(Source) "Survey Research into Various Issues Relating to the ICT Economy in the IoT Age," MIC (2017)

## (2) The Impact of Data Distribution and Utilization

Digital data is characterized by the following.

• It is easily reproduced (non-eliminative, non-competitive)

• It is instantly communicable and has almost zero marginal cost

Digital data has come to be used to a certain extent within information society, subsequent to the 3rd Industrial Revolution. The characteristics of data distribution in the $ 4^{th} $ Industrial Revolution (Society5.0) include the elements of wider use of smartphones, the rollout of various sensors, the exponential growth in processing capability of computers (including AI), and the fact that data distribution and storage is increasing in both quantity and quality.

The establishment of cyber security is a prerequisite, but there is increasing potential for combinations and partnerships in the increased volume and number of types of data, and it is believed that this offers potential for creation of value and problem solving.

An old but also new problem with data analysis and AI is the determination of what variables (feature values) are used in analysis. Machine learning is a category of technology necessary for humans to select feature values. Between 2016 and 2017, however, it became possible for analysis that used to take data scientists several months to be implemented within a few hours, as a result of the software known as DataRobot, provided by DataRobot Inc., an American venture company. The soft

### 2. Japan in 2030 after adopting the IoT

In this section, we look at predicted values for various indicators including market scale between 2011 and 2030 $ ^{24} $ (induced production value), real GDP and the ware still requires feature values to be input by humans, but DataRobot then determines which feature values are effective, and since most of the trial and error procedures formerly implemented by data scientists are mechanized, the time required for analysis is expected to become much shorter, and the scope of analysis is expected to expand, in the situation of a shortage of data scientists.

Changes in data and data utilization have impacted economic growth and society. They have not only brought about changes on the supply side and the demand side, but also made it possible to match suppliers and consumers in real time, thereby improving productivity and enabling the effective utilization of resources and development of new services in ways that were not possible until now. It is believed that the matching of supply and demand is particularly effective in the broader sense of the service industry. (Figure 3-5-1-3)

The share held by tertiary industry is growing globally in many countries, and the economy is also becoming increasingly service-oriented. From a different perspective, in order to achieve economic growth it is necessary to improve productivity within the broader sense of the service industry, which accounts for a large market share.

Since many are intangible from the point of view of service, the role of digital data is considered to be significant in terms of matching supply and demand at the same time and in the same place.

number of people in the workforce $ ^{25} $ (induced labor value), and compare the base scenario based on economic predictions by the Cabinet for the medium- to long-term