"先来找我们":以社区组织为中心的人工智能社会公益伙伴关系

Hongjin Lin, Naveena Karusala, Chinasa T. Okolo, Catherine D'Ignazio, Krzysztof Z. Gajos
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摘要

人工智能促进社会公益(AI4SG)作为探索人工智能技术解决社会问题潜力的研究和实践机构,正在不断发展壮大。这一领域强调与社区组织(如非营利组织和政府机构)的跨学科合作。然而,在对人工智能的新进展及其潜在影响感到兴奋的同时,人们对这些社区组织的需求、期望和愿望--以及它们是否得到满足--并不十分了解。了解这些因素对于确保人工智能团队和社区组织所做的大量努力能够真正实现他们所追求的积极社会影响非常重要。借鉴数据女性主义框架,我们通过 16 个半结构化访谈,探讨了社区组织成员对其与人工智能团队合作关系的看法。尽管社区组织成员提供了大量的智力贡献和劳动,但他们的目标经常被其他利益相关者(包括人工智能团队)搁置一边。尽管许多社区组织成员期待着切实的项目部署,但在所研究的 14 个项目中,只有两个项目进入了部署阶段。不过,社区组织成员仍然相信项目的潜力,认为被削弱的目标仍有价值。为了提高未来合作的效率,我们的参与者分享了他们对成功的渴望,呼吁从项目的早期阶段就开始共同领导。我们建议将数据解放作为推动人工智能4SG发展的基本原则,认为社区组织的共同领导对于促进人工智能更有效、更可持续和更合乎道德的发展至关重要。
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"Come to us first": Centering Community Organizations in Artificial Intelligence for Social Good Partnerships
Artificial Intelligence for Social Good (AI4SG) has emerged as a growing body of research and practice exploring the potential of AI technologies to tackle social issues. This area emphasizes interdisciplinary partnerships with community organizations, such as non-profits and government agencies. However, amidst excitement about new advances in AI and their potential impact, the needs, expectations, and aspirations of these community organizations--and whether they are being met--are not well understood. Understanding these factors is important to ensure that the considerable efforts by AI teams and community organizations can actually achieve the positive social impact they strive for. Drawing on the Data Feminism framework, we explored the perspectives of community organization members on their partnerships with AI teams through 16 semi-structured interviews. Our study highlights the pervasive influence of funding agendas and the optimism surrounding AI's potential. Despite the significant intellectual contributions and labor provided by community organization members, their goals were frequently sidelined in favor of other stakeholders, including AI teams. While many community organization members expected tangible project deployment, only two out of 14 projects we studied reached the deployment stage. However, community organization members sustained their belief in the potential of the projects, still seeing diminished goals as valuable. To enhance the efficacy of future collaborations, our participants shared their aspirations for success, calling for co-leadership starting from the early stages of projects. We propose data co-liberation as a grounding principle for approaching AI4SG moving forward, positing that community organizations' co-leadership is essential for fostering more effective, sustainable, and ethical development of AI.
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