Events

Reid Simmons (Carnegie Mellon University) is a special track co-chair of AAAI-23, which will feature a special track on Safe and Robust Artificial Intelligence (SRAI). This special track, new for AAAI-23, focuses on the theory and practice of safety and robustness in AI-based systems. AI systems are increasingly being deployed throughout society within different domains such as data science, robotics and autonomous systems, medicine, economy, and safety-critical systems. Although the widespread use of AI systems in today’s world is growing, they have fundamental limitations and practical shortcomings, which can result in catastrophic failures. Specifically, many of the AI algorithms that are being implemented nowadays fail to guarantee safety and success and lack robustness in the face of uncertainties.

To ensure that AI systems are reliable, they need to be robust to disturbance, failure, and novel circumstances. Furthermore, this technology needs to offer assurance that it will reasonably avoid unsafe and irrecoverable situations. In order to push the boundaries of AI systems’ reliability, this special track at AAAI-23 will focus on cutting-edge research on both the theory and practice of developing safe and robust AI systems. Specifically, the goal of this special track is to promote research that studies 1) the safety and robustness of AI systems, 2) AI algorithms that are able to analyze and guarantee their own safety and robustness, and 3) AI algorithms that can analyze the safety and robustness of other systems. For acceptance into this track, we would expect papers to have fundamental contributions to safe and robust AI, as well as applicability to the complexity and uncertainty inherent in real-world applications.

In short, the special track covers topics related to safety and robustness of AI-based systems and to using AI-based technologies to enhance the safety and robustness of themselves and other critical systems,

Diyi Yang (Stanford University), Pradeep Dasigi (Allen Institute for AI), Sherry Tongshuang Wu (CMU), Tuhin Chakrabarty (Columbia University), Yuval Pinter (Ben-Gurion University), Mike Shou Zheng (National University of Singapore).
The driving forces of progress in NLP are the people behind the work. We learn from their work. But to generate such good work, what are the principles and strategies they used? What are the roadblocks, challenges, mistakes, and lessons learned? These are quite valuable to the newbies across different career stages. In fact, we always reach out to the senior people around us for advice and reflect on their stories when we start a new career chapter - (1) fresh phd students reach out to early career researchers including senior phds or recent graduate, (2) early career researchers reach out to mid/late career professors, (3) company newbies reach out to industrial leaders. But often, only a few people would be approachable around us. This workshop aims at making the sharing of successful researchers’ stories and lessons learned to be accessible to everyone in our community. Such sharing would be very inspiring and helpful for those who might be struggling with making a choice or feeling lost right now.

About Workshop

The driving forces of progress in NLP are the people behind the work. We learn from their work. But to generate such good work, what are the principles and strategies they used? What are the roadblocks, challenges, mistakes, and lessons learned? These are quite valuable to the newbies across different career stages. In fact, we always reach out to the senior people around us for advice and reflect on their stories when we start a new career chapter - (1) fresh phd students reach out to early career researchers including senior phds or recent graduate, (2) early career researchers reach out to mid/late career professors, (3) company newbies reach out to industrial leaders. But often, only a few people would be approachable around us. This workshop aims at making the sharing of successful researchers’ stories and lessons learned to be accessible to everyone in our community. Such sharing would be very inspiring and helpful for those who might be struggling with making a choice or feeling lost right now. Our workshop will line up with sessions dedicated to individual career stage groups; each session will consist of 3-5 speeches and a panel QA & discussion to interact with the audience.

Wei Xu (GT), Alan Ritter (GT), Afshin Rahimi (University of Queensland), Tim Baldwin (MBZUAI and University of Melbourne)

Workshop Abstract: The WNUT workshop focuses on Natural Language Processing applied to noisy user-generated text, such as that found in social media, online reviews, crowdsourced data, web forums, clinical records and language learner essays. The workshop has accepted 25 papers (short and long).

AI-CARING invited to speak at IPaT Tuesday Think Tank.

Thomas Ploetz, associate professor at the School of Interactive Computing, is representing Georgia Tech as the general chair for this year’s Ubicomp. He has authored or co-authored eight papers that will be presented this year and is one of six IC faculty members who have had papers accepted. The others are professor emeritus Gregory Abowd, assistant professor Sonia Chernova, interim school chair Betsy DiSalvo, associate professor Josiah Hester, and distinguished professor Irfan Essa. The papers are also co-authored by 12 Georgia Tech PhD or graduate students. Tech faculty and students contributed to 13 papers altogether.

Ploetz said any papers presented at Ubicomp were accepted because they were published in a journal called The Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT) during the previous year. Many researchers in the field refer to Ubicomp and IMWUT synonymously, he said.

“It is fantastic to have such a strong presence of GT researchers — first and foremost our students — at our annual flagship conference,” Ploetz said. “It underlines the strength of Ubicomp/IMWUT research at our university.”