Cryptographic Provenance and the Future of Media Authenticity: Technical Standards and Ethical Frameworks for Generative Content - Pallav Laskar (Journal of Computer Science and Technology Studies, 2025)
The proliferation of generative artificial intelligence has fundamentally transformed digital media creation, enabling unprecedented democratization of content production while simultaneously eroding traditional markers of authenticity. Content provenance standards, particularly the Coalition for Content Provenance and Authenticity (C2PA) framework, emerge as critical infrastructure for establishing verifiable chains of custody in digital assets. These cryptographic systems embed signed manifests, hash-chained edit histories, and tamper-evident thumbnails directly into media headers, creating immutable records of content origin and modification. Browser-level verification interfaces and cross-platform authentication networks form the user-facing layer of this trust architecture. However, technical solutions alone cannot address the multifaceted challenges posed by synthetic media. Identity attestation schemes must navigate the tension between creator privacy and public accountability, while policy frameworks struggle to differentiate between legitimate creative remixing and malicious deepfake production. The proposed ethical framework integrates transparent AI labeling requirements, opt-out dataset governance mechanisms, and multi-stakeholder verification coalitions. This convergence of cryptographic technology, regulatory policy, and ethical principles offers a pathway toward preserving epistemic integrity in digital communications without stifling innovation. The success of these initiatives depends on widespread adoption across platforms, standardization of verification protocols, and public education about content authenticity indicators. As generative technologies continue to evolve, content provenance systems represent both a technical necessity and a social contract for maintaining shared truth in an era of infinite synthetic possibilities.