Artificial Intelligence and the Right to Privacy:
Emerging Challenges in the Digital Age

Introduction

The term ‘privacy’ originates from the Latin word ‘Privatus’, which signifies isolation, restriction, personal matters, or uniqueness. Although there is no universally accepted definition, Black’s Law Dictionary defines privacy as “the right to be let alone; the right of a person to be free from unwarranted publicity; and the right to live without unwarranted interference by the public in matters that do not necessarily concern them.” (Dhiman)

The rapid growth and expansion of Artificial Intelligence (AI) across key sectors—including healthcare, finance, and public governance—has ushered in an era of unprecedented convenience, speed, and analytical capability. However, technological boons inherently introduce complex legal challenges, most notably concerning the fundamental Right to Privacy.

Privacy is protected by international human rights frameworks, including the Universal Declaration of Human Rights (UDHR) and the International Covenant on Civil and Political Rights (ICCPR). In recent years, legislators and judiciary bodies worldwide have recognized that privacy rights extend beyond physical spaces to encompass technological, digital, and electronic environments (Kumar Aluri & Rani 77).

How AI Technologies Affect Privacy

AI presents novel risks to personal data protection. Government agencies and law enforcement bodies in India have adopted various AI-driven technologies, raising significant privacy concerns:

Facial Recognition Deployments: Systems like the Automated Facial Recognition System (AFRS), initially introduced for specific criminal identification purposes, have reportedly seen expanded use during public demonstrations, such as the 2020 CAA protests. Such broad deployment creates chilling effects on freedom of speech and peaceful assembly under Article 19, while impinging upon personal liberty under Article 21 of the Constitution (Jha).

Unconsented Data Harvesting: Commercial entities, e-commerce platforms, and health-tracking applications frequently gather vast troves of personal data without clear user knowledge or explicit consent.

Generative AI Systems: Large Language Models (LLMs) and Generative AI platforms (such as ChatGPT or Google Gemini) rely on massive datasets for training. Their inner processing mechanisms often operate opacity, creating risks around indefinite data storage, unauthorized reuse, and repurposed processing beyond the original scope of collection.

Statutory Exemptions: Section 17 of the Digital Personal Data Protection (DPDP) Act, 2023 provides broad exemptions to government agencies on grounds such as state security or public order, raising concerns regarding unchecked state surveillance.

Legal Framework in India

1. The Constitution of India, 1950

The constitutional architecture provides the public-law foundation for data protection and AI regulation. Articles 14, 19, and 21 guarantee equality, basic freedoms, and personal liberty, supported by remedial jurisdiction under Articles 32 and 226. Legislative power under Articles 245, 246, 248, and 253 empowers Parliament to enact national digital governance laws, including those with extra-territorial reach when digital effects cross borders.

2. The Digital Personal Data Protection Act, 2023 (DPDP Act)

The primary statutory framework balances two core objectives: protecting individual personal data rights and allowing lawful processing by data fiduciaries. As statutory provisions take effect through phased notifications, tracking compliance timelines remains critical for evaluating organizational obligations and regulatory enforcement.

Key Challenges

Privacy & Biometric Risks: Massive processing of sensitive biometric and personal data exposes individuals to identity theft, tracking, and unauthorized profiling.

Absence of Informed Consent: Opaque data-gathering practices leave individuals unaware of when, how, or by whom their information is processed.

Algorithmic Bias: Training AI models on biased or non-representative datasets can result in automated discrimination in hiring, credit scoring, and law enforcement profiling.

Mass Surveillance: Unchecked, AI-driven surveillance enables real-time public monitoring, threatening free expression and public association.

Opacity (“Black Box” Problem): Complex neural networks often render automated decision-making processes unexplainable, complicating accountability when harmful or erroneous decisions occur.

Balancing AI Innovation and Digital Rights

While AI offers incredible advancements in healthcare diagnostics, education, and public service delivery, innovation must not bypass fundamental rights. Achieving an optimal balance requires embedding privacy-by-design, strict adherence to data minimization, dynamic consent models, robust audit mechanisms, and algorithmic transparency. State surveillance must remain strictly bounded by judicial oversight and the constitutional principles of necessity and proportionality.

Conclusion

Artificial Intelligence continues to reshape modern society, yet its rapid deployment poses acute challenges to fundamental rights, personal liberty, and digital sovereignty. The jurisprudence laid down in K.S. Puttaswamy v. Union of India serves as an essential legal compass. AI deployment must remain human-centric, ethical, transparent, and strictly compliant with constitutional safeguards.