重建信任：AI方法在人工智能风险管理中的奇怪之处
Rebuilding Trust: Queer in AI Approach to Artificial Intelligence Risk Management
摘要：
值得信赖的人工智能（AI）已经成为一个重要的话题，因为对AI系统及其创造者的信任已经丧失。研究人员、企业和政府长期以来都有将边缘化群体排除在技术开发、部署和监督之外的痛苦历史。因此，这些技术对少数群体用处不大，甚至有害。我们认为，任何渴望信任的人工智能开发、部署和监控框架都必须结合女权主义、非剥削性的参与式设计原则，以及强大的、外部的、持续的监控和测试。我们还解释了在透明度、公平性和问责制之外考虑可信度的重要性，特别是考虑正义和将权力转移给被剥夺权力的人，作为任何值得信赖的人工智能系统的核心价值。创建值得信赖的人工智能首先要资助、支持和授权像Queer in AI这样的草根组织，以便人工智能领域具有多样性和包容性，从而可信且有效地开发值得信赖的人工智能。我们利用人工智能中的酷儿通过多年的工作和宣传发展起来的专家知识，讨论性别，性行为和酷儿身份的其他方面是否以及如何在数据集和人工智能系统中使用，以及如何减轻这些方面的危害。在此基础上，我们分享了一种性别化的人工智能方法，并进一步提出了一种奇怪的认识论，并分析了它可以给人工智能带来的好处。我们还讨论了如何用这种奇怪的认识论来规范人工智能，提出了制定与人工智能和性别多样性以及隐私和奇怪的数据保护相关的政策的框架。
英文摘要：
Trustworthy artificial intelligence (AI) has become an important topic because trust in AI systems and their creators has been lost. Researchers, corporations, and governments have long and painful histories of excluding marginalized groups from technology development, deployment, and oversight. As a result, these technologies are less useful and even harmful to minoritized groups. We argue that any AI development, deployment, and monitoring framework that aspires to trust must incorporate both feminist, non-exploitative participatory design principles and strong, outside, and continual monitoring and testing. We additionally explain the importance of considering aspects of trustworthiness beyond just transparency, fairness, and accountability, specifically, to consider justice and shifting power to the disempowered as core values to any trustworthy AI system. Creating trustworthy AI starts by funding, supporting, and empowering grassroots organizations like Queer in AI so the field of AI has the diversity and inclusion to credibly and effectively develop trustworthy AI. We leverage the expert knowledge Queer in AI has developed through its years of work and advocacy to discuss if and how gender, sexuality, and other aspects of queer identity should be used in datasets and AI systems and how harms along these lines should be mitigated. Based on this, we share a gendered approach to AI and further propose a queer epistemology and analyze the benefits it can bring to AI. We additionally discuss how to regulate AI with this queer epistemology in vision, proposing frameworks for making policies related to AI & gender diversity and privacy & queer data protection.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
