Georgia Tech’s Georgia Manufacturing Extension Partnership (GaMEP) helped transform The Chai Box—a family‑run business born in Marietta—into a nationally recognized brand by guiding them through rigorous food safety audits for retailers like Costco, streamlining production, and boosting their revenue by 20 %. This collaboration not only enabled larger scale success and a feature in Forbes, but vividly illustrated how applied research can turn cultural legacy into commercial opportunities.
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In the morning, before you even open your eyes, your wearable device has already checked your vitals. By the time you brush your teeth, it has scanned your sleep patterns, flagged a slight irregularity, and adjusted your health plan. As you take your first sip of coffee, it’s already predicted your risks for the week ahead.

Georgia Tech researchers warn that this version of AI healthcare imagines a patient who is "affluent, able-bodied, tech-savvy, and always available." Those who don’t fit that mold, they argue, risk becoming invisible in the healthcare system.

The Ideal Future

In their study, published in the Proceedings of the ACM Conference on Human Factors in Computing Systems, the researchers analyzed 21 AI-driven health tools, ranging from fertility apps and wearable devices to diagnostic platforms and chatbots. They used sociological theory to understand the vision of the future these tools promote — and the patients they leave out.

“These systems envision care that is seamless, automatic, and always on,” said Catherine Wieczorek, a Ph.D. student in human-centered computing in the School of Interactive Computing and lead author of the study. “But they also flatten the messy realities of illness, disability, and socioeconomic complexity.”

Four Futures, One Narrow Lens

During their analysis, the researchers discovered four recurring narratives in AI-powered healthcare:

1. Care that never sleeps. Devices track your heart rate, glucose levels, and fertility signals — all in real time. You are always being watched, because that’s framed as “care.”
2. Efficiency as empathy. AI is faster, more objective, and more accurate. Unlike humans, it doesn’t get tired or biased. This pitch downplays the value of human judgment and connection.
3. Prevention as perfection. A world where illness is avoided through early detection if you have the right sensors, the right app, and the right lifestyle.
4. The optimized body. You’re not just healthy, you’re high-performing. The tech isn’t just treating you; it’s upgrading you.

“It’s like healthcare is becoming a productivity tool,” Wieczorek said. “You’re not just a patient anymore. You’re a project.”

Not Just a Tool, But a Teammate

This study also points to a critical transformation in which AI is no longer just a diagnostic tool; it’s a decision-maker. Described by the researchers as “both an agent and a gatekeeper,” AI now plays an active role in how care is delivered.

In some cases, AI systems are even named and personified, like Chloe, an IVF decision-support tool. “Chloe equips clinicians with the power of AI to work better and faster,” its promotional materials state. By framing AI this way — as a collaborator rather than just software — these systems subtly redefine who, or what, gets to be treated.

“When you give AI names, personalities, or decision-making roles, you’re doing more than programming. You’re shifting accountability and agency. That has consequences,” said Shaowen Bardzell, chair of Georgia Tech’s School of Interactive Computing and co-author of the study.

“It blurs the boundaries,” Wieczorek noted. “When AI takes on these roles, it’s reshaping how decisions are made and who holds authority in care.”

Calculated Care

Many AI tools promise early detection, hyper-efficiency, and optimized outcomes. But the study found that these systems risk sidelining patients with chronic illness, disabilities, or complex medical needs — the very people who rely most on healthcare.

“These technologies are selling worldviews,” Wieczorek explained. “They’re quietly defining who healthcare is for, and who it isn’t.”

By prioritizing predictive algorithms and automation, AI can strip away the context and humanity that real-world care requires. 

“Algorithms don’t see nuance. It’s difficult for a model to understand how a patient might be juggling multiple diagnoses or understand what it means to manage illness, while also navigating other important concerns like financial insecurity or caregiving. They are predetermined inputs and outputs,” Wieczorek said. “While these systems claim to streamline care, they are also encoding assumptions about who matters and how care should work. And when those assumptions go unchallenged, the most vulnerable patients are often the ones left out.” 

