借鉴生物医学科学文化,构建健康AI发展传统。
Towards a Healthy AI Tradition: Lessons from Biology and Biomedical Science
- 以生物医学研究的文化传统为蓝本,重塑AI研究生态。
- 强调协作、可复现性与快速人才培养,提升研究效率。
- 适合关注AI可持续发展与科研范式改革的研究者。
人工智能作为深刻影响哲学、计算机科学、工程、数学、数据与决策科学、经济学及认知科学、神经科学等多个领域的学科,其应用广泛且影响力巨大,未来对科学发展的推动潜力尤为令人振奋。尽管对知识、推理、认知和学习的理解已有数百年历史,但人工智能仍属新兴领域。由于与众多学科深度交叉,AI在建立稳固身份与文化方面面临挑战。本文建议将快速发展的AI文化与生物医学科学进行对比,以此开启一种健康的AI传统,助力实现通用人工智能(AGI)及更远目标。人工智能与生物医学科学的协同发展将带来双重收益。此前观点提出,生物医学实验室可借鉴人工智能实验室中的物流管理传统,以增强协作、提高研究可复现性、降低风险规避倾向,并加速博士生与研究员的培养路径。本文则聚焦于从更高层次的文化维度,将生物医学科学的实践模式引入人工智能领域,以优化其长期发展生态。
原文摘要 · Abstract (English)
AI is a magnificent field that directly and profoundly touches on numerous disciplines ranging from philosophy, computer science, engineering, mathematics, decision and data science and economics, to cognitive science, neuroscience and more. The number of applications and impact of AI is second to none and the potential of AI to broadly impact future science developments is particularly thrilling. While attempts to understand knowledge, reasoning, cognition and learning go back centuries, AI remains a relatively new field. In part due to the fact it has so many wide-ranging overlaps with other disparate fields it appears to have trouble developing a robust identity and culture. Here we suggest that contrasting the fast-moving AI culture to biological and biomedical sciences is both insightful and useful way to inaugurate a healthy tradition needed to envision and manage our ascent to AGI and beyond (independent of the AI Platforms used). The co-evolution of AI and Biomedical Science offers many benefits to both fields. In a previous perspective, we suggested that biomedical laboratories or centers can usefully embrace logistic traditions in AI labs that will allow them to be highly collaborative, improve the reproducibility of research, reduce risk aversion and produce faster mentorship pathways for PhDs and fellows. This perspective focuses on the benefits to AI by adapting features of biomedical science at higher, primarily cultural levels.
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