2023/24 Taught Postgraduate Module Catalogue

LUBS5973M Human Centred AI

15 creditsClass Size: 100

Module manager: Linhao Fang
Email: L.Fang1@leeds.ac.uk

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2023/24

Module replaces

LUBS5312M

This module is not approved as an Elective

Module summary

Artificial intelligence (AI), and in particular machine learning, is increasingly used in organisations and society to inform decisions and to deliver products and services. AI provides tremendous capabilities, enabling individuals and organisations to achieve transformational objectives. AI is however a ‘black box’; it lacks transparency in how it derives its ‘predictions’ or recommendations, and its limitations are opaque or ambiguous. AI tends to reproduce and enhance existing biases in organisations or society, because it is built on data produced through processes that may be biased. The combination of biased data and lack of transparency creates serious challenges and risks for individuals, organisations and society. Efforts are being made worldwide to identify methods and approaches to build and use a more ‘human-centred AI’, in a responsible and accountable way, and capable to address people’s needs. This module equips students with the knowledge and skills to critically assess and manage the development, adoption and consequences of AI in organisations and society.

Objectives

Through this module students will develop a critical understanding of opportunities and challenges associated with implementing, using and evaluating AI. The module will cover current ideas, theories and approaches proposed to build and evaluate AI and make decisions about its development and use, in view of delivering AI systems that are responsive to human (society and individual) needs. Students should be aware that the module will not teach them technical skills for building AI. The focus of this module is on achieving a critical understanding of this new technology that will soon become pervasive in all walks of life. Organisations are increasingly implementing AI but they are often unaware of the ethical issues and risks associated with it.
Students will develop their learning through lectures and workshops, group and individual work, and guest lectures.

Learning outcomes
Upon completion of this module students will be able to:
1. Identify key ethical issues associated with the use of AI
2. Demonstrate knowledge and critical understanding of theories, approaches and methods applied to the development of human-centred AI
3. Critically evaluate the strengths and drawbacks of different AI systems
4. Develop and critically assess strategies to manage AI in organisations, and the associated challenges
5. Provide informed personal reflections on the consequences of AI for society and the future of work

Syllabus

Indicative content:
Foundational information about what AI entails and how/why it is different from other digital systems - with a specific focus on big data
Ethical and societal challenges and responsible use of AI
Human-centred approaches to AI development and adoption
AI as a socio-technical system
Human-AI collaboration, or how to work alongside AI (including robotics, automation)
Regulatory and management approaches to human centred AI

Teaching methods

Delivery type	Number	Length hours	Student hours
Workshop	4	2.00	8.00
Lecture	10	2.00	20.00
Private study hours			122.00
Total Contact hours			28.00
Total hours (100hr per 10 credits)			150.00

Private study

A variety of activities such as reading, engaging with case studies, listening to media materials, working in groups outside of class, preparing for assessments.

Opportunities for Formative Feedback

Students will be provided with the opportunity to submit a draft plan for their essay, and will receive written individual feedback on this.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
Essay	2,500 words	100.00
Total percentage (Assessment Coursework)		100.00

The resit for this module will be 100% by 2,500 word essay.

Reading list

The reading list is available from the Library website

Last updated: 26/03/2024

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