调研政策制定者对AI匹配无家可归者住房资源的接受度与设计期待。
Toward AI Matching Policies in Homeless Services: A Qualitative Study with Policymakers
- 通过访谈13位洛杉矶政策制定者，探究AI匹配系统的可行思路。
- 政策制定者认可AI工具价值，但强调需与人工决策协同使用。
- 提出透明、公平、高效的设计考量，适合算法伦理与社会服务研究者。
人工智能研究人员提出了多种数据驱动算法，以优化将无家可归者匹配到稀缺住房资源的流程。然而，这些算法在实践中是否被接纳、如何被采纳，以及其带来的影响仍不明确。通过对洛杉矶13位无家可归者服务政策制定者的半结构化访谈，我们探究了这些变革推动者对将人工智能纳入住房资源匹配流程的看法，识别出他们在效率、公平性和透明度方面的潜在收益与风险。定性分析表明，尽管意识到诸多复杂因素，政策制定者仍欢迎经过审慎设计的AI匹配工具，并主张其应与人类决策者协同使用。虽然尚未就具体系统设计达成共识，但来自政策制定者的洞见为未来研究人员和实践者构建负责任的算法系统提供了重要设计启示，尤其适用于资源有限场景下的决策支持。
原文摘要 · Abstract (English)
Artificial intelligence researchers have proposed various data-driven algorithms to improve the processes that match individuals experiencing homelessness to scarce housing resources. It remains unclear whether and how these algorithms are received or adopted by practitioners and what their corresponding consequences are. Through semi-structured interviews with 13 policymakers in homeless services in Los Angeles, we investigate whether such change-makers are open to the idea of integrating AI into the housing resource matching process, identifying where they see potential gains and drawbacks from such a system in issues of efficiency, fairness, and transparency. Our qualitative analysis indicates that, even when aware of various complicating factors, policymakers welcome the idea of an AI matching tool if thoughtfully designed and used in tandem with human decision-makers. Though there is no consensus as to the exact design of such an AI system, insights from policymakers raise open questions and design considerations that can be enlightening for future researchers and practitioners who aim to build responsible algorithmic systems to support decision-making in low-resource scenarios.
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