Human-Centred Artificial Intelligence (2025)
1. Programme Title:Human-Centred Artificial Intelligence |
NQF Level: |
7 |
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2. Description of the Programme (as in the Business Approval Form) |
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By joining our innovative MSc in Human-Centred Artificial Intelligence (HCAI), you will discover how to address the pressing problem of how to incorporate human-centred design principles into AI practice. By learning how to integrate human factors into AI development, you will gain not only technical prowess but also a deep understanding of the ethical, social, and psychological dimensions of AI. You will learn about how to address the ethical imperative of ensuring AI systems align with societal values and cater to human needs. You will learn about how generative AI and Large-Language Models works and how AI can be used to support human decision making and understand human emotions.
The skills that you learn will be interdisciplinary covering human-computer interaction, artificial intelligence, machine learning and their applications to problems of working with humans in areas such as business, environmental intelligence, health informatics and wellbeing. By prioritizing AI technology for interacting with humans, the programme supports careers that involve working with people including in finance, games design, user experience (UX), defence, law, assistive technology, creative industries, education, healthcare, transportation, and consumer services. It is also a strong foundation for a research career in Artificial Intelligence where there are a wide range of funded research studentships examining problems in the intersection of HCI and AI. Moreover, its interdisciplinary nature fosters collaboration across various research domains, driving innovation and advancing knowledge in the field of AI.
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3. Educational Aims of the Programme |
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This interdisciplinary MSc in Human-Centred Artificial Intelligence is designed to recruit students from a diverse range of academic backgrounds and produce graduates with a strong grounding in the state-of-the-art in contemporary human-centred AI approaches. Using a variety of teaching methods, including lectures, lab-based activities, and seminars, as well as both individual and group projects, students will explore and critically analyse human-centred approaches to solving real-world and societal problems using AI.
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4. Programme Structure |
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MSc Human-Centred Artificial Intelligence is a 1-year full-time programme of study at Regulated Qualifications Framework (RQF) level 7 (as confirmed against the FHEQ). Your programme is divided into units of study called ‘modules’ which are assigned a number of ‘credits’. The credit rating of a module is proportional to the total workload, with 1 credit being nominally equivalent to 10 hours of work. You will need to complete a total of 180 credits across your 12-month programme. This will be a mix of mandatory and optional modules, subject to change and timetabling requirements.
Interim / Exit Awards
If you do not complete the programme, you may be able to exit with a lower qualification.
A Postgraduate Diploma may be awarded when a student gains at least 120 credits from the compulsory modules.
A Postgraduate Certificate may be awarded when a student gains at least 60 credits from the compulsory modules.
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5. Programme Modules |
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Stage 1: 150 credits of compulsory modules, 30 credits of optional modules
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Stage 1
| Code | Title | Credits | Compulsory | NonCondonable |
|---|---|---|---|---|
| COMM514 | Research Project | 60 | Yes | Yes |
| ECMM443 | Introduction to Data Science | 15 | Yes | No |
| ECMM445 | Learning from Data | 15 | Yes | No |
| COMM109 | Programming with Python | 15 | Yes | No |
| ECMM422 | Machine Learning | 15 | Yes | No |
| COMM111 | Foundations of Human-Centred AI | 15 | Yes | No |
| COMM112 | Design Methods for Human-Centred AI | 15 | Yes | No |
| ECMM447 | Social Networks and Text Analysis | 15 | No | No |
| ECMM450 | Stochastic Processes | 15 | No | No |
| BEMM190 | Digital Transformation | 15 | No | No |
| BEMM071 | Leadership and Global Challenges | 15 | No | No |
| SOCM033 | Data Governance and Ethics | 15 | No | No |
6. Programme Outcomes Linked to Teaching, Learning & Assessment Methods |
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| On successfully completing the programme you will be able to: | Intended Learning Outcomes (ILOs) will be accommodated & facilitated by the following learning & teaching and evidenced by the following assessment methods: | |||
A Specialised Subject Skills & Knowledge
1. Demonstrate knowledge and the ability to design human-centred applications.
2. Show awareness of the social context of computer science, including key aspects of data governance, legal requirements, and ethical considerations.
3. Show awareness of the organisational context of artificial intelligence, including how professional software development and security are used for robust computing systems in business.
4. Apply human-centred artificial intelligence methods to solve domain specific problems.
| Learning & Teaching ActivitiesLectures, workshops, seminars, practicals, online materials and formal training. Each module also has core and supplementary texts, or material recommended by module deliverers, which provide in-depth coverage of the subject and go beyond the lectures. | |||
Assessment Methods
The assessment strategy for each module is explicitly stated in the full module description given to students. Group and team skills are addressed within modules dealing with specialist and advanced skills.
Assessment methods will include essays, technical reports, closed book tests, practical exercises in programming and data analysis, project work, and individual and group presentations.
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B Academic Discipline Core Skills & Knowledge
5. Critically analyse and interpret relevant academic and technical literature.
6. Demonstrate competence in the mathematical and computational techniques required to design HCAI systems.
7. Effectively design AI software to solve practical problems.
8. Use appropriate HCI methods and AI algorithms depending on the problem.
9. Critically evaluate the reliability, transparency, and accountability of human-centred AI systems, considering their implications for users, stakeholders, and society.
