SMART+框架助力AI系统安全合规,覆盖医疗、金融、制造等领域。
The SMART+ Framework for AI Systems
- 基于安全、透明、问责等六大支柱构建跨行业AI治理框架
- 整合隐私保护与公平性控制,提升系统可审计性和合规能力
- 适用于医疗临床研究及高风险产业的AI监管与风险防控
人工智能系统已深度融入医疗、金融、制造等多个行业。在临床研究中,AI支持临床试验中的不良事件自动检测、患者入组资格筛选和数据质量验证;在金融领域,实现实时欺诈检测、贷款风险自动化评估与算法决策;在制造行业,推动预测性维护、视觉质检和基于实时数据的生产流程优化。尽管提升了运营效率,这些技术也带来了安全、责任归属与合规方面的挑战。为此,本文提出SMART+框架——以安全、监控、问责、可靠性、透明性为基础,延伸涵盖隐私与安全、数据治理、公平性与偏见、防护机制。该框架提供了一种实用且全面的AI系统评估与治理方法,契合不断演进的监管要求,集成操作保障、监督程序与强化的隐私治理措施。实证表明,SMART+能有效降低风险、增强信任并提升合规准备度,为临床研究等领域的负责任AI应用提供坚实基础。
原文摘要 · Abstract (English)
Artificial Intelligence (AI) systems are now an integral part of multiple industries. In clinical research, AI supports automated adverse event detection in clinical trials, patient eligibility screening for protocol enrollment, and data quality validation. Beyond healthcare, AI is transforming finance through real-time fraud detection, automated loan risk assessment, and algorithmic decision-making. Similarly, in manufacturing, AI enables predictive maintenance to reduce equipment downtime, enhances quality control through computer-vision inspection, and optimizes production workflows using real-time operational data. While these technologies enhance operational efficiency, they introduce new challenges regarding safety, accountability, and regulatory compliance. To address these concerns, we introduce the SMART+ Framework - a structured model built on the pillars of Safety, Monitoring, Accountability, Reliability, and Transparency, and further enhanced with Privacy & Security, Data Governance, Fairness & Bias, and Guardrails. SMART+ offers a practical, comprehensive approach to evaluating and governing AI systems across industries. This framework aligns with evolving mechanisms and regulatory guidance to integrate operational safeguards, oversight procedures, and strengthened privacy and governance controls. SMART+ demonstrates risk mitigation, trust-building, and compliance readiness. By enabling responsible AI adoption and ensuring auditability, SMART+ provides a robust foundation for effective AI governance in clinical research.
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