
doi: 10.4337/9781803926728.00026 , 10.5281/zenodo.15826712 , 10.48550/arxiv.2308.13591 , 10.5281/zenodo.15826713
arXiv: 2308.13591
handle: 1887/4177515
doi: 10.4337/9781803926728.00026 , 10.5281/zenodo.15826712 , 10.48550/arxiv.2308.13591 , 10.5281/zenodo.15826713
arXiv: 2308.13591
handle: 1887/4177515
This book chapter delves into the pressing need to "queer" the ethics of AI to challenge and re-evaluate the normative suppositions and values that underlie AI systems. The chapter emphasizes the ethical concerns surrounding the potential for AI to perpetuate discrimination, including binarism, and amplify existing inequalities due to the lack of representative datasets and the affordances and constraints depending on technology readiness. The chapter argues that a critical examination of the neoliberal conception of equality that often underpins non-discrimination law is necessary and cannot stress more the need to create alternative interdisciplinary approaches that consider the complex and intersecting factors that shape individuals' experiences of discrimination. By exploring such approaches centering on intersectionality and vulnerability-informed design, the chapter contends that designers and developers can create more ethical AI systems that are inclusive, equitable, and responsive to the needs and experiences of all individuals and communities, particularly those who are most vulnerable to discrimination and harm.
FOS: Computer and information sciences, Computer Science - Computers and Society, K.2, Computers and Society (cs.CY), Computer Science - Human-Computer Interaction, K.2; I.2.m, I.2.m, Human-Computer Interaction (cs.HC)
FOS: Computer and information sciences, Computer Science - Computers and Society, K.2, Computers and Society (cs.CY), Computer Science - Human-Computer Interaction, K.2; I.2.m, I.2.m, Human-Computer Interaction (cs.HC)
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 7 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
