Gaze-Aware AI: Mathematical modeling of epistemic experience of the Marginalized for Human-Computer Interaction & AI Systems
This addresses the issue of societal inclusivity in AI systems for marginalized communities, but it appears incremental as it builds on existing concepts from philosophy and psychology.
The paper tackles the problem of quantifying how marginalized groups subconsciously modify self-expression due to dominant cultural norms, resulting in a mathematical Gaze Pressure Index (GPI)-Diff Composite Metric and an equation for training LLMs to promote inclusive HCI.
The proliferation of artificial intelligence provides an opportunity to create psychological spaciousness in society. Spaciousness is defined as the ability to hold diverse interpersonal interactions and forms the basis for vulnerability that leads to authenticity that leads to prosocial behaviors and thus to societal harmony. This paper demonstrates an attempt to quantify, the human conditioning to subconsciously modify authentic self-expression to fit the norms of the dominant culture. Gaze is explored across various marginalized and intersectional groups, using concepts from postmodern philosophy and psychology. The effects of gaze are studied through analyzing a few redacted Reddit posts, only to be discussed in discourse and not endorsement. A mathematical formulation for the Gaze Pressure Index (GPI)-Diff Composite Metric is presented to model the analysis of two sets of conversational spaces in relation to one another. The outcome includes an equation to train Large Language Models (LLMs) - the working mechanism of AI products such as Chat-GPT; and an argument for affirming and inclusive HCI, based on the equation, is presented. The argument is supported by a few principles of Neuro-plasticity, The brain's lifelong capacity to rewire.