Brief Context
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.
Source Content
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