AI for ALL

The researchers argue that future AI systems must be developed in collaboration with those who don’t fit in the vision of a “perfect patient.” 

“Innovation without ethics risks reinforcing existing inequalities. It’s about better tech and better outcomes for real people,” Bardzell said. “We’re not anti-innovation. But technological progress isn’t just about what we can do. It’s about what we should do — and for whom.”

Wieczorek and Bardzell aren’t trying to stop AI from entering healthcare. They’re asking AI developers to understand who they’re really serving.

 

Funding:
This work was supported by the National Science Foundation (Grant #2418059). 

 

A new version of Georgia Tech’s virtual teaching assistant, Jill Watson, has demonstrated that artificial intelligence can significantly improve the online classroom experience. Developed by the Design Intelligence Laboratory (DILab) and the U.S. National Science Foundation AI Institute for Adult Learning and Online Education (AI-ALOE), the latest version of Jill Watson integrates OpenAI’s ChatGPT and is outperforming OpenAI’s own assistant in real-world educational settings.

Jill Watson not only answers student questions with high accuracy. It also improves teaching presence and correlates with better academic performance. Researchers believe this is the first documented instance of a chatbot enhancing teaching presence in online learning for adult students.

How Jill Watson Shaped Intelligent Teaching Assistants

First introduced in 2016 using IBM’s Watson platform, Jill Watson was the first AI-powered teaching assistant deployed in real classes. It began by responding to student questions on discussion forums like Piazza using course syllabi and a curated knowledge base of past Q&As. Widely covered by major media outlets including The Chronicle of Higher Education, The Wall Street Journal, and The New York Times, the original Jill pioneered new territory in AI-supported learning.

Subsequent iterations addressed early biases in the training data and transitioned to more flexible platforms like Google’s BERT in 2019, allowing Jill to work across learning management systems such as EdStem and Canvas. With the rise of generative AI, the latest version now uses ChatGPT to engage in extended, context-rich dialogue with students using information drawn directly from courseware, textbooks, video transcripts, and more.

Future of Personalized, AI-Powered Learning

Designed around the Community of Inquiry (CoI) framework, Jill Watson aims to enhance “teaching presence,” one of three key factors in effective online learning, alongside cognitive and social presence. Teaching presence includes both the design of course materials and facilitation of instruction. Jill supports this by providing accurate, personalized answers while reinforcing the structure and goals of the course.

The system architecture includes a preprocessed knowledge base, a MongoDB-powered memory for storing conversation history, and a pipeline that classifies questions, retrieves contextually relevant content, and moderates responses. Jill is built to avoid generating harmful content and only responds when sufficient verified course material is available.

Field-Tested in Georgia and Beyond

The first AI-powered teaching assistant was developed for Georgia Tech’s Online Master of Science in Computer Science (OMSCS) program. By fall 2023, Jill Watson was deployed in Georgia Tech’s OMSCS artificial intelligence course, serving more than 600 students, as well as in an English course at Wiregrass Georgia Technical College, part of the Technical College System of Georgia (TCSG).

A controlled A/B experiment in the OMSCS course allowed researchers to compare outcomes between students with and without access to Jill Watson, even though all students could use ChatGPT. The findings are striking:

• Jill Watson’s accuracy on synthetic test sets ranged from 75% to 97%, depending on the content source. It consistently outperformed OpenAI’s Assistant, which scored around 30%.
• Students with access to Jill Watson showed stronger perceptions of teaching presence, particularly in course design and organization, as well as higher social presence.
• Academic performance also improved slightly: students with Jill saw more A grades (66% vs. 62%) and fewer C grades (3% vs. 7%).

A Smarter, Safer Chatbot

While Jill Watson uses ChatGPT for natural language generation, it restricts outputs to validated course material and verifies each response using textual entailment. According to a study by Taneja et al. (2024), Jill not only delivers more accurate answers than OpenAI’s Assistant but also avoids producing confusing or harmful content at significantly lower rates.

