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AI for Society (AI4S) group at the AI Institute is focused on enabling people to make rational decisions despite real-world complexities of poor data, changing goals, and limited resources by augmenting their cognitive limitations with technology. Lead by Prof. Biplav Srivastava, the group works in neuro-symbolic methods, trusted AI, and applications of data-driven methods to society. We focus on innovating and applying AI techniques for hard problems facing the society with an inclusive, value-driven, focus. |
AI4Society @ AAAI 2023
ElectionBot-SC Demo @TechInLaw '24
AI for Credible Elections Workshop @AAAI '23
Team Lunch - Spring '25
Holi Celebration @ 2024
All AIISC faculty families @ 2022
All AIISC faculty families @ 2022
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2025
May
Dr. Likitha was formally recognized with PhD hooding on May 8 (see 1:21:37 to 1:21:58). Dissertation defended on topic, Building Trustable Methods for Group Recommendations: Advancing Fairness and Robustness Across Domains, on (Friday, Feb 14). A new resource award received for NAIRR Pilot Demonstration Project: A Compact Foundation Model for Planning-Like (PL) Tasks for Next Generation Trusted Applications (NAIRR250014), to support computing for NSF NAIRR project [Resources, Foundation Models, Planning, Demonstration]. April
Biplav to give a talk, 'From MIA to Becoming Essential: Using Human-Inspired Computing to Help AI Earn Human Trust for Societal Problems' at North Carolina State University, Raleigh, NC on 25 April 2025. Biplav to give a talk, 'Beyond Trustworthy Machine Learning: Using Human-Inspired Computing to Help AI Earn Trust for Societal Problems' at CSIRO - Commonwealth Scientific and Industrial Research Organisation (virtually) on 16 April 2025. March
A new resource award received for Privacy-Preserving Traffic Safety Analysis: A Module on Trusted AI With Real Data from Civic Partners (NAIRR250023), to support class teaching [Resources, Data Analysis, Traffic]. Our paper, 'Do Voters Get the Information They Want? Understanding Authentic Voter FAQs in the US and How to Improve for Informed Electoral Participation' is accepted at TrustNLP workshop in NAACL 2025. Our paper, 'Revisiting LLMs in Planning from Literature Review: a Semi-Automated Analysis Approach and Evolving Categories Representing Shifting Perspectives' is accepted at ICAPS 2025 (AR=22.8%). February
PhD dissertation - Likitha successfully defended on the topic Building Trustable Methods for Group Recommendations: Advancing Fairness and Robustness Across Domains, (Friday, Feb 14). A prestigious recognition received - (VAIBHAV - announcement) for work in summer with IIT-BHU on using AI and sensors for recommending and monitoring Yoga asanas; was 1 among 17 selected from 216 competing globally (2025-2028). Our point of view (POV), on DeepSeek R1, the new AI Large Language Model (LLM) from DeepSeek (Feb 2, 2025). |
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