Electronic Theses and Dissertations (Masters)

Permanent URI for this collectionhttps://hdl.handle.net/10539/37939

Browse

Filters

2023 - 20242

Settings

Subject: search.filters.subject.UCTDSubject: search.filters.subject.SDG-9: Industry, innovation and infrastructureSubject: search.filters.subject.Artificial intelligence

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Artificial intelligence and automated decision making under the GDPR and the POPIA
    (University of the Witwatersrand, Johannesburg, 2024) Goldman, Gavin David; Zitzke, E.
    This analysis considers the concepts of AI and machine learning and examines their reliance on the processing of personal data and the challenges this poses from a data- privacy and human-rights perspective, particularly in relation to profiling. It evaluates the effectiveness of the General Data Protection Regulation (GDPR) and the Promotion of Personal Information Act 4 of 2013 (POPIA) in regulating Automated Decision Making (ADM) and considers the limitations of the right to an explanation under these provisions. The analysis proposes that the current framework of the GDPR and POPIA does not clearly address the issue of explainability and that the focus should shift to providing a data subject with a counterfactual to give practical effect to this right which would better serve data subjects
  • Thumbnail Image
    Item
    A practical review of the effectiveness of artificial intelligence in the automated review of legal contracts
    (University of the Witwatersrand, Johannesburg, 2023) Fouché, Jacques Gerrit
    This research report compares the performance of AI-driven automated contract review platforms with that of human contract reviewers, aiming to see improved effectiveness for the elements of time, cost and quality. An empirical study is done by comparing the specific performance of an automated contract review platform provider, Lawgeex, to the human contract reviewers of a business entity, Endress+Hauser. The results of the effectiveness assessment are reported on through dashboard data and questionnaires to the users of the platform. Recommendations are made both in general and specific to the two entities of the empirical study