Human Oversight in AI

Under the Digital Personal Data Protection Act, 2023 (DPDP Act), human oversight in AI refers to the involvement of human review, monitoring, and decision-making when artificial intelligence systems process personal data. As organizations increasingly use AI systems for automated analysis, recommendations, and decision support, human oversight helps ensure that personal data processing remains accountable, transparent, and aligned with the intended purpose.

AI systems may process personal data during activities such as customer interactions, analytics, personalization, fraud detection, or automated decision-support processes. Without appropriate oversight, organizations may face challenges in understanding how personal data is being used, identifying incorrect outputs, managing risks, and ensuring that AI-driven processes remain consistent with privacy commitments made to Data Principals.

The DPDP Act does not specifically mention artificial intelligence or mandate human oversight for AI systems. However, when AI systems process personal data, Data Fiduciaries remain responsible for complying with applicable obligations under the Act, including lawful processing, providing notices, implementing reasonable security safeguards, and protecting personal data from misuse or Personal Data Breaches.

In practice, gaps emerge when:

• Organizations use AI systems to process personal data without clear accountability.
• AI outputs involving personal data are accepted without review or validation.
• Teams cannot identify what personal data is being used by AI systems.
• AI-related processing purposes are not documented clearly.
• Personal data risks from AI usage are not assessed before deployment.

Organizations address these challenges by defining AI usage policies, maintaining visibility into personal data used by AI systems, assigning accountability, conducting privacy reviews, monitoring AI-related processing, and maintaining governance records. Within Privy, capabilities such as data discovery, data classification, data mapping, privacy assessments, and governance workflows help organizations understand and manage personal data processing across technology environments.