IIT Madras' CeRAI Partners with Ericsson for Research in Responsible AI

The Centre for Responsible AI (CeRAI) at the Indian Institute of Technology (IIT) Madras has formed a strategic partnership with Ericsson to embark on joint research in the field of Responsible AI. The collaboration is aimed to explore the responsible use and development of artificial intelligence particularly in the context of future networks.

In terms of marking this occasion, a Symposium on Responsible AI for Networks of the Future was organized where distinguished leaders from Ericsson Research and IIT Madras participated. The symposium served as a platform for discussions on the latest advancements in Responsible AI.

During the event an official agreement was signed at the IIT Madras campus on 25 September 2023, Ericsson agreed to partner with CeRAI as a 'Platinum Consortium Member' for five years. Under this agreement, Ericsson Research will actively engage in and support all research initiatives undertaken by CeRAI.

The Centre for Responsible AI is an interdisciplinary research center with a vision to become a premier research center for both fundamental and applied research in Responsible AI aimed at immediate implementation in the Indian ecosystem.

AI research holds immense significance for Ericsson particularly in the context of forthcoming 6G networks which are expected to be autonomously driven by AI algorithms.

"Research on AI will produce the tools for operating tomorrow's businesses. IIT Madras strongly believes in impactful translational work in collaboration with the industry, and we are very happy to collaborate with Ericsson to do cutting-edge R&D in this subject," said Chief Guest, Prof. Manu Santhanam, Dean (Industrial Consultancy and Sponsered Research, IIT Madras while addressing the symposium.

"6G and future networks aim to seamlessly blend the physical and digital worlds, enabling immersive AR/VR experiences. While AI-controlled sensors connect humans and machines, responsible AI practices are essential to ensure trust, fairness, and privacy compliance. Our focus is on developing cutting-edge methods to enhance trust and explainability in AI algorithms for the public good. Our partnership with CERAI at IIT Madras is aligned with the Indian Government's vision for the Bharat 6G program," said Dr.Magnus Frodigh, Global Head of Ericsson Research.

During the symposium, a panel discussion titled "Responsible AI for Networks of the Future" was also organized to commemorate the partnership. The event also showcased ongoing research projects at CeRAI related to responsible AI.

"6G and future networks aim to seamlessly blend the physical and digital worlds, enabling immersive AR/VR experiences. While AI-controlled sensors connect humans and machines, responsible AI practices are essential to ensure trust, fairness, and privacy compliance. Our focus is on developing cutting-edge methods to enhance trust and explainability in AI algorithms for the public good. Our partnership with CERAI at IIT Madras is aligned with Indian Government's vision for the Bharat 6G program," said Prof. B.Ravindran, Faculty Head, CeRAI, IIT Madras, and Robert Bosch Centre for Data Science and AI (RBCDSAI), IIT Madras.

Some of the key projects highlighted during the Symposium include

Large Language Models (LLMs) in Healthcare: This project focuses on detecting biases shown by the models, scoring methods for real-world applicability, and reducing biases in LLMs. Custom-scoring methods are being designed based on the Risk Management Framework (RMF) put forth by the National Institute of Standards and Technology (NIST.

Participatory AI: It addresses the black box nature of AI at various stages, including pre-development, design, development and training, deployment, post-deployment, and audit. Inspired by domains such as town planning and forest rights, the project studies governance mechanisms that enable stakeholders to provide constructive inputs for better customization of AI, and improve accuracy and reliability.

Generative AI models based on attention mechanisms: Generative AI models based on attention mechanisms have recently gained significant interest for their exceptional performance in various tasks such as machine translation, image summarization, text generation, and healthcare, but they are complex and difficult for users to interpret. The project on interpretability of attention-based models explores the conditions under which these models are accurate but fail to be interpretable, algorithms that can improve the interpretability of such models, and understanding which patterns in the data these models tend to learn.

Multi-Agent Reinforcement Learning for trade-off and conflict resolution in intent-based networks: Intent-based management is gaining importance in telecom networks due to strict performance demands. Existing approaches often use traditional methods, treating each closed loop independently and lacking scalability. This project studies a Multi-agent Reinforcement Learning (MARL) method to handle complex coordination and encourage loops to cooperate automatically when intents conflict.