This extends the concepts originally discussed in Data, the Ballerina to discuss how narratives can be constructed from datasets. This work is inteded to capture the essence of “accurate description” – to remove narrative bias in the pursuit of objective truth. Which in turn advances my goal of discovering the world as it exists.

One need only read a book such as “Narrative Warfare” to discover that many writing narratives in our society have abandoned the very conception of truth in justifcation of their manipulative behavior. Unfortunately, this troubling attitude has permeated society: from purported journalists to public relations to government. However, the manipulation of narrative in the pursuit of power ends in disaster. Much like a schizophrenic, unable to encounter reality, our nation has destroyed itself through repeated folly and insanity.

However, we can combat this illness by developing new techniques to engage with reality.

Data-driven narratives use innovations in effective semantics to do this by aligning the structure of the data (eg, relationships between facts) with the structure of a narrative space. This approach to mapping spaces onto spaces is a primary objective in effective semantics, creating the narrative structures which best represent a dataset.

This projection into narrative space is accomplished by mapping where datums are mapped to fact recitations, while relationships between datums use narrative words and connective language. By having higher order types within the semantics attached to the dataset, we can allow for words which represent higher order patterns to occur in our narratives. The narrative space can be tuned to particular identities.

One can view the narrative space as an effective type they’re we’re creating to match the diagrammatic structure of our dataset.

In this approach, meaning arises from the latent data structure within our dataset – and how we interpret that when expressed in typical language. This allows for truthful narratives to emerge, which may not match the biases or manipulations of the author. While this is ananthema to the paid manipulators mentioned before, by converging around true narratives, we stabilize society in two ways: 1. by allowing unaligned groups to align around the truth; 2. by preventing repeated failures, such as the Afghanistan, Iraq, and Ukraine wars which all damaged the US through lies about events.

This approach further allows for combating misinformation and manipulation in two ways: 1. by allowing for a programmatic way to compare narratives to explore their omissions, errors, biases, etc; 2. by allowing for automated systems to comprehend reality in a structured way and hence response to algorithmic manipulations. We believe that both technologies are important, given that not only the human sources of misiformation mentioned above but algorithmic ones (eg, feed manipulations) are becoming increasingly prominent.

While those who use narrative in the pursuit of manipulations leading to madness and doom are frequently sponsored by the existing power structure (eg, journalists, public relations, “narrative warriors” in government) there are emerging signs that technology can respond to their techniques effectively by sharing the truth.

“The truth is like a lion; you don’t have to defend it. Let it loose; it will defend itself.”

― Augustine of Hippo