AI研究需以应用为导向，回应真实场景中的伦理与社会需求。
Position: We Need Responsible, Application-Driven (RAD) AI Research
- 组建跨学科团队，从用户需求出发开展研究。
- 在具体场景中验证方法，确保技术适配社会价值。
- 通过分阶段测试与实践社区，持续优化应用效果。
本文主张，实现人工智能在科学与社会层面的实质性进展，必须采用负责任、以应用为导向的研究模式（RAD-AI）。随着AI日益融入社会，研究者需深入其实际应用场景，回应伦理、法律、技术及公众讨论等多重约束。提出三阶段路径：第一，构建跨学科团队和以人为本的研究；第二，针对具体场景设计方法、明确伦理承诺、设定合理指标；第三，通过分阶段测试平台与实践共同体验证并维持有效性。未来愿景是发展出既能技术可行又适应社区需求与价值观的AI系统，创造真正可持续的价值。
原文摘要 · Abstract (English)
This position paper argues that achieving meaningful scientific and societal advances with artificial intelligence (AI) requires a responsible, application-driven approach (RAD) to AI research. As AI is increasingly integrated into society, AI researchers must engage with the specific contexts where AI is being applied. This includes being responsive to ethical and legal considerations, technical and societal constraints, and public discourse. We present the case for RAD-AI to drive research through a three-staged approach: (1) building transdisciplinary teams and people-centred studies; (2) addressing context-specific methods, ethical commitments, assumptions, and metrics; and (3) testing and sustaining efficacy through staged testbeds and a community of practice. We present a vision for the future of application-driven AI research to unlock new value through technically feasible methods that are adaptive to the contextual needs and values of the communities they ultimately serve.
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