We should collectively migrate to a model in which personal data is managed in a network based model in which all parties (individuals, organisations, things) are seen as nodes on the network. Data flows to and from network nodes via managed permissions. This approach can scale to the vast and ever-growing needs of modern data exchange for AI and other purposes.
Machine Learning, now popularly called AI, offers great promise for a wide variety of applications, however it also has a number of serious problems, many of them less severe than the total extinction of humanity. Frequent factual errors, which have been called “hallucinations”, might be more accurately described as “confabulations”.
We have just finished a fantastic Mydata 2023 conference, all in all a great event.
Data spaces are an emerging hot topic, this post illustrates the good fit between the design and running of data spaces, and the JLINC protocol.
This paper sets out a vision for what could become a sustainable set of processes around the sourcing, management, and use of personal data. Our context for doing so is that the current model for personal data management on The Internet is badly broken and has architectural limitations that are largely un-resolvable...
JLINC Technical Philosophy provides a concise background rooted in the lineage of ideas that led up to the JLINC protocol, and explains how it achieves a new paradigm for data exchange on the internet.
In short, JLINC updates the pre-Internet, static “notice and consent” paradigm, with a dynamic, state-of-the-art protocol. At the end of the day, JLINC’s permissioned data protocol harnesses the energy of engaged users to drive new markets.
The JLINC Protocol is the interoperable solution for transparent crypto-contracts – cryptographically signed 'data exchange contracts'.
