CM50304: AI challenge
[Page last updated: 02 August 2022]
| Academic Year: | 2022/23 |
| Owning Department/School: | Department of Computer Science |
| Credits: | 6 [equivalent to 12 CATS credits] |
| Notional Study Hours: | 120 |
| Level: | Masters UG & PG (FHEQ level 7) |
| Period: |
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| Assessment Summary: | CW 100% |
| Assessment Detail: |
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| Supplementary Assessment: |
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| Requisites: | |
| Learning Outcomes: | * Demonstrate knowledge of computer science and artificial intelligence. * Demonstrate knowledge of engineering and artificial intelligence. * Demonstrate knowledge of social science and artificial intelligence. * Show awareness of ethical issues in specifying and designing AI systems. * Critical evaluation of the specification and design of AI systems. * Recognise and critically analyse state of the art developments in AI. * Specify, design, conduct and reflect upon original research into AI systems. |
| Aims: | * To expose students to current challenges in artificial intelligence from academic, industrial, and social perspectives. * To enable students to reach judgements in respect of accountability, responsibility and transparency about solutions to artificial intelligence challenges. * To teach and to allow students to put into practice their developing awareness of ethical and related challenges in artificial intelligence in society. * To give students experience of researching advanced topics in computer science, with a particular focus on artificial intelligence, exposure to the state of the art, undertaking a study and presenting the results. |
| Skills: | * Problem solving (T/F/A). * Working with others (T/F/A). * Working in (interdisciplinary) teams (T/F/A). * Ability to reason analytically and scientifically (T/F/A). * Ability to research, apply, present and argue about the state of the art in AI (T/F/A). * Apply critical thinking and problem solving to a case study (F/A). * Use appropriate evidence, and standards of logic and argumentation to support claims (F/A). * Use appropriate standards of referencing, citations and presentation (F/A). |
| Content: | Course content will draw on a range of foundational, key historical and state of the art material across computer science, engineering and social science. Topics include:
* Effective team working. * Different interpretations of accountability, responsibility and transparency in science, social science and society. * Guest lectures on AI challenges from CDT partners (industry, NGOs, government and academics) and other external parties. * Co-creation of responses to challenges with CDT partners and other external parties. * Team project addressing one of the challenges identified, drawing on relevant literature, to specify, design and build a prototype solution and to reflect critically on the extent to which it meets accountability, responsibility and transparency concerns. |
| Programme availability: |
CM50304 is Compulsory on the following programmes:Department of Computer Science
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Notes:
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