Posts, Privacy, and Plight – Investigating Ethical Boundaries of Consumer Data Usage for AI Training

Khyati Jagani () and Sanjuktha Vikram
Additional contact information
Khyati Jagani: FLAME University
Sanjuktha Vikram: FLAME University

A chapter in Marketing in the Digital Age, 2026, pp 265-286 from Springer

Abstract: Abstract The swift digitisation of society and the widespread use of Artificial Intelligence, AI Training, Social Media, Ethics, Privacy Concerns (AI) technologies have presented fresh obstacles to data security and privacy, especially with the employment of user-generated information on social media platforms. This study looks at privacy regarding privacy policy modifications, which permit the company to train its AI models using publicly uploaded photos, videos, and other information on social media. This study investigates the concerns of young consumers in India regarding these social media policy change and their perceptions of data security and platform trust. This exploratory study uses semi-structured, in-depth interviews to understand the perspectives of users who manage public accounts on consent, transparency, and striking a balance between AI innovation and consumer privacy. The results will provide important context for understanding how this segment negotiates with privacy issues and whether they support or oppose using their public information for AI training. The findings will add to the ongoing conversation on moral AI procedures and the value of privacy in the digital era.

Keywords: Artificial intelligence; AI training; Social media; Ethics; Privacy concerns (search for similar items in EconPapers)
Date: 2026
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-95-6509-2_12

Ordering information: This item can be ordered from
http://www.springer.com/9789819565092

DOI: 10.1007/978-981-95-6509-2_12

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().