Photo-illustration: IEEE Spectrum; Licklider photo: Philip Preston/The Boston Globe/Getty Images
照片插图：IEEE Spectrum; Licklider照片：Philip Preston / The Boston Globe / Getty Images
The history of AI is often told as the story of machines getting smarter over time. What's lost is the human element in the narrative, how intelligent machines are designed, trained, and powered by human minds and bodies.
In this six-part series, we explore that human history of AI---how innovators, thinkers, workers, and sometimes hucksters have created algorithms that can replicate human thought and behavior (or at least appear to). While it can be exciting to be swept up by the idea of super-intelligent computers that have no need for human input, the true history of smart machines shows that our AI is only as good as we are.
Part 4: Licklider's Cyborg Intelligence
At 10:30pm on 29 October 1969, a graduate student at UCLA
1969年10月29日晚上10:30，加州大学洛杉矶分校的一名研究生sent a two-letter message from an SDS Sigma 7 computer to another machine a few hundred miles away at the Stanford Research Institute in Menlo Park.
It read: "LO."
It read: "LO."
The student had meant to send "LOGIN," but the packet switching network supporting the transmission of the message, the
学生本来打算发送"LOGIN"，但是支持传输消息的分组交换网络，ARPANET, crashed before the whole message could be typed out.
In histories of the internet, this moment is celebrated as ushering in a new age of online communication. What is often forgotten, however, is that underlying the technical infrastructure of the ARPANET was a radical vision for a future of human-machine symbiosis developed by a man named
Licklider, who had a background in psychology, became interested in computers in the late 1950s when working at a small consulting firm. He was interested in how these new machines could amplify humanity's collective intelligence, and began to conduct research into the burgeoning field of AI. When he reviewed the existing literature, he found that programmers aimed to "teach" these machines how to perform pre-existing human activities, such as chess or language translation, with greater aptitude and efficiency than humans.
This conception of machine intelligence didn't sit well with Licklider. The problem, for him, was that the existing paradigm saw humans and machines as being intellectually equivalent beings. Licklider believed that, in fact, humans and machines were fundamentally different in their cognitive capacities and strengths. Humans were good at certain intellectual activities---like being creative and exercising judgment---while computers were good at others, like remembering data and processing it quickly. | "How do you get communications started among totally uncorrelated sapient beings?" ---J.C.R. Licklider
这种机器智能的概念并不适合Licklider。对他而言，问题在于现有范式将人类和机器视为智力等同的存在。 Licklider认为，事实上，人类和机器的认知能力和优势根本不同。人类擅长某些智力活动 - 比如有创造力和运用判断力 - 而计算机擅长于其他人，比如记住数据并快速处理。 | "你如何在完全不相关的智慧生物之间开始沟通？" --- JCR Licklider
Instead of having computers imitate human intellectual activities, Licklider proposed an approach in which humans and machines would collaborate, each making use of their particular advantage. He suggested that this strategy would shift the focus from competition (like computer-versus-human chess matches), and facilitate previously unimaginable forms of intelligent activity.
In a 1960 paper entitled "
在1960年的一篇题为"Man-Machine Symbiosis," Licklider spelled out his idea. "The hope is that in not too many years, human brains and computing machines will be coupled together very tightly, and that the resulting partnership will think as no human brain has ever thought and process data in a way not approached by the information-handling machines we know today." For Licklider, a promising existing example of this symbiosis was a system of computers, networking equipment, and human operators known as the
"Licklider阐述了他的想法。"希望在不是多年的时间里，人类的大脑和计算机器将紧密地结合在一起，并且由此产生的伙伴关系将被视为没有人类大脑曾经想过并处理数据。我们今天所知道的信息处理机器没有采用这种方式。"对于Licklider来说，这种共生的一个有希望的现有例子是计算机，网络设备和人类操作员系统，称为Semi-Automatic Ground Environment (SAGE) that had opened two years earlier to track U.S. airspace.
In 1963, Licklider took a job as a director at the U.S. Department of Defense Advanced Research Projects Agency (then called ARPA, now called
1963年，Licklider在美国国防部高级研究计划局（当时称为ARPA，现称为ARPA）担任董事。DARPA), where he had the opportunity to put some of his ideas into practice. In particular, he was interested in designing and implementing what he first called an "
），他有机会将他的一些想法付诸实践。特别是，他有兴趣设计和实施他所谓的"Intergalactic Computer Network."
The idea came from Licklider's realization that at ARPA, he would need an efficient way to keep large, dispersed teams made up of both humans and machines up to date with changes in programming languages and technical protocols. A communication network connecting these actors across distances was his answer. The challenges in building such a network were akin to a problem contemplated by science fiction writers, he
这个想法来自Licklider意识到，在ARPA，他需要一种有效的方法来保持由人和机器组成的大型，分散的团队，最新的编程语言和技术协议的变化。他的答案是连接这些演员跨越距离的通信网络。建立这样一个网络的挑战类似于科幻作家所设想的问题，他wrote in a memo explaining his concept: "How do you get communications started among totally uncorrelated 'sapient' beings?"
解释他的概念："你如何在完全不相关的'sapient'生物之间开始沟通？" Photo: Philip Preston/The Boston Globe/Getty Images J.C.R. Licklider (top) was a professor of electrical engineering at MIT during his post-ARPA career.
照片：Philip Preston / The Boston Globe / Getty Images JCR Licklider（上）在麻省理工学院的职业生涯后担任麻省理工学院电气工程教授。
Licklider left ARPA before a fully funded program for developing this network began. But over the next five years his initial lofty vision was integral to the development of the ARPANET. And as the ARPANET developed into what we now know as the internet, some began to see how this new networked communication method represented a cooperative interaction between human and technological actors, a symbiont that seemed at times to behave, as the Belgian cyberneticist
Licklider在完全资助开发此网络的计划开始之前就离开了ARPA。但在接下来的五年里，他最初的崇高愿景是ARPANET发展不可或缺的一部分。随着ARPANET发展成我们现在所知的互联网，一些人开始看到这种新的网络通信方法如何代表人类和技术参与者之间的合作互动，这种共生似乎有时表现得像比利时的控制论者Francis Heylighen put it, like a "global brain."
Today, many great leaps forward in machine learning applications are underpinned by collaborative networks of humans and machines. The trucking industry, for example, is increasingly looking for ways to allow human drivers and computational systems use their relative strengths to deliver freight more efficiently. Also in the transportation realm,
今天，机器学习应用程序的许多重大飞跃都得到了人和机器协作网络的支持。例如，卡车运输行业越来越多地寻找方法让人类驾驶员和计算系统利用其相对优势更有效地提供货运。也在运输领域，Uber has developed
has developed a system whereby humans are given high-skill driving tasks, like entering and exiting highways in traffics, and machines are left to manage the hours of routine highway driving.
While there are many other instances of human-machine symbiosis, there is still a cultural tendency to envision machine intelligence as a quality belonging to a single supercomputer with human-level cognitive abilities. But in fact, the
虽然还有许多其他人机共生的例子，但仍然存在一种文化倾向，即将机器智能设想为属于具有人类认知能力的单个超级计算机的质量。但事实上，cyborg future that Licklider envisioned has come to pass: We live in a world of human-machine symbiosis, or what he described as the "living together in intimate association, or even close union, of two dissimilar organisms." Instead of focusing on a fear of being replaced by machines, Licklider's legacy makes us aware of possibilities for collaboration.
This is the fourth installment of a six-part series on the untold history of AI. Part 3 explained why Alan Turing thought AI agents should make mistakes. Come back next Monday for Part 5, which describes a shocking case of algorithmic bias---in the 1980s.