提出数字记忆权，防止AI偏见导致弱声量者被遗忘
The Right to Be Remembered: Preserving Maximally Truthful Digital Memory in the Age of AI
- 主张建立数字记忆权，防范大模型压缩多元声音
- 指出当前AI易放大已有强势叙事，边缘群体易被抹除
- 适合关注AI伦理与集体记忆的读者
随着大语言模型（LLMs）的快速普及，人们越来越依赖其进行信息获取。传统搜索引擎虽受搜索优化、广告和个性化影响，但通常呈现多源排名列表；而LLMs则提供单一且权威的合成回答，可能将多种视角压缩为一种表述，削弱用户比较不同观点的能力。这使少数大模型供应商掌握信息主导权，进而决定何者被记住、何者被忽视。长期来看，这导致数字存在感弱的个体或群体被系统性排除，而已有影响力者被进一步放大，重塑集体记忆。为此，本文提出「数字记忆权」（Right To Be Remembered, RTBR）概念，旨在最小化AI驱动的信息遗漏风险，保障公平对待权利，并确保生成内容尽可能真实。
原文摘要 · Abstract (English)
Since the rapid expansion of large language models (LLMs), people have begun to rely on them for information retrieval. While traditional search engines display ranked lists of sources shaped by search engine optimization (SEO), advertising, and personalization, LLMs typically provide a synthesized response that feels singular and authoritative. While both approaches carry risks of bias and omission, LLMs may amplify the effect by collapsing multiple perspectives into one answer, reducing users ability or inclination to compare alternatives. This concentrates power over information in a few LLM vendors whose systems effectively shape what is remembered and what is overlooked. As a result, certain narratives, individuals or groups, may be disproportionately suppressed, while others are disproportionately elevated. Over time, this creates a new threat: the gradual erasure of those with limited digital presence, and the amplification of those already prominent, reshaping collective memory. To address these concerns, this paper presents a concept of the Right To Be Remembered (RTBR) which encompasses minimizing the risk of AI-driven information omission, embracing the right of fair treatment, while ensuring that the generated content would be maximally truthful.
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