Dongwook Yoon

Concern for People Motivates Award-Winning Faculty Member Dongwook Yoon

A quick online search of “AI market values” estimates over $196 billion. Forecasts indicate its value at nearly $300 billion by 2026, and trillions by 2030. 

Related search topics include “how to demystify the role of machine learning to power positive outcomes” and “how AI can help you automate, innovate, and optimize processes for business.”

With so much money at stake, where does AI leave the human in this equation? 

Within the revenue-generating model, humans and their choices become data tracked and leveraged for business advancement.

As computer users, how can we recognize our relationship with AI? And can anyone help us avoid being used for data?


Computer Science Associate Professor Dongwook Yoon investigates deep ethical human computational studies, the social-technical side of computer systems. He studies the intersection of computer science, human-computer interaction, and ethics, focusing on how technology impacts society and individual behavior.

Hired by UBC in 2017 after finishing his PhD at Cornell, Yoon recently received an Early Career Research Award from the Canadian Human-Computer Communications Society (CHCCS) and co-authored two papers recognized with Best Paper Awards at ACM CHI 2024 (Conference on Human Factors in Computing Systems), the premier international conference of human-computer interaction.

Human interface solution

Yoon’s work focuses on critical perspectives on development and research of social-technical systems. He’s interested in the authentic human experience, human relationships, and respect for identities.

“Inclusivity, care for people, and love need to be the backbone of system-design philosophy,” says Yoon. “My objectives haven’t been on productivity or profit.”

While much AI-research is driven by financial gain, Yoon focuses his work on helping people.

“That’s the most distinguishing feature of my research,” he says.

He warns of the risks of system designs, such as social media, that pretend to serve people, yet serve capitalism instead. One of his goals is to help create more inclusive system designs that avoid further marginalizing people. 

Science behind the study

Yoon focuses on bridging the gap between technical systems and human interactions by creating inclusive solutions. He conducts research via three approaches, sometimes in sequence or sometimes separately. 

The first is by understanding people’s live experiences. He asks questions and listens to what people think.

“Hearing what challenges people face using technical systems is imperative to improving design, especially for individuals in marginalized groups,” says Yoon. 

For example, he speaks to women gig workers to understand their experiences. He’s found that women often face harassment in the delivery system when men do not.

“Women are often forced to brush off negative experiences such as harassment,” says Yoon. “If they complain, their hire-ability status will be negatively impacted.”

The second approach is to design, build and deploy technical systems to address bias and exclusivity. 

For example, in research involving human subjects, what if only cisgender men participate in a study? Yoon and his team have created a machine-learning based interactive gender data annotation system that informs researchers whether or not bias exists in experimental design. 

“After analyzing more than 1000 research papers, we made a solid case based on data that systematic gender bias exists,” says Yoon. 

Thirdly, Yoon uses a speculative design approach.

“This method allows us to tap into the future by using a forward-thinking approach to understand what may come next,” says Yoon. “We create scenarios and expose people to them. And we ask questions about their lived experiences related to the target technology.”

He notes a recent study on AI-chatbot tutors in which his research team sketches a scenario into cartoonish expression and asks people how they feel. 

Recognition for work

Debate Chatbots to Facilitate Critical Thinking on YouTube: Social Identity and Conversational Style Make A Difference by Thitaree (Mint) Tanprasert, Sidney Fels, Luanne Sinnamon, and Dongwook Yoon received a 2024 CHI Best Paper Award for investigating how exposure to different perspectives on online video platforms can help break through the “filter bubble” in which people only encounter viewpoints similar to their own. 

The researchers suggest that using advanced chatbots, powered by Large Language Models (LLMs), could encourage people to think critically about views they encounter. They tested how two aspects of these chatbots — their social identity and rhetorical styles — influence users’ critical thinking.

In this study involving 36 participants, they found that chatbots with an identity different from the user’s and using persuasive language were most effective at prompting critical thinking. 

This research lays the groundwork for designing chatbots that could help combat filter bubbles.

Yoon credits PhD candidate Mint Tanprasert with designing the experiment and finding results that encourage users to think critically.

Yoon quotes William Butler Yeats: “Education is not the filling of a pail, but the lighting of a fire.”

“We need to consider alternatives to getting better grades to motivate learning,” says Yoon. “We need to allow students to grow critical thinking skills, to carefully consider what is being said.”

Back to the future—further recognition

A second 2024 CHI Best Paper Award was garnered for Time-Turner: A Bichronous Learning Environment to Support Positive In-class Multitasking of Online Learners by Sahar Mavali, Dongwook Yoon, Luanne Sinnamon, and Sidney Fels.

This study focuses on how university students multitask during online classes, even though they know it can harm their learning. However, the researchers suggest that depending on the student’s goals, multitasking can sometimes be beneficial for productivity. 

In a small preliminary study involving 10 participants, they looked into why students multitask, what they think about it, and the difficulties they face. Based on this, they developed a new design to support multitasking during online classes.

Their design, called Time-Turner, blends synchronous (real-time) and asynchronous (delayed) learning. It allows students to review past content while still participating in the live class. 

When they tested this design with 20 students, they found that multitasking using Time-Turner led to better learning outcomes. Additionally, almost all users found Time-Turner helpful and wanted to use it in their online classes. This research suggests that supporting positive multitasking during online classes has significant potential for improving learning experiences.

“Our system enables students to reserve content while away and catch up to the live lecture in the future,” says Yoon. “This is important because life happens. We get an urgent message or we need to look up a definition, and we get distracted. Time-Turner allows a student to multi-task without getting behind.”

Yoon credits his outstanding collaborators including master’s student Sahar Mavali and Prof. Sidney Fels along with the VIDEX research group for developing the award-winning study.

“Any awards of my work are credit to the team I work with,” says Yoon. “The initiative of students, research trainees, collaborators — especially Prof. Sidney Fels and Luanne Sinnamon — and the support of our sponsors, is essential. I am deeply grateful for the team.”