用数学模型量化边缘群体的表达压力，提升AI与人机交互的包容性
Gaze-Aware AI: Mathematical modeling of epistemic experience of the Marginalized for Human-Computer Interaction & AI Systems
- 引入注视压力指数（GPI）-Diff，量化边缘群体表达受压抑程度
- 提出可训练大语言模型的数学公式，促进更具包容性的AI设计
- 结合神经可塑性理论，倡导以人为本的无障碍人机交互
人工智能的普及为社会心理空间拓展提供了契机。心理空间指容纳多元人际互动的能力，是脆弱性、真实性与亲社会行为的基础，进而促进社会和谐。本文尝试量化人类无意识中为契合主流文化规范而压抑真实自我表达的心理机制。通过后现代哲学与心理学概念，分析若干经匿名处理的Reddit帖子，探讨不同边缘化及交叉身份群体所面临的‘凝视’影响。提出‘注视压力指数（GPI）-Diff’复合度量方法，用于建模两类对话空间之间的关系。该模型导出一个可用于训练大型语言模型（LLMs）的方程，如Chat-GPT等产品的工作机制。基于此，提出以神经可塑性为基础的包容性人机交互原则，强调终身大脑重塑能力在构建公正技术系统中的作用。
原文摘要 · Abstract (English)
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.
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