arXiv:2510.10338cs.AIcs.CY2025-10

让医疗AI更包容,反而能带来更大经济回报。

Beyond Ethics: How Inclusive Innovation Drives Economic Returns in Medical AI

  • 为多样场景设计的AI系统,在更广市场中表现更好。
  • 包容性设计可降低风险成本,提升模型泛化能力。
  • 适合关注长期竞争力与可持续创新的团队。

尽管医疗AI公平性具有伦理正当性,但其经济与战略价值仍被低估。本文提出‘包容性创新红利’概念:专为多元、受限使用场景设计的解决方案,反而能在更广泛市场中创造更高经济回报。基于辅助技术演变为数十亿美元主流产业的案例,我们揭示包容性医疗AI开发可带来超越合规要求的商业价值。识别出四大驱动机制:(1)地理扩展与信任加速带来的市场扩张;(2)减少补救成本与诉讼风险;(3)更强泛化能力与更低技术负债;(4)人才吸引与临床采纳优势。提出医疗AI包容性创新框架(HAIIF),提供量化评估工具,将公平与包容从监管检查项转化为战略差异化来源。研究显示,持续投入包容性设计的机构将获得更广市场覆盖与持续竞争优势,而将其视为负担者将因网络效应和数据优势的累积而处于劣势。

原文摘要 · Abstract (English)

While ethical arguments for fairness in healthcare AI are well-established, the economic and strategic value of inclusive design remains underexplored. This perspective introduces the ``inclusive innovation dividend'' -- the counterintuitive principle that solutions engineered for diverse, constrained use cases generate superior economic returns in broader markets. Drawing from assistive technologies that evolved into billion-dollar mainstream industries, we demonstrate how inclusive healthcare AI development creates business value beyond compliance requirements. We identify four mechanisms through which inclusive innovation drives returns: (1) market expansion via geographic scalability and trust acceleration; (2) risk mitigation through reduced remediation costs and litigation exposure; (3) performance dividends from superior generalization and reduced technical debt, and (4) competitive advantages in talent acquisition and clinical adoption. We present the Healthcare AI Inclusive Innovation Framework (HAIIF), a practical scoring system that enables organizations to evaluate AI investments based on their potential to capture these benefits. HAIIF provides structured guidance for resource allocation, transforming fairness and inclusivity from regulatory checkboxes into sources of strategic differentiation. Our findings suggest that organizations investing incrementally in inclusive design can achieve expanded market reach and sustained competitive advantages, while those treating these considerations as overhead face compounding disadvantages as network effects and data advantages accrue to early movers.

医疗AI包容设计经济回报战略创新

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