Compared to OpenAI’s Assistant, Jill Watson (ChatGPT) not only achieves higher accuracy but also produces confusing or harmful content at significantly lower rates. Jill Watson answers correctly 78.7% of the time, with only 2.7% of its errors categorized as harmful and 54.0% as confusing. In contrast, OpenAI’s Assistant demonstrates a much lower accuracy of 30.7%, with harmful failures occurring 14.4% of the time and confusing failures rising to 69.2%. Additionally, Jill Watson has a lower retrieval failure rate of 43.2%, compared to 68.3% for the OpenAI Assistant.

What’s Next for Jill

The team plans to expand testing across introductory computing courses at Georgia Tech and technical colleges. They also aim to explore Jill Watson’s potential to improve cognitive presence, particularly critical thinking and concept application. Although quantitative results for cognitive presence are still inconclusive, anecdotal feedback from students has been positive. One OMSCS student wrote:

“The Jill Watson upgrade is a leap forward. With persistent prompting I managed to coax it from explicit knowledge to tacit knowledge. Kudos to the team!”

The researchers also expect Jill to reduce instructional workload by handling routine questions and enabling more focus on complex student needs.

Additionally, AI-ALOE is collaborating with the publishing company John Wiley & Sons, Inc., to develop a Jill Watson virtual teaching assistant for one of their courses, with the instructor and university chosen by Wiley. If successful, this initiative could potentially scale to hundreds or even thousands of classes across the country and around the world, transforming the way students interact with course content and receive support.

A Georgia Tech-Led Collaboration

The Jill Watson project is supported by Georgia Tech, the US National Science Foundation’s AI-ALOE Institute (Grants #2112523 and #2247790), and the Bill & Melinda Gates Foundation.

Core team members are Saptrishi Basu, Jihou Chen, Jake Finnegan, Isaac Lo, JunSoo Park, Ahamad Shapiro and Karan Taneja, under the direction of professor Ashok Goel and Sandeep Kakar. The team works under Beyond Question LLC, an AI-based educational technology startup.

From Bigfoot vlogs to algorithmically created personas, hyperrealistic AI content is redefining the boundaries of digital creators. These influencers are entirely virtual personas created using generative AI tools that simulate human features, voices, and behaviors. They post lifestyle content, interact with followers, and even secure brand endorsements — all without existing in the physical world. As these technologies grow more widely available and their results more believable, specialists caution that we are moving into a new age where the line separating fiction from reality is becoming increasingly blurred.

The Rise of Synthetic Creativity

Experts at Georgia Tech say the surge in AI hyperrealism — content that mimics human emotion, speech, and appearance with uncanny precision — is both a technological marvel and a societal challenge.

“AI does not have emotions as we understand them in humans, but it knows how to mimic emotional speech,” said Mark Riedl, professor in the School of Interactive Computing. “Once we understand that AI is mimicking us, it is easy to understand how they can create believable outputs that sound authentic.”

Riedl points to the democratization of video creation as a major shift. “AI video generation tools and the ability to bypass traditional content channels and post directly to social media have opened up the floodgates,” he said.

Recent examples include synthetic influencers such as Nobody Sausage, a digitally animated character that has attracted over 30 million followers across multiple social media platforms through short-form dance videos and brand collaborations. On platforms like Character.AI, users engage with millions of virtual personas designed to simulate conversation and personality traits. These AI-generated figures are reshaping how audiences interact with content, marketing, and identity across Instagram, TikTok, and other social media channels.

Mental Health and the Reality Gap

Munmun De Choudhury, professor in the School of Interactive Computing, warns that hyperreal AI content can distort users’ perception of reality, especially among vulnerable populations.

“This distortion can fuel anxiety, exacerbate body image and self-comparison issues, and contribute to a broader erosion of epistemic trust — our basic belief in what others present as true,” she said.

