Gaze-Aware AI: Mathematical modeling of epistemic experience of the Marginalized for Human-Computer Interaction & AI Systems

TL;DR

This paper introduces a mathematical model to quantify gaze-related social pressures on marginalized groups, aiming to improve inclusive human-computer interaction and AI systems by understanding subconscious conditioning.

Contribution

It presents a novel Gaze Pressure Index (GPI)-Diff Composite Metric and an equation to train Large Language Models for more inclusive AI and HCI.

Findings

Development of GPI-Diff Composite Metric for gaze analysis

Mathematical formulation to incorporate gaze effects into AI training

Support for inclusive HCI principles based on neuroplasticity

Abstract

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.