Programme/Approved Electives for 2024/25
None
Available as a Free Standing Elective
No
Aims
This module will provide the students with an understanding of Data Ethics and Security. They will explore relevant regulations, governance frameworks and standards required for ethically aligned design and how these relate to different aspects of the data science lifecycle. They will apply this knowledge via techniques and tools that can be applied to areas such as data anonymisation, debiasing, and fairness testing.
Intended Learning Outcomes
1Apply the different methods for data anonymisation and psuedoanonymisation and how to protect identification: 1Analyse datasets and algorithmic outcomes for bias by using summative statistics, performance metrics and fairness tests. This will include demonstrating an understanding of protected characteristics and proxy features and methods for debiasing and/or mitigating for bias: 1Compare the data security techniques that can be employed to ensure data privacy and security: 1Test the legislative and governance landscape associated with ethical data science including key legislation such as GDPR, Data Protection Act and international standards and ethics panels: 1Debate the role of accountability and transparency methods and techniques in their provision of Data Science and AI solution that can be understood by humans:
10 hours of practical work6 hours of tutorials14 hours of online lectures120 independent learning
Description of Module Assessment
1: Portfolio weighted 100%Portfolio of practical and theoretical activitiesA portfolio of two case studies with practical and theoretical components that will draw from the skills and content acquired from the module. For each case study, a 1000-word report will be expected.