Causal Reasoning and Meno's Paradox

被引:0
|
作者
Chen, Melvin [1 ]
Chew, Lock Yue [2 ]
机构
[1] Nanyang Technol Univ, Philosophy, 50 Nanyang Ave, Singapore 639798, Singapore
[2] Nanyang Technol Univ, Phys, 50 Nanyang Ave, Singapore 639798, Singapore
关键词
Causal epistemology; Causal reasoning; Automation question; Meno's Paradox; VIRTUE;
D O I
10.1007/s00146-020-01037-4
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Causal reasoning is an aspect of learning, reasoning, and decision-making that involves the cognitive ability to discover relationships between causal relata, learn and understand these causal relationships, and make use of this causal knowledge in prediction, explanation, decision-making, and reasoning in terms of counterfactuals. Can we fully automate causal reasoning? One might feel inclined, on the basis of certain groundbreaking advances in causal epistemology, to reply in the affirmative. The aim of this paper is to demonstrate that one still has good skeptical grounds for resisting any conclusions in favour of the automation of causal reasoning. If by causal reasoning is meant the entirety of the process through which we discover causal relationships and make use of this knowledge in prediction, explanation, decision-making, and reasoning in terms of counterfactuals, then one relies besides on tacit knowledge, as might be constituted by or derived from the epistemic faculty virtues and abilities of the causal reasoner, the value systems and character traits of the causal reasoner, the implicit knowledge base available to the causal reasoner, and the habits that sustain our causal reasoning practices. While certain aspects of causal reasoning may be axiomatized and formalized and algorithms may be implemented to approximate causal reasoning, one has to remain skeptical about whether causal reasoning may be fully automated. This demonstration will involve an engagement with Meno's Paradox.
引用
收藏
页码:1837 / 1845
页数:9
相关论文
共 50 条
  • [31] Causal reasoning in typical computer vision tasks
    KeXuan Zhang
    QiYu Sun
    ChaoQiang Zhao
    Yang Tang
    Science China Technological Sciences, 2024, 67 : 105 - 120
  • [32] Causal reasoning in typical computer vision tasks
    Zhang, Kexuan
    Sun, Qiyu
    Zhao, Chaoqiang
    Tang, Yang
    SCIENCE CHINA-TECHNOLOGICAL SCIENCES, 2024, 67 (01) : 105 - 120
  • [33] Hindsight bias and causal reasoning: a minimalist approach
    Jennelle E. Yopchick
    Nancy S. Kim
    Cognitive Processing, 2012, 13 : 63 - 72
  • [34] Causal Reasoning Methods in Medical Domain: A Review
    Wu, Xing
    Li, Jingwen
    Qian, Quan
    Liu, Yue
    Guo, Yike
    ADVANCES AND TRENDS IN ARTIFICIAL INTELLIGENCE: THEORY AND PRACTICES IN ARTIFICIAL INTELLIGENCE, 2022, 13343 : 184 - 196
  • [35] Hindsight bias and causal reasoning: a minimalist approach
    Yopchick, Jennelle E.
    Kim, Nancy S.
    COGNITIVE PROCESSING, 2012, 13 (01) : 63 - 72
  • [36] Applying Causal Reasoning to Analyze Value Systems
    Macedo, Patricia
    Camarinha-Matos, Luis M.
    EMERGING TRENDS IN TECHNOLOGICAL INNOVATION, 2010, 314 : 3 - 13
  • [37] Heuristics in causal reasoning and their influence on eyewitness testimony
    Remijn, Caroline A. C.
    Crombag, Hans F. M.
    PSYCHOLOGY CRIME & LAW, 2007, 13 (02) : 201 - 211
  • [38] Applying causal reasoning to analyze value systems
    MacEdo P.
    Camarinha-Matos L.M.
    IFIP Advances in Information and Communication Technology, 2010, 314 : 3 - 13
  • [39] The special status of actions in causal reasoning in rats
    Leising, Kenneth J.
    Wong, Jared
    Waldmann, Michael R.
    Blaisdell, Aaron P.
    JOURNAL OF EXPERIMENTAL PSYCHOLOGY-GENERAL, 2008, 137 (03) : 514 - 527
  • [40] Causal reasoning for human supervised process reconfiguration
    Garcia-Beltran, C
    Gentil, S
    PROCEEDINGS OF THE 2001 IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL (ISIC'01), 2001, : 91 - 96