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Measuring Diversity of Artificial Intelligence Conferences
arXiv - CS - Digital Libraries Pub Date : 2020-01-20 , DOI: arxiv-2001.07038
Ana Freire, Lorenzo Porcaro and Emilia G\'omez

The lack of diversity of the Artificial Intelligence (AI) field is nowadays a concern, and several initiatives such as funding schemes and mentoring programs have been designed to fight against it. However, there is no indication on how these initiatives actually impact AI diversity in the short and long term. This work studies the concept of diversity in this particular context and proposes a small set of diversity indicators (i.e. indexes) of AI scientific events. These indicators are designed to quantify the lack of diversity of the AI field and monitor its evolution. We consider diversity in terms of gender, geographical location and business (understood as the presence of academia versus industry). We compute these indicators for the different communities of a conference: authors, keynote speakers and organizing committee. From these components we compute a summarized diversity indicator for each AI event. We evaluate the proposed indexes for a set of recent major AI conferences and we discuss their values and limitations.

中文翻译:

衡量人工智能会议的多样性

人工智能 (AI) 领域缺乏多样性是当今的一个问题,并且已经设计了一些计划,例如资助计划和指导计划来对抗它。然而,没有迹象表明这些举措在短期和长期内实际上如何影响 AI 多样性。这项工作研究了这一特定背景下的多样性概念,并提出了一小组人工智能科学事件的多样性指标(即指数)。这些指标旨在量化人工智能领域缺乏多样性并监测其演变。我们考虑性别、地理位置和业务的多样性(理解为学术界与工业界的存在)。我们为会议的不同社区计算这些指标:作者、主旨发言人和组委会。从这些组件中,我们为每个 AI 事件计算了一个汇总的多样性指标。我们评估了一组近期主要 AI 会议的拟议指标,并讨论了它们的价值和局限性。
更新日期:2020-06-11
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