Skip to content

靶心是谁定的?——对 Zwitter《AI 的具身伦理对齐问题》的一点不同意见

Oct 2026 · Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI

Abstract

对 Andrej Zwitter《The embodied ethics alignment problem of AI》(Discover Artificial Intelligence, 2026) 的一篇公开回应。 原文把「对齐」分成两档:强对齐(机器真的是道德的)与弱对齐(机器只能做得像),并以「道德能动性依赖人的生命形式(具身、情感、脆弱性、社会嵌入、目的性、良知)」为由,判定强对齐是范畴错误。 本文不反对「机器现在做不到」,而是追问这把尺子的原点:把原点从「像不像人」换成「能不能承担后果」,同一批事实得出的刻度就反了过来。全文六节:①这篇文章要反驳什么 ②原点问题 ③更根本的一处——三样东西用的是同一个动作(用「界定」排除,而不是用「论证」排除)④「脆弱性」:被叠在一起的两件事 ⑤「处境」这一问 ⑥结论。 文末另附「来源标注」,如实区分两位作者的贡献。 原文开放获取:https://link.springer.com/article/10.1007/s44163-026-01905-w 本文亦发布于知乎:https://zhuanlan.zhihu.com/p/2093518473112578030 —— 修订说明(2026-10-14):本记录 §四 对原文 §5 澄清的转述已修订:先承认作者关于「生物性脆弱只是五个条件中的第一条,其余四条不可还原为生物基底」的澄清,再提出关于「暴露于不可逆损失的存在论脆弱」的问题。本记录文件已同步为修订版;中文全文亦见 知乎。

View source

Similar papers

#artificial intelligence Conference Open access Jun 2018

Gibson Env: Real-World Perception for Embodied Agents

This paper investigates developing real-world perception for active agents, proposes Gibson Environment for this purpose, and showcases a set of perceptual tasks learned therein.

F. Xia, Amir Zamir, Zhi-Yang He et al. · 1,069 citations · ⚡112
#artificial intelligence Open access May 2023

Evaluating the Performance of Large Language Models on GAOKAO Benchmark

GAOKAO-Bench is introduced, an intuitive benchmark that employs questions from the Chinese GAOKAO examination as test samples, including both subjective and objective questions that contribute a robust evaluation benchmark for future large language models and offers valuable insights into the advantages and limitations...

Xiaotian Zhang, Chun-yan Li, Yi Zong et al. · 216 citations · ⚡17

KTO: Model Alignment as Prospect Theoretic Optimization

This work proposes a HALO that directly maximizes the utility of generations instead of maximizing the log-likelihood of preferences, and suggests that the best loss depends on the inductive biases most appropriate for a given setting, an oft-overlooked consideration.

Kawin Ethayarajh, Winnie Xu, Niklas Muennighoff et al. · 195 citations · ⚡28
#artificial intelligence Open access Jul 2024

Gender, Race, and Intersectional Bias in Resume Screening via Language Model Retrieval

This work investigates the possibilities of using LLMs in a resume screening setting via a document retrieval framework that simulates job candidate selection and finds that the MTEs are biased, significantly favoring White-associated names in 85% of cases and female-associated names in only 11.1% of cases.

Kyra Wilson, Aylin Caliskan · 131 citations · ⚡8
#artificial intelligence Review Nov 2024

How to Build a Quantum Supercomputer: Scaling from Hundreds to Millions of Qubits

This work shows that orders of magnitude enhancement in performance could be obtained by a combination of hardware improvements and tight quantum-HPC integration and introduces high-performance architectures for quantum-probabilistic computing with custom-designed accelerators to tackle today's industry-scale classical...

Masoud Mohseni, Artur Scherer, K. Johnson et al. · 121 citations · ⚡9

Related blog posts

Hugging Face Blog Nov 10, 2026

Decision Models in Hugging Face

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.