摘要
人工智能驱动的科学研究(AI for Science)是大数据时代以机器学习为代表的智能技术与科学研究深度融合的产物,在物理科学、生命科学等多领域科研场景中已经取得突破性进展。以AI支撑前沿科技发展的新模式正在改变科学研究的方式,加速科学发现的进程,引发了科学研究范式的新革命,并产生广泛的社会影响。作为新兴的科学问题解决方案,AI for Science目前仍面临诸多困境,亟需国家政策支撑与平台建设,通过实现项目、平台、人才等维度的跨领域融合与重构,以更好地发挥AI在科研领域的渗透性与颠覆性力量。
Artificial intelligence-driven scientific research(AI for Science)is the product of the deep integration of AI technology represented by Machine Learning and scientific research in the era of big data.Breakthroughs have been made in research scenarios in multiple scientific fields such as Physics and Life Science.This novel mode of supporting the development of cutting-edge science and technology with AI has been accelerating current scientific discovery,changing the way and process of scientific research,triggering a new revolution in the paradigm of research,and generating a wide range of social impacts.As an emerging solution to scientific problems,AI for Science still faces many dilemmas and needs national policy support and platform construction.Through the cross-domain integration and reconstruction of the dimensions of projects,platforms,and talents,the penetrating and revolutionary role of AI in the field of scientific research can be better exploited.
作者
李建会
杨宁
Li Jianhui;Yang Ning
出处
《广东社会科学》
CSSCI
北大核心
2023年第6期81-92,I0001,I0002,共14页
Social Sciences in Guangdong
基金
国家社会科学基金重大项目“大数据驱动的生命科学研究范式变革研究”(项目号22&ZD045)的阶段性成果。
