Analyzing The Adequacy Of India’s Data Protection Frameworks For Hyper- Personalization Of AI Systems
- IJLLR Journal
- 1 hour ago
- 1 min read
Tanisha Mathur, Christ University, India
ABSTRACT
Hyper-personalization is the method where real-time data, AI, and machine learning create individual-centered experiences, products, and messages. Hyper-personalization helps brands create unique personalized interactions using and analyzing real-time personal information. This leads to extreme risks in terms of privacy, consent, algorithmic transparency, and discrimination. These algorithms should be made aware not only to regulatory bodies but to end users as well.
Regulatory frameworks such as GDPR (General Data Protection Regulation), India’s Data Protection Act, and the emerging EU AI Act emphasize informed consent, legitimate interest, and minimization of data, thus placing a strong compliance infrastructure at the core of developing lawful hyper-personalized systems. Over-personalization can lead to manipulative or discriminatory practices. To tackle these problems in India, the current regulatory framework is inadequate and needs to be made more adaptable with different frameworks active in more developed countries, such as the US and the UK. It is recommended that ethical guardrails, algorithmic auditing, and privacy-friendly design should be implemented.
Keywords: Hyper-Personalization, Experience Design, Data Protection Law, Privacy Law, Artificial Intelligence, Indian DPDP Act, GDPR
