Affiliation:
1. Department of Computer Science and Engineering University of Bologna Bologna Italy
Abstract
AbstractDelving into the intricate complexities of naming and categorizing the visual evocation of abstract concepts, this paper brings to light the limitations of relying on binary thinking to tackle these inherently intricate “wicked problems.” As computer vision applications rapidly expand, the pressing challenge of accurately labeling these abstract concepts in visual media comes into focus, necessitating a close examination of the interplay between visual data, nuanced cultural meanings, and artificial intelligence (AI). This work discusses the role these concepts play in automatic visual indexing, as well as the ways in which they expose how binary frameworks curtail technical performance and perpetuate power dynamics. To address this, the paper draws upon insights from recent cognitive neuroscience research and advocates for a more comprehensive, queer, and situated understanding of these concepts. This approach highlights the significance of humanistic and ethical perspectives in shaping the trajectory of AI development.