Exploiting the Relationship of Natural Language and Computer Science: A Novel Theoretical Approach to Fairness

This paper links the challenges of understanding human behavior, including speech, cognition, emotions, fairness, empathy, and cooperation, to the concept of robustness (dynamic adaptability to disturbances in a changing and uncertain environment). This connection will be explored in light of a proposed corollary between natural (human) language and tools from computer science. The author contends that humans come closest to establishing fairness when they can share as accurate an understanding of circumstances and views as possible. To that end, this paper proposes that humans can best develop an accurate understanding with a usage-based natural language model that establishes a reference point of cognitive accuracy paralleling the classes and methods used in the software language of computer science. Such an approach allows for evaluating language for the relative accuracy of its representation of classes and methods using cognitive accuracy as a fitness function. The hypothesis is that natural grammar can be distinguished in a narrow sense by regional, cultural, or local use and more broadly across the human species by scientific, or global use. This, in turn, allows us to design and execute scientific experiments intended to identify human language usage representing an idealized scientific global optimum that can act as a potential reference point for maximizing harmony, cooperation, robustness and the perception of fairness. Further implications and the relationships between the variables and future work will be discussed.

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