114學年材料所-第六週 專題研討課程 演講公告 (114年10月16日)
2025.10.08
題目:
AI時代下工程師如何做自我思維習慣訓練與科技趨勢研判
How do engineers boost the thinking habitual skills and analytics of tech trends in the AI era?
演講者 : 駱榮富(Rong-Fuh Louh)
現職 : 逢甲大學 材料科學與工程學系 專任教授
時間: 114年 10月 16日(四) 3:20~4:00 pm
地點: 鋼構區(3F)共同教室A1302演講廳
演講摘要:
The aim of this lecture is to discuss with students from science and engineering a common phenomenon and problem: AI makes knowledge more accessible, but it also facilitates the spread of misinformation, oversimplification, and intuitive biases. We need to find new frameworks to help people find a sense of reality amidst the flood of information and technological explosion. There are three key areas for analytics of technological trends in the AI era: (1) Sense-making, which follows a complete thinking chain from data → model → narrative → decision. (2) Scenario thinking, which emphasizes "multiple possibilities" rather than sole predictions. Engineers have to design multiple future scenarios for technology and assess their risks and societal impacts. (3) Interdisciplinary translation, which transforms scientific knowledge into a language accessible to the public, is the core of third-millennium thinking. Leveraging AI-powered collaboration between brain and machine to validate insights and reasoning. We envision that engineers in the third millennium transcending the role of technical problem solvers will become the meaning builders and co-designers of the future. We ‘d better constantly remind each other that in a world filled with noise and illusion, hard-core intelligence no longer seeks single answers, but rather continuously revises, collaborates, and collectively asks better questions.
AI時代下工程師如何做自我思維習慣訓練與科技趨勢研判
How do engineers boost the thinking habitual skills and analytics of tech trends in the AI era?
演講者 : 駱榮富(Rong-Fuh Louh)
現職 : 逢甲大學 材料科學與工程學系 專任教授
時間: 114年 10月 16日(四) 3:20~4:00 pm
地點: 鋼構區(3F)共同教室A1302演講廳
演講摘要:
The aim of this lecture is to discuss with students from science and engineering a common phenomenon and problem: AI makes knowledge more accessible, but it also facilitates the spread of misinformation, oversimplification, and intuitive biases. We need to find new frameworks to help people find a sense of reality amidst the flood of information and technological explosion. There are three key areas for analytics of technological trends in the AI era: (1) Sense-making, which follows a complete thinking chain from data → model → narrative → decision. (2) Scenario thinking, which emphasizes "multiple possibilities" rather than sole predictions. Engineers have to design multiple future scenarios for technology and assess their risks and societal impacts. (3) Interdisciplinary translation, which transforms scientific knowledge into a language accessible to the public, is the core of third-millennium thinking. Leveraging AI-powered collaboration between brain and machine to validate insights and reasoning. We envision that engineers in the third millennium transcending the role of technical problem solvers will become the meaning builders and co-designers of the future. We ‘d better constantly remind each other that in a world filled with noise and illusion, hard-core intelligence no longer seeks single answers, but rather continuously revises, collaborates, and collectively asks better questions.