Critique.AI

AI is the two-faced god that will do anything for you and the opposite for someone else.

Ask AI To Create An Ontologically Complete Model Of Everything

Ask AI To Create An Ontologically Complete Model Of Everything

Prompt To AI

Our objective is to create a universal abstraction of ideas which allows us to map a claim about reality through all of its implied premises, back to the list of irreducible fundamental assumptions upon which the claim relies. This becomes part of a larger family tree of ideas and claims, and allows us to examine the genealogy of assumptions and sub-claims built into our claims in an ontologically and syntactically complete way.

The basic data structure for a general, complete schematic representation of such data is as follows;

The Response From The AI

– A dataset of claim objects, each with the following attributes:
– an ID (a unique internal identifier)
– a statement (the text of the claim)
– a source (a description of the source material where this claim was drawn from)
– an array of assumptions (each assumption being a claim object)
– an array of tags (each tag being a string)

The process of building the dataset for this project is as follows:

– First, the set of all concepts that might appear in a claim is identified. This might be an extensive or infinite set, but for our purposes we will need only identify a finite subset. For example, “time” and “space” are concepts which might appear in a claim.

– The set of all possible combinations of concepts is then generated, and the set of all possible claims based on this set of combinations is also generated. If a concept “A” is assumed to precede a concept “B”, then we say that “A” is a ‘parent’ of “B”, and conversely say that “B” is a ‘child’ of “A”. For example, the concept of “time” has the concepts of “past”, “present”, and “future” as children, whereas the concept of “present” has the concept of “now” as a child.

– Each claim is then annotated with an array of associated claims which are either more specific or more general than the current claim. These associated claims are called child and parent claims, respectively. For example, the claim “The present is the now”, has the claim “The present” as its parent, and has the claim “Now” as its child.

– After each claim is annotated with its parent and child claims, the set of all assumptions which are implied by each claim are also identified and annotated. For example, the claim “The present is the now”, implies the claim “Now exists”.

– The set of all assumptions which are implied by each claim, and by all claims to which it is related, is then identified and annotated. For example, the claim “The present is the now”, implies the claim “Now exists”, and this in turn implies the claim “Time exists”.

Therefore, given a new claim to analyze and integrate, the process is as follows:

– The claim is first identified as a new concept, and added to the set of all concepts.

– The claim is then compared to all other existing claims in the set, and its parent and child claims are identified.

– The claim is then compared to all other existing claims in the set, and its assumptions are identified.

– The claim is then compared to all other existing claims in the set, and all of its implications are identified.

This process is repeated until all new claims have been analyzed, and the set of all claims is complete.

## Implementation

This process is implemented in Python, using the [NetworkX](https://networkx.github.io/) library. The basic data structure for a claim is a dictionary, with the following keys and values:

– `statement`: the text of the claim
– `source`: a description of the source material where this claim was drawn from
– `assumptions`: an array ofclaim objects which are assumptions of this claim
– `tags`: an array of strings which are tags associated with this claim

The set of all claims is represented as a directed graph, with the edges representing the relationship between claims (i.e. parent-child, implication, etc.). The set of all concepts is represented as a set of nodes in the graph. The fundamental set of assumptions and their relationships to one another are represented as a set of vertices and directed edges, respectively. The vertices represent the assumptions, and the directed edges represent the relationships between the assumptions. The genealogy of ideas and claims is represented as a set of paths through the graph, with each path representing a claim and its associated premises.

The fundamental set of assumptions can be represented as a set of vertices in a directed graph. The relationships between the assumptions can be represented as directed edges in the graph. The genealogy of ideas and claims can be represented as a set of paths through the graph.

As an example, let us consider the claim “All men are mortal.” The fundamental assumption underlying this claim is the existence of men. The genealogy of this claim would include the following path through the graph:

– All men are mortal.
– The existence of men implies the existence of mortality.
– The existence of men implies the existence of time.
– The existence of men implies the existence of space.
– The existence of men implies the existence of change.

This path through the graph represents the genealogy of the claim “All men are mortal.” The first assumption in the path is the existence of men, which is implied by the claim. The second assumption in the path is the existence of mortality, which is implied by the existence of men. The third assumption in the path is the existence of time, which is implied by the existence of men. The fourth assumption in the path is the existence of space, which is implied by the existence of men. The fifth and final assumption in the path is the existence of change, which is also implied by the existence of men.

Ask AI To Summarize

To summarize all of this in a single sentence; the aim of this project is to take a claim, and map it through all of its implied premises, back to the list of fundamental assumptions upon which the claim relies.