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Dissertation

Ethics of Machine Learning

As of 2019, Machine Learning is one of the fastest growing areas in Computer Science. The knowledge and trends we can extract from data is ever expanding. The amount of data, computational power and techniques available to build models which can predict present today is unprecedented, but so are the risks. Machine Learning is a field which is not immune to regulation and ethical standards.

This dissertation looked at publicly available data sets with attributes such as age, gender and race. Using Machine Learning algorithms and attribute selection, it researched areas of concern such as discrimination, data misuse and applications of Machine Learning. The experiment used Machine Learning algorithms to investigate whether further considerations should be taken when using data with sensitive attributes. This project will attempt to produce desensitised smaller data sets which can achieve similar accuracy to the full data set. It is important to build models which do not harm individuals. Additionally a public survey was conducted to find the concerns the public had with both Machine Learning and data usage in general.

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