Technology is simple, people are difficult. People create pieces of knowledge, like this one: Coronavirus disease (COVID-19) advice for the public, which also has a timing aspect to it. Original pieces of knowledge immediately start spreading and transforming on the way. Knowledge is there to be spread, but there are different ways of doing it. In a search of a piece of spotlight, people sometimes para-phrase the original piece of information, picking out pieces, adding own views and passing it on. This leads to a plethora of information pieces out there, with no possibility of backtracking to the original knowledge object.
What’s the mechanism of retrieving the ground truth, that initial knowledge object provided by empirical evidence? An answer to this is linked data. Instead of copying and passing on a piece of knowledge we send a reference to it. When we only share pointers to knowledge objects we can choose to always get the latest. The knowledge object can by itself evolve as well but keep track of the changes and detect if anyone has tempered with it.
Pointers to pieces of data and knowledge are not only shortcuts but may have metadata that can be used when retrieving exactly the piece one is interested in. The metadata is also useful when adding a new piece of knowledge and linking it to already existing pieces of knowledge.
To complicate it further, knowledge objects get combined together and new pieces of knowledge get inferred. We need to make sure we can back-track this chains of inferencing to original facts and ground truth, in line with what Hans Rosling said in Factfulness. A tiny tweak in a piece of information along the chain of reasoning may lead to an incorrect decision in the end of the reasoning chain.
The tiny tweaks may be intentional and unintentional. A minor variation of the ground truth or an error in the reasoning chain may lead to wrong decisions being taken at the end of the reasoning process. When this process concerns life and well-being of people, business-critical decision-making, or societal challenges, it needs to adhere to certain principles:
- Data should not be copied. Share pointers to data, not the copy.
- Traceability and explainability in decision-making needs to be in place.
- In search for an optimal decision, don’t experiment on a live system without predefined boundaries.
- Mechanisms for resolving conflicts should be in place.
- Mechanisms for detecting tweaks in data should be in place.
- Mechanisms for reversing decisions should be in place.