Exploring the Balance Between Personalisation and Automation in Human–AI Interaction

Abstract

This study investigates the intricate relationship between personalisation and automation in Artificial Intelligence (AI), focussing on their impact on human interactions. The purpose is to discern patterns significantly influencing modern society, using notable examples from e-commerce, social media and digital advertising. The research employs a multifaceted approach, drawing insights from real-world examples of AI implementation. Noteworthy instances include Amazon's use of AI algorithms for personalised product recommendations, Netflix's application of AI in content recommendations and Tesla's Full Self-Driving feature in autonomous vehicles. The findings reveal the dual nature of personalisation and automation. In e-commerce, personalised recommendations, such as those on Amazon, can lead to impulse buying and potential financial strain. Similarly, social media algorithms, like Facebook's echo chamber and advertising strategies, exemplified by Google's ‘skippable’ and ‘non-skippable’ ads, strategically influence user behaviour and decision-making. The research also highlights the success of Netflix's personalised content delivery and the potential safety challenges in Tesla's Full Self-Driving feature. The study underscores the importance of a balanced approach to personalisation and automation, especially in ethical considerations, user privacy and data security.

Citation

Will Arachchige, I.S., Jahankhani, H., Oshadi Karunanayaka, K.A.Y.R. and Amin Metwally Hussien, O.A. (2024), "Exploring the Balance Between Personalisation and Automation in Human–AI Interaction", Dadwal, S.S., Jahankhani, H. and Revett, K. (Ed.) Market Grooming, Emerald Publishing Limited, Leeds, pp. 199-234. https://doi.org/10.1108/978-1-83549-001-320241010