The Design Intelligence Lab’s Ashok Goel was featured in Georgia Tech School of Interactive Computing’s June Newsletter: ‘Friends’ Inspires AI Tool.
While discussing the advantages of AI personalization in education with EducationWeek, Goel makes the point that AI feedback “might be right for, say, a neurotypical child and maybe not right for a neuroatypical child”.
Last week, four DILab team papers were accepted for presentation to the 20th International Conference on Intelligent Tutoring Systems in Greece in June 2024!
AUTHORS: Sandeep Kakar, Pratyusha Maiti, Alekhya Nandula, Gina Nguyen, Karan Taneja, Aiden Zhao, Vrinda Nandan and Ashok Goel
AUTHORS: Sandeep Kakar, Rhea B, Ida Camacho, Christopher Griswold, Alex Houk, Chris Leung, Mustafa Tekman, Patrick Westervelt, Qiaosi Wang and Ashok Goel.
AUTHORS: John Kos, Dinesh Ayyappan and Ashok Goel
AUTHORS: Rhea Basappa, Mustafa Tekman, Hong Lu, Benjamin Faught, Sandeep Kakar and Ashok Goel
Congratulations to all the authors!
On March 19, 2024, AAAI published the Special Issue if AI Magazine in National AI Institutes. The publication includes an Introduction by DILab’s Ashok Goel and AI-ALOE’s Chaohua Ou which describes the scheme for the organization of the 20 articles in the issue.
Within the Special Issue is also “AI-ALOE: AI for reskilling, upskilling, and workforce development” by Ashok Goel, Chris Dede, and Chaohua Ou. The article highlights how AI-ALOE is developing models and techniques to make AI assistants usable, learnable, teachable, and scalable.
Congratulations to Vrinda Nandan, Spencer Rugaber, and Ashok Goel for the publication of their chapter, “Explanation as Question Answering based on User Guides”, in Explainable Agency in Artificial Intelligence: Research and Practice.
This book focuses on a subtopic of explainable AI (XAI) called explainable agency (EA), which involves producing records of decisions made during an agent’s reasoning, summarizing its behavior in human-accessible terms, and providing answers to questions about specific choices and the reasons for them. We distinguish explainable agency from interpretable machine learning (IML), another branch of XAI that focuses on providing insight (typically, for an ML expert) concerning a learned model and its decisions. In contrast, explainable agency typically involves a broader set of AI-enabled techniques, systems, and stakeholders (e.g., end users), where the explanations provided by EA agents are best evaluated in the context of human subject studies.
The chapters of this book explore the concept of endowing intelligent agents with explainable agency, which is crucial for agents to be trusted by humans in critical domains such as finance, self-driving vehicles, and military operations. This book presents the work of researchers from a variety of perspectives and describes challenges, recent research results, lessons learned from applications, and recommendations for future research directions in EA. The historical perspectives of explainable agency and the importance of interactivity in explainable systems are also discussed. Ultimately, this book aims to contribute to the successful partnership between humans and AI systems.
DILab’s Karan Taneja and Ashok Goel published Machine Teaching for Building Modular AI Agents based on Zero-shot Learners in January, 2024.
In the publication, they “propose an approach to enhance the robustness and performance of modular AI agents that utilize LLMs as zero-shot learners”.
Presentation poster for Self-Explanation in AI Agents
Researchers: Sungeun An, Scott Bunin, Stephen Buckley, Willventchy Celestin, Andrew Hornback, Vrinda Nandan, Spencer Rugaber, Ashok Goel
Congratulations to Qiaosi “Chelsea” Wang for acceptance of her proposal to the ACM CHI conference for a CHI 2024 Workshop on Theory of Mind on Human-AI Interaction!
The CHI conference on Human Factors in Computing Systems is the premier international conference of Human-Computer Interaction. The conference embraces the theme of Surfing the World – reflecting the focus on pushing forth the wave of cutting-edge technology and riding the tide of new developments in human-computer interaction. The conference serves as a platform for researchers, practitioners, and industry leaders to share their latest work and ideas and to foster collaboration and innovation in the field
On November 13, 2023 the U.S. National Science Foundation (NSF) published the latest episode of the NSF’s Discovery Files Podcast.
Joining the podcast are Aarti Singh from the AI Institute for Societal Decision Making; Amy McGovern from the AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography; Ashok Goel from the National AI Institute for Adult Learning and Online Education; Vikram Adve from the Artificial Intelligence for Future Agricultural Resilience, Management, and Sustainability Institute; and Michael Littman, division director for Information and Intelligent Systems in NSF’s Computer and Information Science and Engineering Directorate, to hear how these institutes will revolutionize the frontiers of AI and how society will benefit from these innovations