Her research shows that social media already blurs the line between authentic self-expression and performative identity. Hyperreal AI content — from deepfakes to emotionally resonant synthetic personas — further complicates users’ ability to evaluate what is real or trustworthy. Adolescents and those facing mental health challenges may be especially susceptible.

“Individuals experiencing stress or social isolation may be more prone to believe deepfakes,” De Choudhury explained. “Such content often reinforces existing beliefs or fills gaps in social connection.”

The AI content challenges our understanding of authenticity, trust, and digital identity. It also raises questions about consent, misinformation, and the psychological effects of interacting with synthetic personas. Gen Z users, she notes, often judge AI content by emotional resonance rather than factual accuracy, while older users may struggle to detect synthetic cues altogether. 

Platforms, Persuasion, and Misinformation

Riedl emphasizes that AI storytelling tools can be used to sway public opinion through “narrative transportation,” a psychological phenomenon in which audiences become immersed in a story and are less likely to question its truth.

“Storytelling is a means of persuasive communication,” he said. “Our brains are attuned to stories in a way that can bypass critical thinking.”

Recent incidents highlight the changing landscape. Deepfakes of public figures such as Taylor Swift and Tom Hanks have surged in 2025, with over 179 incidents in the first four months of the year alone — surpassing all of 2024. These deepfakes range from humorous impersonations to fraudulent and explicit content, raising ethical and legal concerns about identity misuse and misinformation. Riedl notes that video misinformation has historically been harder to produce but is now easier and more likely to be tailored to niche audiences.

Social media companies face mounting pressure to take action. De Choudhury argues that labeling AI-generated content is necessary but insufficient. “Platforms must invest in user-centered design, digital literacy interventions, and transparency about how algorithms surface such content,” she said.

The stakes are especially high in mental health communities, where authenticity and lived experience are critical. “Users often feel overwhelmed or deceived when they encounter synthetic content without clear cues of its artificial origin,” she added.

Governance in a Globalized AI Era

Milton Mueller, professor in the Jimmy and Rosalynn Carter School of Public Policy, argues that regulation may be ineffective or even counterproductive in a decentralized digital ecosystem.

“Generative AI is part of a globalized and distributed digital ecosystem,” Mueller said. “So, which regulatory authority are you talking about, and how does it gain the leverage needed to control the outputs?”

While the EU’s AI Act mandates labeling and imposes steep fines, U.S. efforts remain fragmented. The Federal Communications Commission has made AI-generated voices in robocalls illegal, with entities facing fines, and several states are pushing for watermarking and criminal penalties for political deepfakes. But experts warn that First Amendment protections complicate enforcement.

Mueller cautions that governments are already using AI as a geopolitical tool, which could undermine global cooperation and lead to strategic escalation. “Instead of freely trading data and establishing common rules, governments are asserting digital sovereignty,” he said.

He advocates for addressing AI-generated misinformation through decentralized governance, public debate, and media literacy, rather than centralized regulation or automated controls, emphasizing that content moderation should be guided by open processes and existing legal remedies applied after the fact.

As AI-generated content becomes more sophisticated and widespread, researchers say the challenge lies not only in technological safeguards but in how society adapts. Experts at Georgia Tech emphasize the need for transparency, interdisciplinary collaboration, and public engagement. The future of hyperreal media, they say, will depend on how well platforms, policymakers, and users navigate its risks and possibilities.

Siobhan Rodriguez

Institute Communications

The Institute for Matter and Systems (IMS) has selected six interdisciplinary research projects to receive funding including four new research initiatives and two new programs. This funding is part of a larger IMS effort to identify and support visionary leaders driving groundbreaking research and innovation.

IMS focuses on transformational technological and societal systems that arise where innovative materials, devices, and processes converge.

“Interdisciplinary research often struggles to find a home,” said Michael Filler, IMS deputy director. “IMS aims to fill that gap—through programs like the CPI, we provide a place where unconventional collaborations from across Georgia Tech and beyond can take root, grow, and ultimately redefine what’s possible.

