• 1 row = 1 team (lead author is labeled)
  • Left column = GT-led teams
  • Right column = Teams with GT
  • Bars sorted by percent of GT contributors on each team


Misinformation Detection Models are Vulnerable to ChatGPT and Other LLMs

Existing machine learning (ML) models used to detect online misinformation are less effective when matched against content created by ChatGPT or other large language models (LLMs), according to new research from Georgia Tech.

Current ML models designed for and trained on human-written content have significant performance discrepancies in detecting paired human-generated misinformation and misinformation generated by artificial intelligence (AI) systems, said Jiawei Zhou, a Ph.D. student in Georgia Tech’s School of Interactive Computing.

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Jiawei Zhou and Munmun De Choudhury (Photo by Kevin Beasley)

Researchers Examine the Boundaries of Using AI ‘Sensing’ to Understand Office Workers’ Performance and Wellbeing

Researchers at Georgia Tech and Northeastern University conducted a study with information workers to learn about their perspectives on being monitored and their information being collected with passive-sensing enabled artificial intelligence (PSAI), where computing devices can unobtrusively detect and collect user behaviors.

“One of the underlying subtexts of the research is that there are these asymmetries at work because the employee doesn’t have as much power as the employer. And if these technologies keep progressing as they are, this gap is going to widen because the employer will just keep getting more and more worker information,” said Vedant Das Swain, lead researcher and a Ph.D. candidate in computer science at Georgia Tech.

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Photo by Kevin Beasley

Researchers Facilitate Discussions on Women’s Health in Taboo Culture

In many countries around the world, cultural and religious taboos create environments that silence women and gender minorities and restrict access to health information.

But a team of graduate students within the School of Interactive Computing have explored how technology can help circumvent these barriers so that women can engage in freer communication on stigmatized health issues.

Hannah Tam, Karthik Bhat, and Priyanka Mohindra conducted research to study how safe spaces could be curated to support 35 women of Indian origin in discussing subjects that are otherwise considered taboo.

Neha Kumar (pictured), an associate professor who teaches jointly with the School of Interactive Computing and the Sam Nunn School of International Affairs, served as advisor to the students. Kumar is the director of the Tandem Lab, which works to explore cultural taboos and investigate their impact on health and well-being among women and gender minorities internationally.

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Andrea Parker is Georgia Tech’s leading paper author at CHI 2023 with five papers, including a honorable mention paper and a best paper. (Photo by Northeastern University)

Vanessa Oguamanam has researched the correlation of digital tools and how often Black women in perinatal stages use them to improve their mental health.

Oguamanam has spent most of her doctoral career researching technology designed to benefit the health of Black women.

Researchers Find Perinatal Black Women are Underserved by Digital Mental Health Tools

Pregnant and postpartum Black women experience disproportionately higher rates of mental health challenges, and new research indicates that a one-size-fits-all approach to digital mental health tools and platforms is falling short for these women.

According to the American Counseling Association, Black women are at higher risk for perinatal and postnatal mood and anxiety disorders (PMADs) such as depression, anxiety, obsessive compulsive disorder, and posttraumatic stress disorder. The risk for PMADs is estimated to be double that of the general population.

The problem has worsened since the Covid-19 pandemic, says Vanessa Oguamanam, a Ph.D. student in the School of Interactive Computing under the advisement of Associate Professor Andrea Parker.

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What Do We Mean When We Talk about Trust in Social Media? A Systematic Review
Yixuan Zhang, Joseph D Gaggiano, Nutchanon Yongsatianchot, Nurul M Suhaimi, Miso Kim, Yifan Sun, Jacqueline Griffin, Andrea G Parker

Synthetic Lies: Understanding AI-Generated Misinformation and Evaluating Algorithmic and Human Solutions
Jiawei Zhou, Yixuan Zhang, Qianni Luo, Andrea G Parker, Munmun De Choudhury

Functional Destruction: Utilizing sustainable materials’ physical transiency for electronics applications
Tingyu Cheng, Taylor Tabb, Jung Wook Park, Eric M Gallo, Aditi Maheshwari, Gregory D. Abowd, HyunJoo Oh, Andreea Danielescu

Coaching Tool Guides Rejected Loan Applicants Toward Better Outcomes

A new web-based tool is set to provide people with unprecedented visibility into the machine learning models that are used to make high-stakes decisions impacting their daily lives.

Developed at Georgia Tech in work led by Machine Learning Ph.D. candidate Zijie Jay Wang, GAM Coach is the first interactive tool of its kind to give people with rejected loan applications the power to personalize recourse options that are realistically actionable to help ensure a better outcome in the future.

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CHI Countries Ranked

by number of people and contributions from each country

See you in Germany!

Web Development: Joshua Preston
Writers: Nathan Deen, Joshua Preston, Albert Snedeker
Interactive Graphics: Joshua Preston