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Title: | Automata : a babbage machine analyst based human automation paradigm | Authors: | Tan, Yan Hao | Keywords: | Engineering::Mechanical engineering | Issue Date: | 2021 | Publisher: | Nanyang Technological University | Source: | Tan, Y. H. (2021). Automata : a babbage machine analyst based human automation paradigm. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/155748 | Abstract: | Singapore is undergoing an automation transformation through Artificial Intelligence (AI) to substitute human labour with machine and robots. However, AI’s confusing narrative has inexplicably prevented its sound development and deployment. In this thesis, a level-headed human automation paradigm was interpreted, formalized, and experimented through engineering demonstrations. Alan Turing’s Computing Machinery and Intelligence (CMI) was used as foundational element to identify and investigate arguments and circumstances which lead to AI’s inception and its critique. Two causal precedence in automata grand challenge and automating rational mental activities were identified as CMI’s underlying motivation and AI bounded by this designer’s intent. A Charles Babbage machine analyst based human automation framework was formalized by synthesizing elements from CMI and its accompanying literature. Two personified system of machines were discretized through the framework and experimented for efficacy (with a third in Appendix B). These two cases were representatives of key industries that were undergoing drastic job rescoping exacerbated by the COVID-19 situation. All two artefacts had demonstrated efficacy for respective applications by employing suitable sensors and customized AI algorithms. It has been demonstrated that the proposed human automation framework proposed serves as a valid tool to engineer human automations and handle AI. | URI: | https://hdl.handle.net/10356/155748 | DOI: | 10.32657/10356/155748 | Schools: | School of Mechanical and Aerospace Engineering | Rights: | This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | MAE Theses |
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20220126 - PhD Thesis signed.pdf | 5.01 MB | Adobe PDF | ![]() View/Open |
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