10. Use appropriate tools and processes to support human values, ensure traceability, and promote responsible innovation in human-centred AI systems.
11. Appreciate the basic legal and regulatory requirements for data privacy, ethical use of data, and data governance.
| Learning & Teaching ActivitiesLectures, workshops, seminars, practicals, online materials and formal training. Each module also has core and supplementary texts, or material recommended by module deliverers, which provide in-depth coverage of the subject and go beyond the lectures. | |||
Assessment Methods
The assessment strategy for each module is explicitly stated in the full module description given to students. Group and team skills are addressed within modules dealing with specialist and advanced skills.
Assessment methods will include essays, technical reports, closed book tests, practical exercises in programming and data analysis, project work, and individual and group presentations.
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C Personal / Transferable / Employment Skills & Knowledge
12. Effectively communicate methods and designs of AI Systems based on HCI informed analysis of human behaviour in both written reports and oral presentations.
13. Demonstrate awareness of tools and technologies relevant to human-centred AI.
14. Design and manage an HCAI project from initiation to final report.
15. Work effectively independently or in a team.
| Learning & Teaching ActivitiesLectures, workshops, seminars, practicals, online materials and formal training. Each module also has core and supplementary texts, or material recommended by module deliverers, which provide in-depth coverage of the subject and go beyond the lectures. | |||
Assessment Methods
The assessment strategy for each module is explicitly stated in the full module description given to students. Group and team skills are addressed within modules dealing with specialist and advanced skills.
Assessment methods will include essays, technical reports, closed book tests, practical exercises in programming and data analysis, project work, and individual and group presentations.
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7. Programme Regulations |
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Full details of assessment regulations for all taught programmes can be found in the TQA Manual, specifically in the Credit and Qualifications Framework, and the Assessment, Progression and Awarding: Taught Programmes Handbook. Additional information, including Generic Marking Criteria, can be found in the Learning and Teaching Support Handbook. |
8. College Support for Students and Students' Learning |
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In accordance with University policy, a system of personal tutors is in place for all students on this programme. A University-wide statement on such provision is included in the University's TQA Manual. As a student enrolled on this programme, you will receive the personal and academic support of the Programme Coordinator and will have regular scheduled meetings with your Personal Tutor; you may request additional meetings as and when required. The role of personal tutors is to provide you with advice and support for the duration of the programme and extends to providing you with details of how to obtain support and guidance on personal difficulties, such as accommodation, financial difficulties and sickness. In addition to this, a Pastoral Mentor is also available for all students on this programme to engage with. The Pastoral Mentor can offer further support around wellbeing and academic concerns, and offers regular opportunities for students to engage with them, such as bookable meetings. You can also make an appointment to see individual teaching staff. Student/Staff Liaison Committee enables students & staff to jointly participate in the management and review of the teaching and learning provision. Online Module study resources provide materials for modules that you are registered for, including recording of lectures, as well as useful subject and IT resources. Generic study support resources, library and research skills, past exam papers, and the 'Academic Honesty and Plagiarism' module are also available through the student portal. Information Technology (IT) Services provide a wide range of services throughout the Exeter campuses including open access computer rooms, some of which are available 24 hours, 7 days a week. Help may be obtained through the Helpdesk, and most study bedrooms in halls and flats are linked to the University's campus network. Additionally, the department has its own dedicated IT support staff, helpdesk and computer facilities which are linked to the wider network, but which also provide access to some specialised software packages. Email is an important channel of communication between staff and students in the department and a student handbook is available with relevant information for your studies. The department has dedicated access to two new state-of-the-art computer labs (Lovelace and Babbage), where practical sessions of modules are typically held and that students can also use for self-studying and group work. |
10. Admission Criteria |
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Undergraduate applicants must satisfy the Undergraduate Admissions Policy of the University of Exeter. Postgraduate applicants must satisfy the Postgraduate Admissions Policy of the University of Exeter. Specific requirements required to enrol on this programme are available at the respective Undergraduate or Postgraduate Study Site webpages.
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11. Regulation of Assessment and Academic Standards |
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Each academic programme in the University is subject to an agreed Faculty assessment and marking strategy, underpinned by institution-wide assessment procedures. The security of assessment and academic standards is further supported through the appointment of External Examiners for each programme. External Examiners have access to draft papers, course work and examination scripts. They are required to attend the Board of Examiners and to provide an annual report. Annual External Examiner reports are monitored at both Faculty and University level. Their responsibilities are described in the University's code of practice. See the University's TQA Manual for details. |
12. Indicators of Quality and Standards |
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Certain programmes are subject to accreditation and/or review by professional and statutory regulatory bodies (PSRBs). |
| 14 | Awarding Institution | University of Exeter | |
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| 15 | Lead College / Teaching Institution | Faculty of Environment, Science and Economy | |
| 16 | Partner College / Institution | ||
| 17 | Programme accredited/validated by | ||
| 18 | Final Award(s) | MSc | |
| 19 | UCAS Code (UG programmes) | HUMCENAI | |
| 20 | NQF Level of Final Awards(s): | 7 | |
| 21 | Credit (CATS and ECTS) | 180/90 | |
| 22 | QAA Subject Benchmarking Group (UG and PGT programmes) | ||
| 23 | Origin Date | November 11th 2024 | Last Date of Revision: | September 11th 2025 |
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