56 citations · 84 across the 8 of their papers we have counts for
8 papers
Making Power Explicable in AI: Analyzing, Understanding, and Redirecting Power to Operationalize Ethics in AI Technical Practice
Weina Jin, Elise Li Zheng, Ghassan Hamarneh
The operationalization of ethics in the technical practices of artificial intelligence (AI) is facing significant challenges. To address the problem of ineffective implementation o…
Ethical Medical Image Synthesis
Weina Jin, Ashish Sinha, Kumar Abhishek +1
The task of ethical Medical Image Synthesis (MISyn) is to ensure that the MISyn techniques are researched and developed ethically throughout their entire lifecycle, which is essent…
AI for Just Work: Constructing Diverse Imaginations of AI beyond "Replacing Humans"
Weina Jin, Nicholas Vincent, Ghassan Hamarneh
"why" we develop AI. Lacking critical reflections on the general visions and purposes of AI may make the community vulnerable to manipulation. In this position paper, we explore th…
Why is plausibility surprisingly problematic as an XAI criterion?
Weina Jin, Xiaoxiao Li, Ghassan Hamarneh
Explainable artificial intelligence (XAI) is motivated by the problem of making AI predictions understandable, transparent, and responsible, as AI becomes increasingly impactful in…
Invisible Users: Uncovering End-Users' Requirements for Explainable AI via Explanation Forms and Goals
Weina Jin, Jianyu Fan, Diane Gromala +2
Non-technical end-users are silent and invisible users of the state-of-the-art explainable artificial intelligence (XAI) technologies. Their demands and requirements for AI explain…
Transcending XAI Algorithm Boundaries through End-User-Inspired Design
Weina Jin, Jianyu Fan, Diane Gromala +3
The boundaries of existing explainable artificial intelligence (XAI) algorithms are confined to problems grounded in technical users' demand for explainability. This research parad…
EUCA: the End-User-Centered Explainable AI Framework
Weina Jin, Jianyu Fan, Diane Gromala +2
The ability to explain decisions to end-users is a necessity to deploy AI as critical decision support. Yet making AI explainable to non-technical end-users is a relatively ignored…
Artificial Intelligence in Glioma Imaging: Challenges and Advances
Weina Jin, Mostafa Fatehi, Kumar Abhishek +3
Primary brain tumors including gliomas continue to pose significant management challenges to clinicians. While the presentation, the pathology, and the clinical course of these les…