If the personal-data management is aggregated to the data subject and the data can be utilized by his or her AI and shared safely with others, then businesses will be spared the cost of storing large amounts of personal data and the risk of data leaks, and individuals will be able to fully use their data to maximize their own profits, increasing the value of various services. PLR is a software library for such personal-data management, possibly supporting hundreds of millions of users with just the application-maintenance cost. The revision of relevant regulations, and the shift to IT in education and healthcare may aggregate various personal data to data subjects, and PLR is considered the safest and least expensive way to facilitate this. We are studying applications of PLR and related social systems.

Although information sharing and consensus building through documents are essential for the operation of society, the average adult’s ability to comprehend documents is quite low. Since this problem cannot be solved by AI or education, a new form of document easier to read and write is needed. A graph document as in the figure is a good candidate. We have experimentally shown that graph documents are significantly higher-quality than traditional text documents, both in single-authored and multi-authored composition. The intellectual productivity of society will hence dramatically improve if we provide appropriate editing apps and popularize graph documents. So we are developing a graph-document editing app (Semantic Editor) to collaboratively edit document data safely and inexpensively by incorporating PLR. We are also conducting research on cooperation among services based on graph documents, and knowledge acquisition by collecting and analyzing a large number of graph documents.