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Unit information: Responsible AI in 2020/21

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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.

Reading and References

Selected literature, references and online material will be provided at the start of the unit

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