6 papers
Disrupting Cognitive Passivity: Rethinking AI-Assisted Data Literacy through Cognitive Alignment
Yongsu Ahn, Nam Wook Kim, Benjamin Bach
AI chatbots are increasingly stepping into roles as collaborators or teachers in analyzing, visualizing, and reasoning through data and domain problem. Yet, AI's default assistant…
From Answer Givers to Design Mentors: Guiding LLMs with the Cognitive Apprenticeship Model
Yongsu Ahn, Lejun R Liao, Benjamin Bach +1
Design feedback helps practitioners improve their artifacts while also fostering reflection and design reasoning. Large Language Models (LLMs) such as ChatGPT can support design wo…
Understanding Why ChatGPT Outperforms Humans in Visualization Design Advice
Yongsu Ahn, Nam Wook Kim
This paper investigates why recent generative AI models outperform humans in data visualization knowledge tasks. Through systematic comparative analysis of responses to visualizati…
How Good is ChatGPT in Giving Advice on Your Visualization Design?
Nam Wook Kim, Yongsu Ahn, Grace Myers +1
Data visualization creators often lack formal training, resulting in a knowledge gap in design practice. Large language models such as ChatGPT, with their vast internet-scale train…
Human-centered explanation does not fit all: The interplay of sociotechnical, cognitive, and individual factors in the effect AI explanations in algorithmic decision-making
Yongsu Ahn, Yu-Ru Lin, Malihe Alikhani +1
Recent XAI studies have investigated what constitutes a \textit{good} explanation in AI-assisted decision-making. Despite the widely accepted human-friendly properties of explanati…
Gender Bias in LLM-generated Interview Responses
Haein Kong, Yongsu Ahn, Sangyub Lee +1
LLMs have emerged as a promising tool for assisting individuals in diverse text-generation tasks, including job-related texts. However, LLM-generated answers have been increasingly…