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Unit information: Responsible AI in 2021/22

Unit name Responsible AI
Unit code COMSM0027
Credit points 10
Level of study M/7
Teaching block(s) Teaching Block 2 (weeks 13 - 24)
Unit director Professor. Charlesworth
Open unit status Not open
Pre-requisites

None

Co-requisites

None

School/department Department of Computer Science
Faculty Faculty of Engineering

Description including Unit Aims

This unit gives a solid grounding in fairness, accountability, transparency, privacy and trustworthiness in AI, and related concepts relating to ethics, law and regulation. Using case studies we will present and analyse these concepts from the perspective of industry, academia and government. Wherever possible these case studies will be drawn from PhD projects from earlier-cohort CDT students or other PhD students in the school.

Intended Learning Outcomes

Upon successful completion of this unit students will be able to:

  1. recognise the main sources of algorithmic bias in AI systems;
  2. identify and describe key concepts in algorithmic fairness, accountability, transparency, and privacy
  3. identify and discuss the main ethical and regulatory context in which AI systems operate;
  4. present a case study with a critical analysis of these concepts as has arisen in recent practice.

Teaching Information

Teaching will be delivered through a series of mostly synchronous sessions, including lectures, seminars, practical activities, discussion groups and self-directed exercises.

Assessment Information

The unit will be assessed through an essay (~ 2,000 words) drawing on literature study and selected case studies. (100%) ILOs 1-4.

Resources

If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.

If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. COMSM0027).

How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours of study to complete. Your total learning time is made up of contact time, directed learning tasks, independent learning and assessment activity.

See the Faculty workload statement relating to this unit for more information.

Assessment
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit. The Board considers each student's outcomes across all the units which contribute to each year's programme of study. If you have self-certificated your absence from an assessment, you will normally be required to complete it the next time it runs (this is usually in the next assessment period).
The Board of Examiners will take into account any extenuating circumstances and operates within the Regulations and Code of Practice for Taught Programmes.

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