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Common law principles of contract viewed in the context of artificial intelligence

Mini Dissertation (LLM (Law of Contract))--University of Pretoria, 2023.

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Other Authors: Cornelius, Steve J.
Format: Thesis
Language:English
Published: University of Pretoria 2024
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access_status_str Open Access
author2 Cornelius, Steve J.
author_browse Cornelius, Steve J.
author_facet Cornelius, Steve J.
collection Thesis
dc_rights_str_mv © 2023 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.
description Mini Dissertation (LLM (Law of Contract))--University of Pretoria, 2023.
format Thesis
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institution University of Pretoria (South Africa)
language English
last_indexed 2026-06-10T12:40:34.602Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository
publishDate 2024
publishDateRange 2024
publishDateSort 2024
publisher University of Pretoria
publisherStr University of Pretoria
record_format dspace
source_str UPSpace — University of Pretoria Institutional Repository
spelling oai:repository.up.ac.za:2263/94875 Common law principles of contract viewed in the context of artificial intelligence Cornelius, Steve J. u21794902@tuks.co.za Mabasa, Khobae Clementine UCTD Artificial intelligence Interpretion Machine System Code Mini Dissertation (LLM (Law of Contract))--University of Pretoria, 2023. Contract formation in the new age of advanced Artificial Intelligence has brought about varied world-wide legal concerns and debates. A preeminent and emerging legal concern is the legal capacity of the autonomous systems and machines that are based and function on advanced Artificial Intelligence. Further, legal debates raised questions of whether contracts that are concluded by autonomous AI-driven systems and machines should be legally recognised as valid and enforceable. The primary aim of the research is to analyse the South African common law principles of contract by determining whether the principles are relevant and applicable to contracts concluded by autonomous AI-driven systems and machines. The principles are discussed and viewed in the context of advance Artificial Intelligence. Various theories of contractual interpretation are analysed in an attempt to find the most suitable theory for the interpretation of the affected contracts. The drafting process of code-based contracts and prescribed formalities thereof are also discussed. The dissertation is concluded with guidelines and recommendation for the successful application of AI machine-based contracts. Private Law LLM (Law of Contract) Unrestricted Faculty of Laws SDG-09: Industry, innovation and infrastructure 2024-02-22T14:38:40Z 2024-02-22T14:38:40Z 2024-04 2023 Mini Dissertation * A2024 http://hdl.handle.net/2263/94875 en © 2023 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria
spellingShingle UCTD
Artificial intelligence
Interpretion
Machine
System
Code
Common law principles of contract viewed in the context of artificial intelligence
title Common law principles of contract viewed in the context of artificial intelligence
title_full Common law principles of contract viewed in the context of artificial intelligence
title_fullStr Common law principles of contract viewed in the context of artificial intelligence
title_full_unstemmed Common law principles of contract viewed in the context of artificial intelligence
title_short Common law principles of contract viewed in the context of artificial intelligence
title_sort common law principles of contract viewed in the context of artificial intelligence
topic UCTD
Artificial intelligence
Interpretion
Machine
System
Code
url http://hdl.handle.net/2263/94875