How AI training models could compromise privacy

Source: The post “How AI training models could compromise privacy” has been created based on “How AI training models could compromise privacy” published in “The Hindu” on 3 November 2026. How AI training models could compromise privacy.

UPSC Syllabus: GS 3 – Science and Technology

Context: The right to privacy is a constitutional right upheld by the Supreme Court in Justice K. S. Puttaswamy v. Union of India (2017) judgment. The rapid development of Artificial Intelligence (AI) has raised concerns regarding the collection, processing and use of personal data, which may compromise individual privacy and fundamental rights.

How AI training models threaten privacy

1. Unauthorised collection of data: AI companies collect large amounts of personal information from the internet, including social media platforms, websites and other publicly accessible sources, often without users’ informed consent.
2. Extraction of personal information: AI models may memorise sensitive information during training and reproduce it in response to specific queries, thereby exposing private information.
3. Identification of individuals: Studies suggest that AI models can be queried to extract personal details that they have memorised during training, potentially identifying individuals and building their profiles.
4. Exposure of sensitive information: Personal data may include names, gender, sexual orientation, institutional affiliations, images, videos, browsing history and other behavioural patterns.
5. Lack of meaningful consent: Users may not be adequately informed that their personal data is being used to train AI models, limiting their ability to exercise control over their information.
6. Profiling and discrimination: The misuse of personal data can facilitate profiling and discriminatory practices, affecting individual autonomy and fundamental rights.

Legal and regulatory concerns in India

1. Digital Personal Data Protection Act, 2023: The Act was enacted in 2023, and the DPDP Rules were notified in November 2025. The framework seeks to regulate the processing of digital personal data and strengthen data protection.
2. Consent and safeguards: The framework provides for consent, notice and other safeguards governing the processing of personal data, subject to applicable provisions and exemptions.
3. Uncertainty regarding AI training: Questions remain regarding the application of data protection requirements to information collected from publicly accessible sources and subsequently used for AI training.
4. Limitations of the right to erasure: The ability to delete personal data does not necessarily mean that information already incorporated into a trained AI model can be completely removed.
5. Right to object: Indian users currently lack a fully effective, general right to object to the use of their personal data for AI training.

Challenges arising from AI companies’ practices

1. Use of publicly available data: Companies such as Meta, Amazon and Google collect publicly available information to train AI models, raising concerns about whether public accessibility should be treated as consent for AI training.
2. Limited opt-out mechanisms: Meta provides users in the European Union with an option to object to the use of their public data for AI training, while comparable protection is not available to Indian users.
3. Weak accountability: Companies may use personal data for purposes beyond those originally intended, while individuals may have limited knowledge of how their information is processed.
4. Risk of commercial exploitation: AI-driven profiling may allow corporations to derive sensitive insights about individuals, potentially weakening their autonomy and privacy.

Measures to protect privacy

1. Strengthening legal safeguards: India should ensure effective implementation of the Digital Personal Data Protection framework and clarify its application to AI training, inferred information and publicly available personal data.
2. Ensuring transparency: AI companies should clearly disclose the sources of training data, the purposes of processing and the safeguards adopted to protect personal information.
3. Providing meaningful consent and opt-out options: Users should have accessible mechanisms to object to the use of their personal data for AI training, wherever required under the applicable legal framework.
4. Promoting privacy-by-design: AI developers should incorporate privacy safeguards at every stage of model development, including data collection, training, deployment and subsequent processing.
5. Limiting data collection: Companies should collect and retain only the personal data necessary for legitimate purposes and adopt suitable techniques to reduce the exposure of sensitive information.
6. Strengthening accountability: Regulatory authorities should ensure compliance through appropriate monitoring, enforcement and penalties for violations.
7. Improving technical safeguards: AI developers should test models for memorisation and unintended disclosure of personal information and adopt appropriate measures to reduce such risks.
8. Protecting vulnerable groups: Special attention should be given to preventing discriminatory profiling and the misuse of personal data belonging to vulnerable individuals.
9. Encouraging responsible innovation: The government should promote AI innovation while ensuring that commercial interests do not undermine constitutional rights and individual privacy.

Conclusion: AI offers significant opportunities for economic and social development, but its benefits must not come at the cost of individual privacy. India needs a balanced approach combining effective data protection laws, transparency, accountability and privacy-preserving AI technologies to ensure responsible and rights-based AI development.

Question: “Artificial Intelligence training models pose significant challenges to individual privacy and data protection.” Discuss the concerns associated with AI training models in India and suggest measures to address them.

Source: The Hindu