Fascinating endlessness

Thu 21 August 2025, Philippe Ropenga Digital assets Artificial intelligence Graphs

Software development and legal practice are threatened by uniformisation: the paperwork and the output tend to matter more than the solution to a practical issue. This is true with intellectual property: people struggle to show their efforts to support their claim and once they get the title they tend to downplay the need to preserve their intellectual capital and stop tracking what has been done with the knowledge involved in the legal title.¹ Their knowledge becomes a dead language that is sometimes hard to understand. This puts people who do not want to pay others for their work in a very comfortable position: they reuse the piece of work to achieve a different result and claim that it is theirs. Previous contributions get less attention than the latest one.² Once you know what a document is made of, do you really care about what a contributor thinks of your reuse of the material as long as it complies with the licence? A software developer may argue that this is how software development goes, especially in open source where one may freely hack the work of others, following one's instincts to achieve a given result. A craftsman such as a baker does not need to hack, he knows that he shares professional knowledge and relies on it when he applies the rules of his art. His work is not purely logical although logic is useful to notice the train of thought that leads to a practical result.³ Not everything that is felt is easily described and yet the way in which one connects the dots from theory to practice can make a big difference, at least in a legal matter⁴. Graph theory is a source of inspiration for anyone who wants to overcome this obstacle since connecting dots or vertices is a common issue.

Following Polanyi's Personal knowledge, first published in 1958, one notices that theory is not needed to discover anything but to understand better what one has discovered although anyone tends to pay a greater attention to discoveries that are related to scientific laws.⁵ One does similarly not need to produce data about the thing that one has discovered because the discovery exists but is hard to share with others without data and people may pay a greater attention to the data related to the discovery than to the discovery itself. Lyotard has highlighted in a book first published in French in 1979 that knowledge had to be formulated in machine language to be shared among people.⁶ This seems obvious nowadays. When data prevail over facts, feelings, and experience, work becomes less valuable because, unlike data, it cannot be fully processed. When anything that is open source can be accessed and processed, the person who shared something with others does not count as much as the data derived from his or her work because facts cannot be processed as such; open source becomes an open bar.⁷

During Antiquity, vanities were as important⁸ as data today. People were less keen on recording anything that they were doing, probably because that they did not have tools such as computers to do it; probably also because innovation is a modern issue that underpins intellectual property. Many people then knew that long lasting creations were out of reach of helpless human beings.⁹ Justice was already very important¹⁰, and practitioners knew that legal practice had to guide to good and fair¹¹. Spirit is necessary to notice value and a machine that has no spirit can only process data. It is time to notice what was once was seen as too fragile to be worthwhile. It helps to solve practical management issues.¹² This task could once be seen as overwhelming and can now be achieved in a convenient way by mapping what is noticeable and connecting the dots by drawing a graph to learn where to go to find what is missing.

In brief, stop bouncing around machines, start drawing graphs!

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