44 citations · 105 across the 25 of their papers we have counts for
5 papers · 1 filter
Human learning is an understudied but promising lever for boosting human--AI synergy
Julian Berger, Jason W. Burton, Ralph Hertwig +9
Humans collaborating with artificial intelligence (AI) hold the promise of achieving superior outcomes compared to either acting alone (i.e., human--AI synergy). However, the condi…
If You Had to Pitch Your Ideal Software -- Evaluating Large Language Models to Support User Scenario Writing for User Experience Experts and Laypersons
Patrick Stadler, Christopher Lazik, Christopher Katins +1
The process of requirements analysis requires an understanding of the end users of a system. Thus, expert stakeholders, such as User Experience (UX) designers, usually create vario…
Prompt-Hacking: The New p-Hacking?
Thomas Kosch, Sebastian Feger
As Large Language Models (LLMs) become increasingly embedded in empirical research workflows, their use as analytical tools for quantitative or qualitative data raises pressing con…
Evaluating Eye Tracking and Electroencephalography as Indicator for Selective Exposure During Online News Reading
Thomas Krämer, Francesco Chiossi, Thomas Kosch
Selective exposure to online news consumption reinforces filter bubbles, restricting access to diverse viewpoints. Interactive systems can counteract this bias by suggesting altern…
The Impostor is Among Us: Can Large Language Models Capture the Complexity of Human Personas?
Christopher Lazik, Christopher Katins, Charlotte Kauter +4
Large Language Models (LLMs) created new opportunities for generating personas, expected to streamline and accelerate the human-centered design process. Yet, AI-generated personas…