Reconfiguring Diversity and Inclusion for AI Ethics
Reconfiguring Diversity and Inclusion for AI Ethics
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DOI：
10.1145/3461702.3462622
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发表时间：
2021-05
期刊：
影响因子：
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通讯作者：
Nicole Chi;Emma Lurie;D. Mulligan
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文献类型：
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作者：
Nicole Chi;Emma Lurie;D. Mulligan
积极分子、记者和学者长期以来一直对数据密集型工具和服务中的多样性、代表性和结构性排除之间的关系提出关键问题。我们以绘制企业人工智能伦理的新兴图景为基础，以这些对话的一个结果为中心：将多样性和包容性纳入企业人工智能伦理活动。使用来自设计价值领域的解释性文档分析和分析工具，我们研究了由三家创建应用和服务层人工智能基础设施的公司制作的面向公众的人工智能伦理文档是如何阐述多样性和包容性的工作的：谷歌、微软和Salesforce。我们发现，随着这些文件使多样性和包容性对工程师和技术客户来说变得更容易处理，它们揭示了与20世纪80年代中期企业“多元化管理化”产生共鸣的民权理由的偏离。对技术制品的关注--例如多样化和包容性的数据集--以及以公平取代公平，使得道德工作对日常从业者来说更具可操作性。然而，它们似乎脱离了更广泛的Dei倡议和相关主题专家，后者可以为关于如何实施这些价值观和新解决办法的微妙决定提供必要的背景。最后，按照工程逻辑的配置，多样性和包容性将公司定位为道德配置者，而不是“道德所有者”；尽管这些公司声称拥有人工智能伦理方面的专业知识，但定义多样性和包容性旨在保护谁以及相关领域的责任被推向下游，交给客户。
Activists, journalists, and scholars have long raised critical questions about the relationship between diversity, representation, and structural exclusions in data-intensive tools and services. We build on work mapping the emergent landscape of corporate AI ethics to center one outcome of these conversations: the incorporation of diversity and inclusion in corporate AI ethics activities. Using interpretive document analysis and analytic tools from the values in design field, we examine how diversity and inclusion work is articulated in public-facing AI ethics documentation produced by three companies that create application and services layer AI infrastructure: Google, Microsoft, and Salesforce. We find that as these documents make diversity and inclusion more tractable to engineers and technical clients, they reveal a drift away from civil rights justifications that resonates with the "managerialization of diversity" by corporations in the mid-1980s. The focus on technical artifacts - such as diverse and inclusive datasets - and the replacement of equity with fairness make ethical work more actionable for everyday practitioners. Yet, they appear divorced from broader DEI initiatives and relevant subject matter experts that could provide needed context to nuanced decisions around how to operationalize these values and new solutions. Finally, diversity and inclusion, as configured by engineering logic, positions firms not as "ethics owners" but as ethics allocators; while these companies claim expertise on AI ethics, the responsibility of defining who diversity and inclusion are meant to protect and where it is relevant is pushed downstream to their customers.