Summary
UH researchers are using artificial intelligence and machine learning to optimize a variety of applications across fields such as inorganic chemistry, materials science, community health, computational medicine and law. Such research focuses on using data to make predictions about natural disasters and other geophysical problems, population health, environmental impact, disease diagnoses and progression, and compound formation.

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HPE DSI Affiliate Meng Li explores how social class impacts AI use at work.

August 27, 2025 / Donna Keeya


Meng Li at computer

With more people using artificial intelligence tools like ChatGPT, C. T. Bauer College of Business researchers have found that middle-class workers may be the most receptive to incorporating the tool on the job. 

The rise of large language models (AI models including ChatGPT) have led people to ask what they mean for society, and what benefits they offer, explained Professor and Endowed C. T. Bauer Chair of AI Meng Li. These questions are part of the thought process behind Li’s research, which looks at workers’ social class backgrounds and how that impacts their adoption of LLMs in place of supervisor assistance. 

“We already understand that AI tools, ChatGPT, self-driving cars they are not going away,” Li said. “They are going to be there regardless of if we like it or not, so just answering this question will be critical for our society.”

In their quest to see the relationship between social classes and adopting AI instead of getting help from supervisors, researchers did large scale surveys and behavioral experiments. This included early career professionals from various social class backgrounds.   

The paper, co-authored by Li, Bauer Ph.D. student Yao Yao and Boston College Assistant Professor Lai Wei, defines “early career” as workers with less than two to three years of experience. This group was selected because of their typical reliance on their supervisors, and because their relatively standardized current social class allows for more context to examine their social class background. 

The research insights found that middle-class workers are more willing to use LLMs instead of asking their supervisor for help compared to their lower-class and upper-class peers. 

“For the upper class, they are comfortable to talk to humans,” Li said. “They have the resources. For the lower class, they don't have the literacy or the knowledge of large language models. So, it turns out the middle class is more willing to adopt AI tools such as large language models.”

The results could be seen as an inverted U-shaped pattern and bring a light to the middle-class workers. The middle-class group stood out because they were most inclined to use the LLMs in this way. 

“They have the knowledge,” Li said. “They know how to use it. They know how the large language model can help them, or they are comfortable with technology. I think this unique advantage makes their adoption easier.” 

Li says it’s important to understand that LLMs impact people differently. 

“Trying to help the people who are not adopting AI, or have the need to, like the lower class, but don't know how to use it,” Li said. “I think finding a way to help them will be important.” 

Moving forward, how these dynamics will impact workplace inequality is a question the paper says is still up for future research. 

The next step to continue advancing research on how AI impacts the workplace is an exploration of how these dynamics may impact workplace inequality, Li said. 


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Research Topics

Claudia Neuhauser

Claudia Neuhauser headshot
Director
HPE Data Science Institute
Faculty Bio

Claudia Neuhauser is the Vice President/Vice Chancellor for Research at the University of Houston. Prior to coming to the University of Houston, Claudia served as Associate Vice President for Research and Director of Research Computing at the University of Minnesota. In her capacity as Director of Research Computing she directed the University of Minnesota Informatics Institute (UMII), the Minnesota Supercomputing Institute (MSI), and U Spatial.

Research Areas

    Research Topics
    ML / AI
    Scientific Computing

Winston Liaw

Winston Liaw
Clinical Associate Professor
College of Medicine
Faculty Bio

Dr. Liaw is interested in the intersection of artificial intelligence, geography, and electronic health records. His research uses geocoded health records to develop prediction tools, with the ultimate goal of implementing these tools to improve the delivery of care.

Research Areas

    Research Topics
    ML / AI

Vedhus Hoskere

Vedhus Hoskere
Assistant Professor
Civil and Environmental Engineering
Faculty Bio

Vedhus Hoskere's current research interests are highly interdisciplinary, at the intersection of civil engineering, computer science and robotics. His doctoral work at the University of Illinois with Billie F. Spencer Jr. focused on developing artificial intelligence, machine learning and computer vision solutions for rapid and automated civil infrastructure inspection and monitoring. For his research toward automated post-earthquake building inspections, Hoskere received the Liu Huixian Earthquake Engineering Scholarship in 2018. 

Research Areas

    Research Topics
    Image Analysis
    ML / AI
    Natural Language Processing
    Robotics
    Scientific Computing
    Visualization

Tracy Hester

Tracy Hester
Lecturer
UH Law Center
Teaching Unit 2 Building, Room 142
Faculty Bio

I work on legal issues affected by artificial intelligence or, alternatively, the expansion of digital tools that can alter that way that lawyers function. For example, I’ve worked with the Red Cross on the legal liabilities posed by their reliance on machine learning platforms to predict disaster sites, and the ability of environmental regulators to use machine learning systems to predict ozone formation in the Houston region.

Research Areas

    Research Topics
    ML / AI

Nouhad Rizk

Nouhad Rizk
Professor
Computer Science
Faculty Bio

Dr. Rizk's teaching philosophy reflects her interests in creating an atmosphere that fosters learning and facilitates student discovery by supporting and challenging students both inside and outside of the classroom. Dr. Rizk favors peer learning, which is a powerful method for sharing knowledge, ideas, and experience, and it influences student-learning outcomes in a positive, measurable way. Dr. Rizk's other approach of efficiently implementing her teaching philosophy is "gamifying" the classroom which strongly increases student engagement and motivation. Dr. Rizk's interests include: data science, educational data mining, machine learning and information retrieval.

Research Areas

    Research Topics
    ML / AI

Nikolas Guggenberger

Nikolas Guggenberger
Assistant Professor
UH Law Center
Faculty Bio

Nikolas Guggenberger is Assistant Professor of Law at the University of Houston Law Center. He also holds an appointment at the Cullen College of Engineering’s Electrical and Computer Engineering Department. Guggenberger’s work focuses on antitrust, law & technology, privacy, and regulation. He has frequently advised government entities and served as expert witness on technology policy, financial markets regulation, and media law.

Research Areas

    Research Topics
    ML / AI

Mini Das

Mini Das
Professor
Physics, Chemistry, and Computer Science
Science and Research 1, Room 419B
Faculty Bio

I am an Applied Physicist and an Engineer who works at the interface of multiple disciplines to solve outstanding challenges in medical and biological imaging. We combine tools and techniques from optical physics, applied mathematics, cutting edge instrumentation, analytical methods and extensive computational platforms. The broader impact and applications of my group’s work are in multiple areas besides biological and medical imaging, such as in defense/security, materials imaging, quantitation and characterization in chemical, materials and geophysical imaging problems. We are also very motivated to explore fundamental aspects related to light-matter interactions via quantum detection and other cutting edge tools being developed in my lab. Some of my key interests are : Experimental/Optical design and computational imaging for advanced and innovative imaging methods, computational simulation platforms for “virtual clinical trials”, psychophysics/image science aspects, vision science as well as global health/cancer screening to help bring cancer screening and imaging to underserved population and third world countries.

Research Areas

    Research Topics
    Image Analysis
    ML / AI
    Scientific Computing

Meng Li

Meng Li
Associate Professor
Faculty Bio

I am an Associate Professor, and Bauer Fellow at C.T. Bauer College of Business, University of Houston. My recent research interests focus on platform and Al. My research has appeared in Management Science, Manufacturing and Service Operations Management, Production and Operations Management, and Strategic Management Journal, among others. I am a Senior Editor for Production and Operations Management, and an Associate Editor for Decision Sciences Journal.

Research Areas

    Research Topics
    ML / AI

News

HPE DSI Affiliate Meng Li explores how social class impacts AI use at work.
August 27, 2025