6 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…
What Can We Learn from Inter-Annotator Variability in Skin Lesion Segmentation?
Kumar Abhishek, Jeremy Kawahara, Ghassan Hamarneh
Medical image segmentation exhibits intra- and inter-annotator variability due to ambiguous object boundaries, annotator preferences, expertise, and tools, among other factors. Les…
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…
FiGO: Fine-Grained Object Counting without Annotations
Adriano D'Alessandro, Ali Mahdavi-Amiri, Ghassan Hamarneh
Class-agnostic counting (CAC) methods reduce annotation costs by letting users define what to count at test-time through text or visual exemplars. However, current open-vocabulary…
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…
Disentangled PET Lesion Segmentation
Tanya Gatsak, Kumar Abhishek, Hanene Ben Yedder +2
PET imaging is an invaluable tool in clinical settings as it captures the functional activity of both healthy anatomy and cancerous lesions. Developing automatic lesion segmentatio…