The handbook was unveiled by MeitY Secretary S. Krishnan at a roundtable in Bengaluru, with support from the iSPIRT Foundation. The framework seeks to address barriers to sharing large datasets for artificial intelligence (AI) development by allowing institutions to collaborate without surrendering control over their data.
It combines contractual permissions, controlled computing environments and privacy safeguards to enable data use for specific purposes. It also provides for tracking the origin, permissions and use of data throughout the AI training process to improve transparency and accountability.
Krishnan said India’s AI ambitions must be supported by the responsible and secure use of data. The framework could expand access to large datasets for AI training while protecting privacy, commercial confidentiality and institutional control, he said. Principal Scientific Adviser to the government Ajay Kumar Sood said the framework allows AI models to be taken to datasets rather than transferring the data to the models.
This approach could facilitate secure collaboration among multiple institutions and across national borders, accelerate scientific research and help address problems that individual institutions cannot solve alone, he said.
Sood described the framework as India’s contribution to global scientific cooperation and efforts to develop an inclusive and responsible AI ecosystem. Sharad Sharma, co-founder of iSPIRT Foundation, said the launch marked a significant development in India’s data economy and compared its potential importance with the announcement of the Unified Payments Interface in February 2016.
Anjani Rathor, group head of digital banking and customer experience at HDFC Bank, said trusted data sharing could create opportunities for AI applications in banking. The bank’s experience with DEPA Inference had demonstrated the potential of secure data collaboration, providing a foundation for exploring DEPA Training, she said.
The roundtable brought together representatives from government, industry, technology, academia, research and the media to discuss trusted data sharing and its role in advancing AI innovation and public welfare.
