Ministry of Electronics & IT
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India Commits to Safe and Trusted AI with New EoI initiative


Empowering Society Through AI: IndiaAI mission selects 8 projects to enhance Safe and Trusted AI development across diverse themes

Top Indian institutions to enable Safe and Trusted AI through bias mitigation, Machine Unlearning & privacy enhancing strategies

Posted On: 16 OCT 2024 8:14PM by PIB Delhi

The IndiaAI Mission has selected eight Responsible AI Projects against the Expression of Interest (EoI) floated under the Safe and Trusted AI Pillar of the IndiaAI Mission. Recognizing the need for adequate guardrails to advance the responsible development, deployment, and adoption of AI, the selected Responsible AI projects include the development of indigenous tools and frameworks, and establishing guidelines for ethical, transparent, and trustworthy AI technologies.

Promoting responsible AI through 8 strategic projects

As AI continues to permeate various sectors of society, India is committed to invest in agile mechanisms for developing indigenous governance tools, frameworks, and guidelines that are based on Indian datasets and reflect its unique challenges, opportunities, and datasets. To support this vision, IndiaAI has issued an Expression of Interest (EoI) to promote responsible AI projects across a range of critical themes. These include Machine Unlearning, Synthetic Data Generation, AI Bias Mitigation, Ethical AI Frameworks, Privacy-Enhancing Tools, Explainable AI, AI Governance Testing, and Algorithm Auditing Tools.

More than 2000 proposals were received from reputed Academic Institutions, Start-ups, Research Organisations & Civil Society. A multi-stakeholder committee was created to provide technical expertise for the evaluation of the proposals, resulting in the selection of 8 projects across various themes.

The details of the Selected Projects are given below:-
 

 

S.No.

 

Name of the Theme

 

Name of the Selected Project

 

 

Title of the Project

  1.  

Machine Unlearning

Indian Institute of Technology, Jodhpur

Machine Unlearning in Generative Foundation Models

  1.  

Synthetic Data Generation

Indian Institute of Technology, Roorkee

Design and Development of Method for Generating Synthetic Data for Mitigating Bias in Datasets; and Framework for Mitigating Bias in Machine Learning Pipeline for Responsible AI

  1.  

AI Bias Mitigation Strategy

National Institute of Technology Raipur

Development of Responsible Artificial Intelligence for Bias Mitigation in Health Care Systems

  1.  

Explainable AI Framework

Defence Institute of Advanced Technology (DIAT), Pune in partnership with Mindgraph Technology Pvt. Ltd.

Enabling Explainable and Privacy Preserving AI for Security

  1.  

Privacy Enhancing Strategy

Indian Institute of Technology, Delhi in partnership with Indian Institute of Technology, Dharwad, Indraprastha Institute of Information Technology, Delhi and Telecommunication Engineering Center (TEC)

Robust Privacy-Preserving Machine Learning Models

  1.  

AI Ethical Certification Framework

Indraprastha Institute of Information Technology, Delhi in partnership with Telecommunication Engineering Center (TEC)

Nishpaksh: Tools for assessing fairness of AI model

  1.  

AI Algorithm Auditing Tool

Civic Data Labs

ParakhAI - An open-source framework and toolkit for Participatory Algorithmic Auditing

  1.  

AI Governance Testing Framework

Amrita Vishwa Vidyapeetham in partnership with Telecommunication Engineering Center (TEC)

Track-LLM, Transparency, Risk Assessment, Context & Knowledge for Large Language Models



Advancing India's leadership in AI through the IndiaAI Mission

This initiative aligns with the Government of India’s vision of leveraging AI for inclusive growth. IndiaAI, an IBD (Independent Business Division) under the Digital India Corporation (DIC) of the Ministry of Electronics and IT (MeitY), is the implementation agency of the IndiaAI Mission, which aims to democratize AI's benefits across all strata of society, bolster India’s global leadership in AI, foster technological self-reliance, and ensure ethical and responsible use of AI.

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Dharmendra Tewari/Kshitij Singha


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