Artificial Intelligence for Culture and Languages
Kartavya Desk Staff
Source: PIB
Subject: Indian Culture
Context: The PIB released a comprehensive update on India’s institutionalization of Artificial Intelligence for Culture and Languages, highlighting how national AI platforms are being leveraged to bridge the gap between heritage and modern participation
About Artificial Intelligence for Culture and Languages:
What it is?
• This initiative represents a strategic shift from merely preserving cultural resources to enabling active cultural participation. By leveraging AI, the Government of India aims to democratize technology, making manuscripts, monuments, and oral traditions accessible to citizens in their native languages.
• It positions AI as Technology for Humanity, aligning with the vision of Welfare for All and Happiness for All.
Role of AI in the Conservation of Culture and Language:
• Digitization and Discovery of Manuscripts: AI enables the high-speed scanning and cataloging of ancient scholarly works that were previously vulnerable to decay.
E.g. The Gyan Bharatam Mission has already documented over 44 lakh manuscripts, using AI for metadata extraction and intelligent cataloging.
• Multilingual and Voice-Based Access: AI removes literacy and language barriers by providing real-time speech-to-text and translation services for diverse dialects.
E.g. At Kashi Tamil Sangamam 2.0, PM Hindi speech was translated in real-time into Tamil using the BHASHINI platform for the attendees.
• Preservation of Tribal and Endangered Languages: AI helps revitalize languages that lack a script or are primarily oral by transcribing community narratives and folklore.
E.g. The Adi Vaani platform provides real-time translation and transcription for languages like Santali, Bhili, and Gondi, bringing them into the digital fold.
• Integration of Artisans into Digital Value Chains: AI-inclusive platforms allow craftspeople to showcase their products and stories globally without language being a constraint.
E.g. AI-based discovery tools currently help Indian artisans present GI-tagged products in multilingual catalogs, reducing their dependence on intermediaries.
• Scaling Cultural Events and Pilgrimages: AI enhances the visitor experience at large-scale heritage events by providing automated, multilingual assistance.
E.g. The Kumbh Sah’AI’yak chatbot provided navigation and event information in 11 languages to pilgrims during Maha Kumbh 2025.
Key Initiatives Taken:
• BHASHINI (National Language Translation Mission): A digital public infrastructure providing AI-led language services like translation and speech-to-text across 22 Scheduled languages.
• Anuvadini: An AI-based platform by AICTE that translates technical and academic textbooks into regional languages to ensure knowledge, not just communication.
• Gyan Bharatam Mission: A national mission (2024–31) with an outlay of ₹482.85 crore focused on the digitisation and dissemination of India’s manuscript heritage.
• Adi Vaani: A dedicated AI platform for tribal languages that supports subtitling for health advisories and government messages in native tribal tongues.
• Technology Development for Indian Languages (TDIL): A foundational program focused on standardizing OCR, machine translation, and handwriting recognition for Indian scripts.
Key Challenges Associated:
• The Literacy and Digital Barrier: Many cultural practitioners remain excluded from high-tech tools due to limited digital familiarity or formal literacy.
E.g. Despite BHASHINI’s reach, artisans in remote clusters still struggle to navigate complex digital storefronts without assisted voice-interfaces.
• Scattered and Undocumented Intellectual Wealth: A significant portion of India’s manuscript tradition is in private collections or mutts, making centralized AI-processing difficult.
E.g. Gyan Bharatam faces the challenge of surveying manuscripts held in private mutts and temples where custodians are wary of centralizing ownership.
• Low-Resource Language Datasets: Endangered tribal languages lack the massive text-corpora required to train accurate Large Language Models (LLMs).
E.g. Languages like Kui and Garo are still in the beta development phase under Adi Vaani because of a lack of existing digital documentation.
• Authenticity and Provenance Issues: As cultural content is digitized, ensuring the trust and authenticity of GI-tagged heritage products remains an uphill task.
E.g. The misuse of traditional designs by mass-producers necessitates AI-supported tagging systems that are not yet fully standardized across all craft clusters.
• Offline Access and Infrastructure Gaps: AI models often require high compute power or stable internet, which is absent in many heritage sites and tribal belts.
E.g. NITI Aayog recently highlighted that AI systems must be redesigned to work offline to benefit the last-mile cultural workers in areas with poor connectivity.
Way Ahead:
• Building Language as Digital Public Infrastructure: Expanding the Language Layer so that startups and government bodies can build inclusive apps without starting from scratch.
• Verifiable Digital Credentials: Issuing reliable, AI-tracked skill certificates for artisans to improve their formal employability and market trust.
• Encouraging Local Innovation: Establishing Digital Work Hubs at the district level to support local language content creation and digital skilling.
• Multi-Stakeholder Collaboration: Linking academia (IITs/IIITs), industry, and community organizations to ensure AI solutions remain inclusive-by-design.
• Democratization of Technology: Shifting toward Open-Source AI models to ensure that cultural preservation tools remain a public good rather than proprietary tech.
Conclusion:
India is positioning AI not just as a tool for efficiency, but as a guardian of its civilizational identity through initiatives like BHASHINI and Gyan Bharatam. By aligning technological progress with social empowerment and linguistic inclusion, the nation ensures that its rich heritage becomes a living asset for the digital age.
Q. “India’s AI ambition will be constrained less by talent and more by compute, energy and institutional capacity”. Discuss. (15 M)