臺灣農業與製造業發展人工智慧之經濟影響評估

An Economy-wide Assessment of the Development of Artificial Intelligence in Taiwan's Agriculture and Manufacturing Sectors

朱育賢(Yu-Hsien Chu)

指導教授 ： 張靜貞

國立臺灣大學/生物資源暨農學院/農業經濟學研究所/博士(2020年)

https://doi.org/10.6342/NTU202004197

摘要

隨著科技進步日新月異，除了對人類生活型態帶來改變外，對產業的發展也產生影響，其中人工智慧技術的應用對消費型態與生產模式造成質變。為掌握人工智慧技術的發展與應用，行政院於2017年開始積極推動「臺灣AI行動計畫」等相關政策，民間企業亦積極發展人工智慧的技術應用，啟動產業智慧化。臺灣農業因勞動人口高齡化，面對開放進口農產品與極端氣候之威脅，可透過智慧農業的導入改善農業勞動力不足，並提升效率與品質。臺灣製造業以半導體及資通訊科技產業為主，對於推動智慧製造深具發展利基，且有助於掌握臺灣於全球製造業產業鏈的角色。
為解析臺灣產業發展人工智慧之經濟影響與為產業鏈所帶來之效益，本研究以臺灣的農業及製造業供應鏈為重點，透過由中央研究院永續科學中心與澳洲農業與資源經濟局 (ABARES) 共同研發的動態可計算一般均衡模型及資料庫，根據政府積極投資建構基礎環境，以及民間不斷加強產業跨域創新與高值化的發展趨勢，進行情境模擬分析，評估臺灣農業及製造業發展人工智慧之經濟效益。模擬結果顯示，至2025年，透過農業及製造業的產業價值鏈結關係，臺灣的總生產值將較當年度基線增加0.17~1.37個百分點，實質GDP則較當年度基線多出0.38~2.78個百分點，各產業別的產出成長亦較基線增加，總就業方面則較當年度基線減少0.09~0.53個百分點，且於就業需求均有節省人力的顯著效益，顯見在政府政策推動與民間投資發展智慧農業、智慧製造的策略下，除可帶動我國經濟持續成長外，也可成為各產業因應少子化與缺工的有效調適策略。

關鍵字

可計算一般均衡模型 ； 人工智慧 ； 智慧農業 ； 智慧製造 ； 智慧工廠 ； 工業4.0

並列摘要

With the rapid advancement of science and technology, human life styles are reshaped and industry development is also impacted. The use of artificial intelligence technology on various applications has caused fundamental change on consumer behavior and also manufacturing production pattern. In order to master the development and application of artificial intelligence technology, Taiwan government, the Executive Yuan, has been actively promoting "Taiwan AI Action Plan" and some other related policies from 2017. Moreover, the enterprises are also passionately developing the technology applications by using artificial intelligence which initiate industrial intelligence.
Due to the aging population in Taiwan’s agriculture industry, as well as the threat of foreign agricultural product competition and climate change, the introduction of smart agriculture can resolve labor shortage issues, and also improve production efficiency and product quality. Taiwan’s manufacturing industry is dominated by semiconductor, information and communication technology sectors. Therefore, Taiwan has great advantages on promoting and developing smart manufacturing. This could help Taiwan to be in an important position in the global manufacturing industry supply chain.
In order to understand the impact on the economy and the industry supply chain by the development of artificial intelligence in Taiwan’s industry, this study focuses on Taiwan agriculture and manufacturing supply chain. It uses a dynamically computable general equilibrium model and database which is jointly developed by the Taiwan Center for Sustainability Science and the Australian Bureau of Agricultural and Resource Economics and Science (ABARES). The study is based on the government's active investment on building a basic environment, and the enterprises’ continuous development on strengthening cross-segment innovation and the high-value-add. Then it conducted scenario simulation analysis to evaluate the economic benefits of Taiwan's agricultural and manufacturing industry after applying artificial intelligence.
The simulation results show that by 2025, with the correlated industrial value chain relationship between the agriculture and manufacturing industry, Taiwan’s production value will increase by 0.17 to 1.37 percentage points from the baseline of the year, also the real GDP will be 0.38 to 2.78 percentage points more than the baseline of the year. The output growth of each industry also increases from the baseline, and total employment decreases by 0.09 to 0.53 percentage points from the baseline of the year. The decrease in employment demand indicates it has significant benefits in saving manpower, which is evidence of government policies and enterprises investment. Under the strategy of smart agriculture and smart manufacturing strategies, it not only drives the continuous growth of Taiwan's economy, but also become an effective adjustment strategy for various industries in response to the declining birthrate and labor shortage.

並列關鍵字

Computable General Equilibrium (CGE) ； Artificial Intelligence (AI) ； Smart Agriculture ； Smart Manufacturing ； Smart factory ； Industry 4.0

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