The funded initiatives come from four colleges and 11 schools across the Institute, and from GTRI. These research projects were selected based on their innovative approaches, potential impact, and alignment with IMS’ mission to push the boundaries of science and technology. They will receive funding, access to state-of-the-art facilities, and other support from IMS to bring their projects to life.

IMS supports interdisciplinary research both in nationally recognized areas of need and those just emerging. It scaffolds research from the ground up, from seed funding for new initiatives to infrastructure support for research programs and embedded support for research centers. The four newly announced initiatives are funded at the lowest level of IMS’ three-tiered model.

The two new research programs were previous IMS research initiatives that have been elevated to the program level. The successful elevation to research program highlights the funding pipeline and its design to support novel interdisciplinary research. As initiatives, these researchers were given seed funding and support for workshops, visioning and team nucleation, they demonstrated dedication to their research and team building. As IMS research programs, these projects will have the opportunity to expand their operations including with support for team expansions, proposals, and some staff support. 

“The IMS funding pipeline is about giving researchers a ladder where none exists—support to take the first step with a new idea, and the structure to keep climbing as their work matures,” said Filler. “By providing that scaffold, we enable bold, interdisciplinary teams to turn early sparks of discovery into thriving research programs with real-world impact.”

The new research initiatives and programs:

Research Initiatives

Multifunctional Materials for Efficient Buildings | Akanksha Menon, George W. Woodruff School of Mechanical Engineering

Adaptive Biomacromolecular and Cellular Networks | Anant Paravastu, School of Chemical and Biomolecular Engineering; Vinayak Agarwal, School of Chemistry and Biochemistry; Andrew McShan, School of Chemistry and Biochemistry; and Itamar Kolvin, School of Physics

Precision Agriculture in Controlled Environments | Antonio Facchetti, School of Materials Science and Engineering; Yongsheng Cheng, School of Civil and Environmental Engineering; Anju Toor, School of Materials Science and Engineering

Electrochemical Manufacturing of Materials and Resource Recovery | Hailong Chen, George W. Woodruff School of Mechanical Engineering

Research Programs

Autonomous Research for Materials | Mark Losego, School of Materials Science and Engineering; Shreyas Kousik, George W. Woodruff School of Mechanical Engineering; Animesh Garg, School of Interactive Computing

Magnetometry and Spectrum-Based Quantum Sensing Platforms| Zhigang Jiang, School of Physics; Martin Mourigal, School of Physics; Yan Wang, George W. Woodruff School of Mechanical Engineering

 

Learn more about IMS’s research focuses and see a full list of its centers, programs, and initiatives.

Daniel Yue, assistant professor of IT Management at the Scheller College of Business, has been awarded the prestigious Best Dissertation Award by the Technology and Innovation Management Division of the Academy of Management. The recognition celebrates the most impactful doctoral research in the field of business and innovation.

Yue’s dissertation, developed during his Ph.D. at Harvard Business School, explores a paradox at the heart of the AI industry: why do firms openly share their innovations, like scientific knowledge, software, and models, despite the apparent lack of direct financial return? His work sheds light on the strategic and economic mechanisms that drive this openness, offering new frameworks for understanding how firms contribute to and benefit from shared technological progress.

“We typically think of firms as trying to capture value from their innovations,” Yue explained. “But in AI, we see companies freely publishing research and releasing open-source software. My dissertation investigates why this happens and what firms gain from it.”

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Georgia Tech researchers have designed the first benchmark that tests how well existing AI tools can interpret advice from YouTube financial influencers, also known as finfluencers.

Lead author Michael Galarnyk, Ph.D. Machine Learning ’28, joined lead authors Veer Kejriwal, B.S. Computer Science ’25, and Agam Shah, Ph.D. Machine Learning ’26, along with co-authors Yash Bhardwaj, École Polytechnique, M.S. Trustworthy and Responsible AI ‘27; Nicholas Meyer, B.S. Electrical and Computer Engineering ’22 and Quantitative and Computational Finance ’24; Anand Krishnan, Stanford University, B.S. Computer Science ‘27; and, Sudheer Chava, Alton M. Costley Chair and professor of Finance at Georgia Tech.

