探讨生成式AI中包容性参与对边缘群体的真实影响
Provocation: Who benefits from "inclusion" in Generative AI?
- 基于研究者集体经验提出反事实案例
- 指出参与机制未明示边缘群体的收益与风险
- 呼吁开发者直面系统性变革的必要性
生成式AI要求更准确和具代表性的系统，推动了参与式评估结构的发展。尽管这些结构对于反映非主导群体的价值、知识和物质文化至关重要，但我们在本文中指出，当前主流的AI开发与评估中的社区参与机制，未能充分揭示边缘群体成员可能面临的实际收益与伤害。若开发者不主动审视这些影响，我们可能无法意识到所需进行的深层系统性变革。为此，我们基于自身研究经历构建了一个推测性案例，旨在列举实现边缘群体真实收益所必须克服的障碍，并减少潜在危害。
原文摘要 · Abstract (English)
The demands for accurate and representative generative AI systems means there is an increased demand on participatory evaluation structures. While these participatory structures are paramount to to ensure non-dominant values, knowledge and material culture are also reflected in AI models and the media they generate, we argue that dominant structures of community participation in AI development and evaluation are not explicit enough about the benefits and harms that members of socially marginalized groups may experience as a result of their participation. Without explicit interrogation of these benefits by AI developers, as a community we may remain blind to the immensity of systemic change that is needed as well. To support this provocation, we present a speculative case study, developed from our own collective experiences as AI researchers. We use this speculative context to itemize the barriers that need to be overcome in order for the proposed benefits to marginalized communities to be realized, and harms mitigated.
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