sustainable solution and explore the moral and ethical issues related to AI.
Resourcefulness and Resilience: Students will develop resourcefulness and resilience through embracing academic opportunities and the methodology adopted in this module. Students will actively participate during interactive tutorials and assume responsibility to improve their learning. The module tutorials, guided learning, independent learning and assessment encourage students to think critically and to carry out research to address complex issues. This develops students’ approach to a deeper level of understanding and independent learning.

Programmes this module appears in

Programme Semester Classification Qualifying conditions
People-Centred Artificial Intelligence (Online) MSc 1 Compulsory A weighted aggregate mark of 50% is required to pass the module

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2025/6 academic year.