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IT and AI Technology and New Agricultural Management (Japanese)

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  • YAMASHITA Kazuhito

Abstract

Certain advanced technology such as biotechnology have not made any great or significant contributions to the advancement of agriculture. Researchers have only explored the feasibility of technology and have yet to consider the aspects of economics or management. This applies to a portion of the agricultural industry such as fruits and vegetables but does not pertain to grain production which is a vital and indispensable food source for humans. Furthermore, technology has made partial improvements to agricultural production but has not provided fundamental solutions for Japanese agriculture in general. There are concerns that the same kinds of mistakes made in the past technological developments may be repeated in the current application of information technology (IT) and artificial intelligence (AI) technology to agriculture. IT and AI technology, which gathers, analyzes, or assimilates information, could potentially improve the agricultural system as a whole while biotechnology has only addressed the production side. In particular, if we could create open access big data along with an appropriate agricultural policy reform, Japanese agriculture would be drastically enhanced by IT and AI technology. The open access big data will enable IT and AI technology to make great contributions to the national food security. In order to create open access big data, we have to overcome numerous problems including how to collect interoperable data among different stakeholders and how to support farmers and industry participants who are not necessarily well versed in those technologies. In these aspects, this paper tries to make specific policy proposals to overcome such difficulties.

Suggested Citation

  • YAMASHITA Kazuhito, 2017. "IT and AI Technology and New Agricultural Management (Japanese)," Policy Discussion Papers (Japanese) 17017, Research Institute of Economy, Trade and Industry (RIETI).
  • Handle: RePEc:eti:rpdpjp:17017
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    File URL: https://www.rieti.go.jp/jp/publications/pdp/17p017.pdf
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