Libraries Of The Future Licklider

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Libraries Of The Future Licklider

Libraries Of The Future Licklider

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Joe Licklider And Harvey Fletcher

The history of artificial intelligence is often told as the story of machines getting smarter over time. What is missing is the human element in the description of how human minds and bodies design, train and operate intelligent machines.

In this six-part series, we explore the human history of artificial intelligence—how innovators, thinkers, workers, and sometimes terrorists have created algorithms that can replicate (or at least appear to) human thought and behavior. While it may be tempting to get carried away with the idea of ​​super-intelligent computers that don’t need human input, the actual history of intelligent machines shows that our AI is only as good as we are.

At 10:30 p.m. on October 29, 1969, at the Stanford Research Institute in Menlo Park, a UCLA graduate student sent a two-letter message from an SDS Sigma 7 computer to another machine hundreds of miles away.

The student intended to send “LOGIN,” but the packet-switched network supporting the transmission of the message, the ARPANET, crashed before the entire message could be typed.

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In the history of the Internet, this moment is celebrated as ushering in a new era of online communication. What is often forgotten, however, is that at the heart of Arpanet’s technological infrastructure was a radical vision of the future of human-machine coexistence developed by a man named JCR. Liquidder.

With a background in psychology, Licklider became interested in computers while working at a small consulting firm in the late 1950s. He became interested in how these new machines could augment humanity’s collective intelligence and began researching the emerging field of AI. When he reviewed the existing literature, he found that programmers aimed to “teach” these machines how to perform existing human tasks, such as chess or language translation, more skillfully and efficiently than humans.

This concept of machine intelligence does not sit well with Licklider. The problem for him was that the existing paradigm viewed humans and machines as intellectual equals. Licklider believed that humans and machines actually differed fundamentally in their cognitive abilities and powers. While humans were good at some intellectual functions — such as creativity and judgment — computers were good at others, such as remembering and processing data quickly.

Libraries Of The Future Licklider

Instead of computers imitating human intellectual activity, Licklider proposed an approach in which humans and machines cooperated, each exploiting their specific strengths. He proposed that this strategy would shift attention away from competition (such as computer vs. human chess games) and enable previously unimaginable types of intellectual activity.

Applications Of Information Networks

Licklider detailed his idea in 1960 in a paper entitled “Man-Machine Symbiosis”. “In a few more years, the expectation is that human minds and computing machines will be so closely related to each other that the resulting partnership is thought to be absent. The human mind has thought and processed data in ways never before possible. Information processing machines as we know them today are close.” For Licklider, a current and promising example of this symbiosis is the Semi-Ground Environment (SAGE), a system of computers, network equipment and human operators that opened two years ago to monitor US airspace.

In 1963, Licklider joined the US Department of Defense (then called ARPA, now called DARPA) as director of the Advanced Research Agency, where he had the opportunity to implement some of his ideas. In particular, he was interested in the design and implementation of what he first called the “Intergalactic Computer Network”.

The idea came from Licklider’s realization that he needed an efficient way at ARPA to keep large, dispersed teams of men and machines abreast of changes in programming languages ​​and technical protocols. His answer was a communication network connecting these players across distances. The challenges of building such a network are similar to a problem that befell science fiction writers, he wrote in a memo explaining his idea: “How do you initiate communication between completely unrelated ‘intelligent’ organisms?”

J.C.R. Licklider (above) was a professor of electrical engineering at MIT during his post-ARPA career. Photo: Philip Preston/The Boston Globe/Getty Images

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Licklider left ARPA before starting a fully funded program to develop this network. But his initial lofty vision was integral to Arpanet’s development for the next five years. As the Arpanet evolved into what we now know as the Internet, some began to see how this new form of networked communication represented a cooperative interaction between humans and technologists, a symbiont sometimes behaving as Belgian cyberneticist Francis Heiligen. put It is like a “global brain”.

Today, many breakthroughs in machine learning applications are based on collaborative networks of humans and machines. The trucking industry, for example, is looking for ways to enable human drivers and computational systems to use their relative strengths to deliver freight more efficiently. In transportation, too, Uber has developed a system that assigns highly skilled driving tasks to humans, such as entering and exiting highways during traffic jams, while leaving machines to manage hours of normal highway travel.

Although there are many other cases of human-machine coexistence, there is still a cultural tendency to imagine machine intelligence as an attribute of a single supercomputer with human-level cognitive abilities. But in fact, the cyborg future that Licklider envisioned has become a reality: We live in a world of human-machine symbiosis, or what he described as “a close relationship or even a close union of two dissimilar beings.” Rather than focusing on the fear of being replaced by machines, Licklider’s legacy makes us aware of the possibilities for collaboration.

Libraries Of The Future Licklider

This is the fourth part 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. The only reason we don’t celebrate a national “Licklider Day” is because people may have the wrong idea about the best way to show their remembrance; Watch “Lick” Meets “Hover Glide.” But Joseph Carl Robert Licklider was the first to write a vision of what we now call the Internet, and this and his other dreams read like a blueprint for our evolving relationship with information technology. This is the man who “eyes sparkled when talking about ideas” and accepted the directorship at ARPA only on the condition that “his research would benefit society as a whole.” It’s a guy. Maybe you already have him. A poster on your wall? You may have read his biography

The Data Delusion

Do you call him “Lick” when you refer to him in conversation? As a concession to Licklider die-hards and those who have never heard of the man, the timeline below is not a chronology of his amazing life and career, though if you haven’t already read it, here it is instead. The story of how long it took Licklider to make his sensational predictions…

Ray Tomlinson sent the first email to himself in 1971, and because he forgot, it was 6 years after Lickleder’s study.

Published by MIT in 1965. Ok… so it might seem easy to send a message from one place to another using computers, read a hot picture.

The same Licklider study described paperless, searchable access to data “using convenient procedure-oriented and field-oriented languages,” and System R’s SEQUEL query language was developed in the mid-1970s, about 10 years after those words were written. Scared.

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It’s a big deal… at least for now… The Internet had a better name when Licklider first described it in a series of memos in 1962, he called it the “Intergalactic Computer Network” Let’s bring it back ! The first network connection was established between the University of California University and Stanford Research Institute.

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