我们所知的智力的衰退

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在希腊神话中,古代众神住在奥林匹斯山上(希腊最高的山)。他们拥有非凡的能力,聚集在山峰上,俯视下面的凡人。假设底层的人类非常勇敢或杰出。然而,他们也可以变得像神一样:在希腊人称之为“神化”的过程中,他们会爬上山顶,坐在山顶上。这就是发生在希腊英雄赫拉克勒斯身上的事情。在他生命的尽头,他被带到了奥林波斯山上,和众神一起生活,自由自在,永远不老。
今天,我们许多人似乎相信人类坐在他们的山顶上。我们不认为自己是神,但我们认为自己比其他存在的生物更有才干、更聪明、更有能力。我们中的许多人也相信,如果一个在山脚下的机器要和我们一起站在山顶,它也必须经过神化——不是变得更像神,而是变得更像我们——人类。这意味着对人工智能的纯粹观点。一旦机器达到了人类的智能,这种顶级能力就实现了,它的崛起也就结束了。
但是,从整个人类历史来看,实用主义革命告诉我们,这种假设面临着两个挑战。第一个是那些超越“能力之山”的其他方法,而不是遵循人类走过的独特道路。纯粹的形式只是提升的一种方式;技术进步也揭示了一系列其他令人鼓舞的途径。另一种不同的看法是,在这座山脉的其他山峰上,人类自豪地坐在山顶上。我们中的许多人都被山顶上的景色分散了注意力:我们花时间盯着下面那些不那么智能的机器,或者看着彼此,对自己的能力、技能和能力感到惊奇。但如果我们向上看,而不是向下或往远处看,我们就会看到并认出其他高耸在我们头顶的山脉。
就目前而言,我们可能是现存最智能的“机器”,但机器还可以实现许多其他潜在的设计。想象一个存储所有这些不同组合和迭代的通用仓库:它将是难以想象的大,也许是无限的大。自然选择探索了这个广阔空间的一个小角落,花了很长时间在一个很长的过程中浏览,并确定了人类的设计。然而,用新技术武装起来的人类,现在正在研究其他物种。进化利用时间,今天,我们利用计算能力。很难想象,在未来,我们将如何不跨越各种各样的设计,独特的制造机器的新方法,这些方法将开拓高山和山峰的能力,即使是当今最能干的人类也无法企及。
假设我们设想机器不需要复制我们的智能来获得高度的能力;目前科学界对智力的理解存在的巨大差距,远没有人们通常认为的那么重要。我们不需要解决大脑和思维如何工作的谜题和奥秘,就能制造出能超越我们的机器。假设智能机器和设备不需要复制人类的智能来达到高度胜任和智能。在这种情况下,没有理由认为人类目前的能力代表着未来机器可能达到的极限。然而今天,人们普遍认为人类的智慧勇气是智能机器所能达到的极限。然而,这种情况是不太可能发生的。

英文原文

In Greek mythicism, the ancient gods lived on top of Mount Olympus (the highest mountain in Greece).  Empowered with extraordinary capabilities, they convened on the summit and looked down on the ordinary people underneath.  Suppose the humans at the bottom were exceptionally valiant or distinguished. However, they also could become like gods:  in a process the Greeks called apotheosis, they would climb the mountain and take their seat on the summit.  This is what happened to the Greek hero Hercules, for instance.  At the end of his life, he was brought up to Olympus to live alongside the gods, left to continue unhampered and ageless for all his days.  

Today, many of us seem to believe human beings sit on top of their mountain.  We do not think we are gods, but we consider ourselves more capable, intelligent, competent, and able than any other creature in existence.  Many of us also believe that, if a machine at the bottom of the mountain is to join us at the top, it must go through apotheosis as well – not to become more like a god, but to become more like us – human beings.  This implies the purist view of Artificial intelligence.  Once the machine reaches human intelligence, this top capability is achieved, and its rise is over.  

But as the pragmatist revolution has taught us throughout our human history, there are two challenges with this assumption.  The first is those other ways to climb the “Capability Mountains” than to follow the singular path that human beings have taken.  The purist form is just one way to make the ascent;  technological progress has revealed a range of other encouraging pathways as well.  The different vision is that other tips in this mountain range alongside humans proudly sit at the top.  Many of us have become distracted by the view down from the peak:  we spend our time gazing down at the less intelligent machines below or looking at each other and wondering at our abilities, skills, and capabilities.  But if we looked up, rather than downward or beyond, we would see and recognize other mountains towering above us.  

For the moment, we may be the most intelligent machines in existence, but here are a great many other potential designs that machines could achieve.  Imagine a universal warehouse that stores all those different combinations and iterations:  it would be unimaginably big, perhaps infinitely so.  Natural selection has explored one little corner of this vast space, spent its time browsing in one albeit very long course and settled upon the human design.  However, human beings, armed with new technologies, are now examining others.  Where evolution utilized time, today, we employ computational power.  And it is hard to see how, in the future, we will not trip across various designs, uniquely new ways of building machines, ones that will open up mountains and peaks in capability well beyond the reach of even the most competent human beings alive today.

Suppose we assume that machines do not need to copy our intelligence to be highly competent; the vast gaps in science’s current understanding of intelligence matter far less than is generally assumed.  We do not need to solve the puzzles and mysteries of how the brain and mind work to build machines that can outperform us.  And suppose intelligent machines and devices do not need to replicate human intelligence to be highly competent and intelligent. In that case, there is no reason to think that what human beings are currently able to do represents a limit on what future machines might achieve.  Yet today, this is commonly assumed – that human beings’ intellectual courage is as far as intelligence machines can ever reach.  Nevertheless, it is unlikely that this will be the case.  


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美国AI教育先驱ReadyAI CEO,全球增长顾问公司合伙人,厚仁集团学生领航导师,美国陆军特种部队心理作战司前军官,《论坛报》提名杰出青年公民。
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