Artificial intelligence and automated contracting in electronic commerce

Kambovski, Igor (2024) Artificial intelligence and automated contracting in electronic commerce. In: International Scientific Conference - Legal Principles in Contemporary Law, 18 Apr 2024, Faculty of Law, University of Niš, Serbia. (Submitted)

Text Zbornik sazetaka, Pravni fakultet u Nisu, 2024 - Kambovski.pdf - Presentation Download (1MB)

Abstract

AI is useful for analysis and processing of large databases,
which includes contract pattern recognition, anomaly identification, optimization, etc. AI can quickly absorb and analyze data, it can identify inapplicable clauses and warn
the user about possible errors in the stages of preparing an electronic contract. In the post-contract phase, AI is expected to monitor the implementation of rights and obligations arising from the contract. It can also prevent delays or deviations in the contract performance phase. However, the potential use of a fully autonomous AI system
for concluding contracts is worrisome. When an AI system makes an offer or accepts an offer on behalf of a merchant, without the merchant's explicit knowledge of the
exact content of such an agreement, can this offer or acceptance be considered valid? Has a contract been concluded and is it legally binding on both parties? Autonomous contracting based on AI has the potential and tendency to change the basic classical postulates of contract law. AI can create, review, analyze and give a recommendation for a contract in a short period of time. However, the lack of transparency, responsibilities
and fairness in the creation and management of the life cycle of the contract is of crucial importance for the contract itself. Therefore, it is necessary to make complicated decisions and create the contract with a "human touch".

Item Type:	Conference or Workshop Item (Paper)
Subjects:	Social Sciences > Law
Divisions:	Faculty of Law
Depositing User:	Igor Kambovski
Date Deposited:	15 Jan 2025 10:01
Last Modified:	15 Jan 2025 10:01
URI:	https://eprints.ugd.edu.mk/id/eprint/35433

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