人工智能的重新定义:超越人工,超越智能

Roger Clarke
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引用次数: 0

摘要

人工智能(旧ai)的最初概念是对人类智能的模拟。事实证明,这是一个欠考虑的探索。它导致太多的研究人员重复地进入太多的死胡同,并体现了对个人、社会和经济的许多威胁。为了增加价值和减少伤害,有必要重新定义该领域。回顾了旧ai的风格、操作定义和重要范例。有人认为,问题的核心在于,人们不恰当地把重点放在实现人类智能的替代上,要么在硅中复制人类智能,要么发明功能上与人类智能相当的东西。相反,人类需要人工制品来传递不同于人类智能的智力价值。通过设计互补的人工智能(CAI),并将其与人类智能相结合,任务变成了增强智能(new-AI)的交付。这些不同的概念可以比人类或人工智能单独更好地满足人类的需要。提议的重新定义更进一步。推理和决策是行动的基础。旧的人工智能倾向于将讨论划分开来,机器人被认为是一个平行的领域,或者充其量是重叠的领域。将智力与物理相结合会产生更广泛的概念,这些概念具有更大的价值:补充人工能力(CAC)和增强能力(AC)。这使研究能够重新定位,以避免死胡同和误入歧途的设计,并提供服务于现实世界需求的技术,并增强人类负责任的创新能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Re-Conception of AI: Beyond Artificial, and Beyond Intelligence
The original conception of artificial intelligence (old-AI) was as a simulation of human intelligence. That has proven to be an ill-judged quest. It has led too many researchers repetitively down too many blind alleys, and embodies many threats to individuals, societies and economies. To increase value and reduce harm, it is necessary to re-conceptualise the field. A review is undertaken of old-AI’s flavours, operational definitions and important exemplars. The heart of the problem is argued to be an inappropriate focus on achieving substitution for human intelligence, either by replicating it in silicon or by inventing something functionally equivalent to it. Humankind instead needs its artefacts to deliver intellectual value different from human intelligence. By devising complementary artefact intelligence (CAI), and combining it with human intelligence, the mission becomes the delivery of augmented intelligence (new-AI). These alternative conceptions can serve the needs of the human race far better than either human or artefact intelligence can alone. The proposed re-conception goes a step further. Inferencing and decision-making lay the foundations for action. Old-AI has tended to compartmentalise discussion, with robotics considered as though it were a parallel or at best overlapping field of endeavour. Combining the intellectual with the physical leads to broader conceptions of far greater value: complementary artefact capability (CAC) and augmented capability (AC). These enable the re-orientation of research to avoid dead-ends and misdirected designs, and deliver techniques that serve real-world needs and amplify humankind’s capacity for responsible innovation.
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