4 papers
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…
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…