人工智能科学家对科学认识论的挑战

The Challenge of Artificial Intelligence Scientists to the Epistemology of Science

[目的/意义]本研究旨在探讨人工智能科学家可能给科学认识论带来的挑战。[方法/过程]科学发现一直是人工智能研究的重要主题,人工智能科学发现的下一步是发展人工智能科学家,即能进行自主和自动化科学发现的人工智能系统,其研究质量与最优秀的人类科学家的水准无法区分。回顾人工智能在科学研究中的相关应用之后,阐述了人工智能科学家最为重要的特征及其研究计划的核心,在此基础上提出了人工智能科学家在认识论层面带来两个根本性的改变:人工智能能力跃升和人工智能驱动的科学研究范式嬗变。[结果/结论]对于相关科学认识论问题的讨论需要走出一般的哲学式论辩,面向即将到来的人工智能科学革命提出了搁置否定性的批评、关注过渡期的难题、动态追踪可能的突破口、寻求更好的类比等4个认识论策略。

[Purpose/Significance]This study aims to explore the challenges that artificially intelligent(AI)scientists may bring to scientific epistemology.[Method/Process]Scientific discovery has long been of interest to AI researchers.The next big step in AI is the development of AI scientists.AI scientists should be able to independently motivate,make,understand,and communicate discoveries.Although the current robot scientists are still just a form of AI-driven automated experimental apparatus,and the best AI systems today cannot define their own hypothesis space and experimental design.At best,they can be considered to be a primitive form of AI scientists.Clearly,the specific path of AI-driven scientific research or the transition to AI scientists will inevitably be influenced by the frontier development of AI.Current AI systems must overcome the following major technical challenges:1)making strategic choices in their research goals;2)developing the ability to generate exciting and novel hypotheses in areas that push boundaries;3)designing innovative approaches and experiments to test hypotheses that go beyond the use of prototype experiments;4)focusing on and describing important discoveries in a way that can be understood by human scientists.The highly autonomous AI scientists can either make discoveries on their own or collaborate with other human and machine scientists to make Nobel-level discoveries.After reviewing the relevant AI applications in scientific research,this study illustrates the main characteristics of AI scientists and the two disruptive changes they bring about at the epistemological level:a leap in AI capabilities and AI for Science as the 5th paradigm of scientific research.[Results/Conclusions]The implications of AI for Science are revolutionary,but recent AI-driven explorations in scientific research increasingly support the possibility of its realization.In this situation,discussions on the epistemological issues of relevant sciences need to go beyond general philosophical debates and instead explore epistemological strategies for the coming scientific revolution in AI.In view of the coming scientific revolution in AI,this study proposes four strategies.First,we should pay more attention to the problems and solutions in the process of developing AI scientists.Second,the key to advancing the scientific revolution in AI is to find ways to eliminate factors that may lead to failure.Then,we use different strategies to achieve the scientific revolution of AI.Finally,we take advantage of metaphorical methods to help us develop AI scientists.