Philosophy through Machine Learning

被引:1
|
作者
Lim, Daniel [1 ]
机构
[1] Duke Kunshan Univ, Philosophy, Suzhou, Peoples R China
关键词
D O I
10.5840/teachphil202018116
中图分类号
B [哲学、宗教];
学科分类号
01 ; 0101 ;
摘要
In a previous article (2019), I motivated and defended the idea of teaching philosophy through computer science. In this article, I will further develop this idea and discuss how machine learning can be used for pedagogical purposes because of its tight affinity with philosophical issues surrounding induction. To this end, I will discuss three areas of significant overlap: (i) good / bad data and David Hume's so-called Problem of Induction, (ii) validation and accommodation vs. prediction in scientific theory selection and (iii) feature engineering and Nelson Goodman's so-called New Riddle of Induction.
引用
收藏
页码:29 / 46
页数:18
相关论文
共 50 条
  • [41] Advancing Rheumatology Care Through Machine Learning
    Hugle, Thomas
    PHARMACEUTICAL MEDICINE, 2024, 38 (02) : 87 - 96
  • [42] Theorizing Mathematical Narrative through Machine Learning
    Gati, Daniella
    JNT-JOURNAL OF NARRATIVE THEORY, 2023, 53 (01): : 139 - 165
  • [43] Volcanic Ash Classification Through Machine Learning
    Benet, Damia
    Costa, Fidel
    Widiwijayanti, Christina
    GEOCHEMISTRY GEOPHYSICS GEOSYSTEMS, 2024, 25 (03)
  • [44] Extraction of Definitional Contexts Through Machine Learning
    Mijangos, Victor
    Montes, Azucena
    Sierra, Gerardo
    2015 26TH INTERNATIONAL WORKSHOP ON DATABASE AND EXPERT SYSTEMS APPLICATIONS (DEXA), 2015, : 217 - 221
  • [45] Predicting Toxicity Properties through Machine Learning
    Adriana Borrero, Luz
    Sanchez Guette, Lilibeth
    Lopez, Enrique
    Bonerge Pineda, Omar
    Buelvas Castro, Edgardo
    11TH INTERNATIONAL CONFERENCE ON AMBIENT SYSTEMS, NETWORKS AND TECHNOLOGIES (ANT) / THE 3RD INTERNATIONAL CONFERENCE ON EMERGING DATA AND INDUSTRY 4.0 (EDI40) / AFFILIATED WORKSHOPS, 2020, 170 : 1011 - 1016
  • [46] Designing Poisson Integrators Through Machine Learning
    Vaquero, Miguel
    Martin de Diego, David
    Cortes, Jorge
    IFAC PAPERSONLINE, 2024, 58 (06): : 31 - 35
  • [47] Virtual Sensors Determined through Machine Learning
    Iwashita, Yumi
    Stoica, Adrian
    Nakashima, Kazuto
    Kurazume, Ryo
    Torresen, Jim
    2018 WORLD AUTOMATION CONGRESS (WAC), 2018, : 318 - 321
  • [48] Towards the study on the geochemistry through machine learning
    Xu, Na
    Huang, Bin
    Li, Qiang
    Zhu, Wei
    Wang, Zhiwei
    Wang, Ru
    Meitan Xuebao/Journal of the China Coal Society, 2022, 47 (05): : 1895 - 1907
  • [49] Maintaining container sustainability through machine learning
    Mahendra Pratap Yadav
    Dharmendra Kumar Rohit
    Cluster Computing, 2021, 24 : 3725 - 3750
  • [50] Maintaining container sustainability through machine learning
    Yadav, Mahendra Pratap
    Rohit
    Yadav, Dharmendra Kumar
    CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2021, 24 (04): : 3725 - 3750