Since the Beginning, humankind has sought something for nothing. Data, being both free and priceless satisfies that need. Every action we take, each decision we make contributes to a rapidly expanding data universe.
In fact the data itself is generating its own data. We are simply cogs in a perpetual data machine. The smartest organizations have discovered the secrets of data alchemy, turning raw data into competitive advantage, social good and better cat videos.
We came up with the concept of such a machine around which to structure conversations around how personal data is used and potentially abused by businesses, organizations and those with malicious intent. We believe that as the body of personal data being analyzed grows there is a need for such considerations
Design Criteria
- Transparency as a default for input and output data
- Symmetry of the individual and the organization
- Remuneration model built into the system infrastructure
- Refinery, the managed processes for adding value to data
- Levels of value that can be output from the Refinery
- Outputs which are data products or product components
- Agent as a consumer of the Outputs to deliver end-user value
- Governance, an automated means of self-policing data usage
- Up-cycling, where each data output spawns an improved cycle
[Edited May 2020] Data is created by consumers, harvested by companies providing free or paid-for services, today the permission is sketchy, The data goes into various refineries… the actual paths and ownership of refineries is getting more complex by the data and downstream data transactions are largely untracked which has created the problems of Privacy we know today. Finally a system of Agents make use of that data and the processed data is fed back into the other stage systems. Whether it is provenance, privacy of agency, these flows of data need to be governed and re-commercialized.
By Dr Andreas Weigend & Gam Dias for Predictive Analytics World 2015