Aptly named VideoConviction, the multimodal benchmark included hundreds of video clips. Experts labelled each clip with the influencer’s recommendation (buy, sell, or hold) and how strongly the influencer seemed to believe in their advice, based on tone, delivery, and facial expressions. The goal? To see how accurately AI can pick up on both the message and the conviction behind it.

“Our work shows that financial reasoning remains a challenge for even the most advanced models,” said Michael Galarnyk, lead author. “Multimodal inputs bring some improvement, but performance often breaks down on harder tasks that require distinguishing between casual discussion and meaningful analysis. Understanding where these models fail is a first step toward building systems that can reason more reliably in high stakes domains.”

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Georgia Tech and Shepherd Center recently awarded four seed grants totaling nearly $200,000 to researchers focusing on projects that will advance discoveries in neurorehabilitation, including acquired brain injury, spinal cord injury, multiple sclerosis, chronic pain, and other neurological conditions. 

The Georgia Tech-Shepherd Center Seed Grant Program is part of an ongoing partnership between the two institutions that started in 2023 with the goal of advancing rehabilitative patient care and research.

“The seed grant program is intended to stimulate new interdisciplinary research collaborations by providing seed funding to obtain preliminary data or prototypes necessary for the submission of an external grant or industry opportunities,” says Deborah Backus, vice president of Research and Innovation at Shepherd Center. “As two leading research institutions, we know the potential for advancing rehabilitation therapies is even greater when we work together. We look forward to the solutions, treatments, and therapies that emerge from these initial seed grants.” 

Experts from both institutions evaluated and scored seed grant applications based on the research’s innovation, approach, and potential for training opportunities, as well as its anticipated impact, prospects for commercial translation, and strategy for securing continued funding. This year, each awardee team received close to $50,000.

“We are very excited to launch this new seed grant program, which will spur ideas and propel research forward,” said Michelle LaPlaca, professor in the Coulter Department of Biomedical Engineering and the Georgia Tech lead of the Collaborative. “The complementary expertise of Georgia Tech and Shepherd Center researchers, combined with the motivation to find solutions for individuals with neurological injury and disability, is a winning formula for innovation.”

"Offering new hope for neurorehabilitation patients requires bringing together interdisciplinary researchers to explore new and creative ideas,” adds Chris Rozell, Julian T. Hightower Chaired professor in the School of Electrical and Computer Engineering and the inaugural executive director of the Institute of Neuroscience, Neurotechnology, and Society (INNS) at Georgia Tech. “I'm excited to see the talent at these world class institutions coming together to develop new solutions for these complex problems."

This year’s seed grants were awarded to the following projects:

• Proof of Concept Development of the Recovery Cushion – Stephen Sprigle, professor, School of Industrial Design and School of Mechanical Engineering, Georgia Tech; Jennifer Cowhig, research physical therapist, Shepherd Center.
• Paving a Smooth Path from Hospital to Home: A Feasibility Study of an Integrated Smart Transitional Home Lab to Support Stroke Rehabilitation Patients’ Transition to Home – John Morris, senior clinical research scientist, Shepherd Center; Hui Cai, professor in the School of Architecture, executive director of the SimTigrate Design Center, Georgia Tech.
• A Comparative Analysis of Lower-Limb Exoskeleton Technology for Non-Ambulatory Individuals with Spinal Cord Injury – Maegan Tucker, assistant professor, School of Electrical and Computer Engineering and School of Mechanical Engineering, Georgia Tech; Nicholas Evans (AP 2023), clinical research scientist, Shepherd Center.
• Improving Accessibility and Precision in Neurorehabilitation at the Point of Care with AI-Driven Remote Therapeutic Monitoring Solutions – Brad Willingham, clinical research scientist, director of Multiple Sclerosis Research, Shepherd Center; May Dongmei Wang, professor, Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech.