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Knowledge Production – The Limits of Big Data and AI

Knowledge Production – The Limits of Big Data and AI

Presentation slide for Knowledge Production in a Data Driven Society of lecture series; MWS Web Forum Series 'The Digital Transformation' on September 23rd, 2021 online.

The presentation will discuss knowledge production in the context of platform business models, big data and artificial intelligence. The cost of generating, storing, and processing data has dropped significantly. However, with such technological advancement, it is possible to realize progress only in restricted areas. Three technological and social elements such as common data architecture, advanced trust framework and ethics by design, are necessary for sustainable knowledge production to realize a data driven society.

Yoshiaki Fukami

September 25, 2021

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  1. Knowledge Production The Limits of Big Data and AI Knowledge

    Production in a Data Driven Society MWS Web Forum Series ‘The Digital Transformation’ Yoshiaki FUKAMI, Ph. D Gakushuin University/ Keio University yoshiakiˏfukami-lab.com
  2. Information necessary to utilize • Common (meta) data model of

    context –Model of devices • Measuring method • Measurement precision –Procedure of data generation • Time • Method • Etc. (C)Yoshiaki FUKAMI
  3. SEKI model (Nonaka and Takeuchi, 1995) (C)Yoshiaki FUKAMI Socialization Externalization

    Internalization Combination Tacit Knowledge Tacit Knowledge Explicit Knowledge Explicit Knowledge
  4. Prejudice for digital data and knowledge • Is digital data

    explicit knowledge? • It may cost more to convert tacit data to explicit knowledge than human’s one. (C)Yoshiaki FUKAMI
  5. •Lack of common data model for recognizing context •Bias in

    data generation, sampling and algorism development •Inequality of data and skilled human resource (C)Yoshiaki FUKAMI
  6. Enabling Environment of Knowledge Production • Pursuit for More Exhaustive

    and Accessible Data Set. • Introducing Broadly Accepted Data Model • Exhaustive Data for Eliminating Bias • Control of Risks Associated with Data Provision • Global Distribution of Human Resources for Utilizing Knowledge Generation (C)Yoshiaki FUKAMI