论文标题

在包含的人工通用智能中检测合成现象学

Detecting Synthetic Phenomenology in a Contained Artificial General Intelligence

论文作者

Pittman, Jason M., Hanks, Ashlyn

论文摘要

机器中的人类智力是一个有争议的主题。人造一般情报是否应该追求人工通用情报的创造。同样,研究人员还根据人类是否可以创造对方的派系保持一致。出于我们的目的,我们假设人类可以而且会这样做。因此,有必要以安全且可信赖的方式考虑如何进行操作 - 输入拳击或遏制的想法。作为这种思想的一部分,我们想知道如何在任何潜在的遏制系统施加的操作限制下如何检测到现象学。因此,这项工作通过Qualia进行了现有现象学测量的分析,并将这些思想扩展到包含的人工通用智能的背景下。

Human-like intelligence in a machine is a contentious subject. Whether mankind should or should not pursue the creation of artificial general intelligence is hotly debated. As well, researchers have aligned in opposing factions according to whether mankind can create it. For our purposes, we assume mankind can and will do so. Thus, it becomes necessary to contemplate how to do so in a safe and trusted manner -- enter the idea of boxing or containment. As part of such thinking, we wonder how a phenomenology might be detected given the operational constraints imposed by any potential containment system. Accordingly, this work provides an analysis of existing measures of phenomenology through qualia and extends those ideas into the context of a contained artificial general intelligence.

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