The field of AI is evolving quickly and the specific tools used to interact with consumer data will evolve. The goal of this work is to establish a global system of cooperation that enables a user to maintain an Augmented Personal Repository, enriching it over time with many multimodal sources of data, offering consent management, portability into any local or distributed environment on a phone, watch, computer, or any other device of the consumer’s choosing and ensuring privacy and security. Once the Augmented Personal Repository is available, the user can then leverage it for any interaction with other systems.
Kisop aims to enable a Distributed Architecture that enables Privacy, Consumer Choice and Portability in the age of AI. A consumer should be able to know the answer to these questions:
- “Who controls the tools I depend on?”
- “What are my choices for local, on premise and on-device implementations?”
- “What are my choices for Cloud Implementations that guarantee certain privacy, security and portability conditions?” We refer to these as “KISOP-compatible”.
- “Is all of my data fully portable?”
- “Exactly what are the Privacy measures I am being offered when it comes to copies of my data?”
The goal of a “distributed architecture” can be achieved through many solutions. We do not intend to imply only one solution is best to meet the aims.
The system’s architecture facilitates learning from highly distributed data and can be fine-tuned on curated datasets to understand nuanced variation.