Modern Privacy Challenges
An analysis of contemporary privacy challenges — from AI and biometrics to cross-border data flows — and how the DPDPA addresses them.
🎯 Learning Objectives
- ▸ Identify contemporary privacy challenges
- ▸ Understand the intersection of technology and privacy
- ▸ Analyze how the DPDPA addresses modern challenges
- ▸ Identify emerging privacy issues that may require future regulation
Artificial Intelligence and Privacy
Artificial intelligence represents both an opportunity and a threat to privacy. AI systems can process vast amounts of data, identify patterns invisible to humans, and make decisions at scale. While these capabilities have enormous benefits, they also create new privacy risks.
AI-Specific Privacy Risks
- • AI training: Models trained on personal data may memorise and reproduce sensitive information
- • Inference: AI can infer sensitive information from seemingly harmless data
- • Profiling: AI can build detailed profiles that predict behaviour and vulnerabilities
- • Automated decisions: AI can make decisions about individuals without transparency
- • Bias: AI models can perpetuate or amplify discrimination
- • Scale: AI can process personal data at unprecedented scale
The DPDPA does not specifically address AI, but its general obligations apply. Data minimisation, purpose limitation, and security requirements all apply to AI systems. Significant Data Fiduciaries — which may include large AI companies — have additional obligations.
AI regulation is evolving globally. The EU AI Act (2024) is the first comprehensive AI law. India may follow with AI-specific regulations.
Biometric Data and Privacy
Biometric data — fingerprints, iris scans, facial recognition, voice patterns — presents unique privacy challenges. Unlike passwords, biometric data cannot be changed if compromised. Once your fingerprint is exposed, it is exposed forever.
Biometric Privacy Challenges
- • Permanence: Biometric data cannot be reset if compromised
- • Uniqueness: Biometric data is uniquely identifying
- • Sensitive inference: Biometric data can reveal health conditions, ethnicity, age
- • Mass collection: Biometric data is increasingly collected at scale
- • Function creep: Data collected for one purpose may be used for others
- • Security risks: Biometric databases are attractive targets for attackers
The DPDPA does not explicitly define "biometric data" as a special category, but its requirements apply. Data fiduciaries collecting biometric data should ensure explicit consent, strong security, and purpose limitation.
💡 Example
Aadhaar collects biometric data from over a billion Indians. While Aadhaar has specific legal protections, the risks of biometric data collection have been widely discussed, including surveillance and function creep.
Government Surveillance
Government surveillance — through Aadhaar, CCTV, drone monitoring, and internet surveillance — presents profound privacy challenges. While some surveillance is necessary for national security and public safety, it must be balanced against privacy rights.
The DPDPA provides some safeguards: data principals have rights, data fiduciaries have obligations, and the Data Protection Board enforces compliance. However, government processing for certain functions (like national security) may be exempt from some provisions.
Balancing government surveillance with privacy requires robust legal frameworks, independent oversight, and transparency. The DPDPA is part of this framework in India.
Cross-Border Data Flows
Data crosses borders constantly. A single transaction can involve servers in multiple countries, cloud providers in different jurisdictions, and third-party services across the globe. Cross-border data flows create complex privacy challenges.
Challenges of Cross-Border Data
- • Different legal standards across jurisdictions
- • Enforcement challenges across borders
- • Conflicting legal requirements (e.g., GDPR vs US law)
- • Security risks of international transfers
- • Inadequate protection in some destination countries
The DPDPA addresses cross-border flows through Section 16, which allows the government to restrict transfers to specific countries. Unlike GDPR's adequacy approach, DPDPA uses a blacklist approach — transfers are allowed unless restricted.
The DPDPA's approach is simpler but gives the government broad discretion. The first list of restricted countries has not yet been notified, so for now, most transfers are allowed. This may evolve as the government notifies restrictions.
💡 Example
An Indian company using a US-based cloud provider transfers personal data to the US. Under DPDPA, this is allowed (unless the US is notified as restricted). Under GDPR, however, this would require an adequacy decision or Standard Contractual Clauses.
These modern challenges — AI, biometrics, surveillance, cross-border flows — are not fully addressed by any single law. The DPDPA is an important step, but privacy protection in the digital age requires continuous legal and technical innovation.
📖 Glossary
- Biometric Data
- Data relating to physical or behavioural characteristics of a person, such as fingerprints, iris scans, or voice patterns.
- Function Creep
- The gradual expansion of a technology or data collection's use beyond its original purpose.
- Adequacy Decision
- A determination by the EU Commission that a country provides adequate data protection, allowing data transfers without additional safeguards.
- Cross-Border Data Flow
- The transfer of personal data from one jurisdiction to another.
🔑 Key Takeaways
- Modern privacy challenges are complex and multifaceted
- Technology creates new privacy risks that require new legal responses
- The DPDPA addresses many — but not all — modern privacy challenges
- Emerging technologies will require continuous updates to privacy law
📚 Further Reading
- The Age of Surveillance Capitalism — Shoshana Zuboff (2019)
- AI and Privacy — Journal of Data Protection (2022)
- Digital Personal Data Protection Act 2023 — Government of India (2023)
Shilpi Kulshrestha
Shilpi is a corporate lawyer with over a decade of experience in data protection, company law, and regulatory compliance. She has advised 50+ startups and enterprises on DPDPA readiness, privacy gover...