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Man-Computer Symbiosis by J.C.R. Licklider, 1960 Presented by Judeth Oden Choi 1/20/15.

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Presentation on theme: "Man-Computer Symbiosis by J.C.R. Licklider, 1960 Presented by Judeth Oden Choi 1/20/15."— Presentation transcript:

1 Man-Computer Symbiosis by J.C.R. Licklider, 1960 Presented by Judeth Oden Choi 1/20/15

2 J.C.R. Licklider, “Lick” or “the Johnny Appleseed of Computing” 1942 PhD in Psychoacoustics 1950 teaching at MIT, SAGE 1957 BBN, started computing group 1960 “Man-Computer Symbiosis” 1962 ARPA – Intergalactic Computer Network 1963 Memo on networking – ARPANET 1965 Libraries of the Future 1968 “The Computer as Communication Device”

3 Time-and-Motion Analysis on Technical Thinking Self-study, recorded his activities during work time 85% of “thinking” time actually dedicated to clerical and mechanical work: “searching, calculating, plotting, transforming, determining the logical or dynamic consequences of a set of assumptions or hypotheses, preparing the way for a decision or an insight” “it seems evident that the cooperative interaction would greatly improve the thinking process.”

4 What if… Every step of a problem didn’t have to be thought through before using a computer… You could think with computers in real-time… Computers could help formulate the problem, not just generate answers…

5 Separating the Functions of Man and Machine Men: Set goals Ask questions Provide motivations Write procedures Set parameters “Fill in the gaps” when a low- probability alternative is returned Or a process has not yet been automated Computers: Carry out procedures Return results Interpolate and extrapolate Transform data Suggest action based on stastical- inference, game theory or decision-theory Make diagnoses Establish relevance Recognize patterns

6 Prerequisites for Man-Computer Symbiosis: 1.Sync speed between man and computer 2.Sufficient memory hardware 3.Memory organized for easy retrieval 4.Develop a computer language closer to human language 5.Natural, easy-to-use input and output equipment

7 1. Speed Mismatch Problem: not economical or efficient for one person to use one large-scale computer Solution: Time-Sharing Systems, allowing many users to access one machine at the same time through Terminals (alternating between users). John McCarthy at MIT was studying this. Eventually Licklider’s work at ARPA would help fund Project MAC at MIT to address time-sharing.

8 2. Memory Hardware Problem: Memory not sufficient for the massive amount of data needed Solution: the goal is not to digitize books, scientific papers, etc. in their entirety, but to index and reference them in a way that the computer can find them. “Indelible Memory” The computer can write once in indelible memory and read it back whenever it is called, or write over it (not delete it) “Published memory” is already structured—this type of memory is “read-only.”

9 3. Memory Organization Problem: Information needs to be retrievable by name and PATTERN Solution: Trie Memory (recently developed by Edward Fredkin)

10 4. Shared Language Problem: Men use goal-oriented language, computers use course-oriented language Solution: Develop a new computing language, Which we can’t really do until computers are improved

11 5. Input and Output Devices Problem: “The department of data processing that seems least advanced, in so far as the requirements of man-computer symbiosis are concerned, is the one that deals with input and output equipment or, as it is seen from the human operator’s point of view, displays and controls. “ Solution: Intimate relationship between man/computer Handwriting recognition Monitors (displayed for mulitple users) Speech production and recognition

12 Impact A move toward real-time interactive computing Eliminating the punch card (and the technician) for a more intimate interaction between user and computer Computer that can respond to changing variables Directly led to further research in time-sharing systems, trie memory structures, information retrieval and networking.

13 Discussion Would we divide the tasks between humans and computers differently? To particular fields, such as education (Xu), media (Eunki) require a different division between automated and human tasks? How do we measure progress toward human-computer symbiosis? Is “intimacy” a good goal? What devices/approaches in use now lean most-heavily toward symbiosis? How does social computing and crowd sourcing fit in? How does “the crowd” compare to the “thinking center”? Are we in fact learning the computer’s language—are we becoming more course-oriented because of our “over-apped” lives? What, if anything, is lost when problems are solved for us by our computers?


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