The emerging AI policy for e-commerce industry

Yildiz, Zehra Ozge and Beloff, Natalia (2020) The emerging AI policy for e-commerce industry. ICIIT 2020, Hanoi, Viet Nam, February 19–22, 2020. Published in: Proceedings of the 2020 5th International Conference on Intelligent Information Technology. 66-70. ACM ISBN 9781450376594

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Abstract

For the fast-growing e-Commerce industry, the AI is the game-changer but is it really utilised in a most effective way or is it just a risky 'artificial balloon'? Is it gambling to rely on AI technologies without forming a dedicated policy? To answer these questions and propose a cautious approach towards the emerging technologies, in this explanatory research, the risks related to the fast adaptation of AI technologies addressed with recommended actions. Within the scope of the research, eCommerce industry is analysed to reveal the issues related to AI implementations. Accordingly, the challenges of AI technologies have been questioned so that necessary precaution, preparation, and considerations can be pointed out. Accordingly, an AI policy for e-Commerce industry is formed for the businesses to benefit from the most recent technologies without risking the possible issues. Three main policy subjects have been determined as transparency of the technologies, accountability for the purpose, process and performance of them, and lastly, emerging user privacy and security related issues. For each policy subject, a review of the AI implementations, recent critics and forecasted expectations are investigated to list the recommendations for the candidate AI implementer. The research aims to provide an AI policy guideline for e-Commerce industry with a detailed overview of the outstanding issues, best practices and recommendations from scholars.

Item Type: Conference Proceedings
Schools and Departments: School of Engineering and Informatics > Informatics
SWORD Depositor: Mx Elements Account
Depositing User: Mx Elements Account
Date Deposited: 25 Jun 2021 07:38
Last Modified: 12 Aug 2021 07:38
URI: http://sro.sussex.ac.uk/id/eprint/99991

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