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.

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

  • Khyati Jagani,
  • Sanjuktha Vikram

摘要

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.