Artificial Intelligence for Culture and Languages

Syllabus: GS1/ Culture, GS2/ Governance

Context

• India is institutionalising AI to bridge the digital, linguistic, and literacy divide through a suite of national platforms that transform cultural heritage into accessible digital assets.

AI Driven National Interventions

• BHASHINI: Launched in 2022 under the National Language Translation Mission, BHASHINI was developed to respond to India’s wide linguistic diversity in the digital space.
  • The initiative focuses on building language and voice capabilities directly into digital systems.
• Technology Development for Indian Languages (TDIL): It focuses on the development and standardisation of core language technologies, including:
  • machine translation
  • optical character recognition (OCR) for Indian scripts
  • speech-to-text and text-to-speech systems
  • handwriting recognition and transliteration tools.
• Anuvadini (AICTE): Anuvadini is an AI-based multilingual translation platform developed by the All India Council for Technical Education (AICTE) to enable large-scale translation of academic, technical and knowledge content into Indian languages.
• Gyan Bharatam Mission: It is a national mission for the survey, documentation, digitisation and dissemination of India’s manuscript heritage and traditional knowledge systems, including creation of a National Digital Repository.
• Gyan-Setu: It was launched as a national challenge to source AI-led solutions for manuscript preservation, decipherment, restoration and access.
• Adi Vaani: It is an AI-based platform for the preservation, promotion and revitalisation of tribal languages, which are central to India’s cultural and oral heritage.

Role of AI in Conservation of Culture and Languages

• Cultural Preservation: AI enables high-speed scanning, OCR, metadata extraction, and intelligent cataloguing of fragile manuscripts.
  • Example: Gyan Bharatam Mission has documented over 44 lakh manuscripts, many of which were previously inaccessible or at risk of decay.
• Democratisation of Knowledge: AI-based speech-to-text and real-time translation reduce literacy and language barriers.
  • Example: During Kashi Tamil Sangamam 2.0, speeches were translated in real time using BHASHINI, enabling seamless cross-linguistic participation.
• Social Inclusion: It integrates tribal and marginalised communities into digital ecosystems.
  • Example: The Adi Vaani platform supports languages such as Santali, Bhili, and Gondi, bringing them into the digital ecosystem.
• Economic Empowerment: AI strengthens livelihoods in the cultural and creative sectors by improving visibility, market access, productivity, and authenticity verification for artisans and cultural workers.
• Digital Public Infrastructure: AI converts India’s linguistic diversity into scalable technological strength by embedding multilingual and voice-based capabilities into large-scale public systems.
  • Example: BHASHINI powered the Kumbh Sah’AI’yak multilingual chatbot, which provided navigation, event updates, and lost-and-found assistance in 11 languages.

What are the challenges?

• Digital Divide: Limited internet connectivity, low digital literacy, and lack of access to smart devices in rural and tribal regions restrict effective utilisation of AI platforms.
• Algorithmic Bias: AI systems trained on uneven or dominant-language datasets may distort meanings, overlook cultural nuances, or marginalise smaller linguistic communities.
• Contextual Limitations: Machine translation and speech recognition tools struggle with dialects, accents, idiomatic expressions, and culturally embedded knowledge systems.
• Traditional Knowledge Protection: Digitisation of manuscripts and oral traditions raises concerns about ownership, consent, and potential misuse of indigenous knowledge.

Way Ahead

• Community-Centric Approach: AI models must be developed with active participation of local communities, linguists, and tribal groups to ensure cultural sensitivity, contextual accuracy, and ownership over knowledge systems.
• Offline and Low-Bandwidth AI Solutions: AI systems should be designed to function effectively in remote and low-connectivity regions to bridge the digital divide.
• Public–Private–Academic Collaboration: Partnerships among government institutions, startups, research bodies, and civil society organisations can accelerate innovation and scalable implementation.
• Global Leadership in Multilingual AI: India can position itself as a global leader in inclusive multilingual AI by exporting scalable language technologies to other linguistically diverse nations.

Source: PIB