LESSON_7: CHANGING THE WAY WE TEACH AND LEARN
"One of the great challenges in the United States and throughhout the world is integrating technology and information to change the way people teach and learn"

"The Cisco Learning Institute (CLI) can provide forward-thinking organizatoons and educators with the innovative tools and expertise they need to meld technology and education."

"The Cisco Learning Institute is dedicated to enhancing the way teachers teach and students learn using technology"

<http://hti.ciscolearning.org>
Lest we take ourselves too seriously, there is also Professor Langdon Winner's satire on "The Automatic Professor Machine", a fictional device which dispenses knowledge as other machines dispense pop. See
<http://www.webct.com/service/ViewContent?contentID=3175969>
In completing this series on teaching machines, let us note that the teaching machine could be elaborated into a giant AI. Suppose we were to take all of the courses taught at a university like MIT and  prepare them as these IMP lectures are being prepared. Subsequent to that, the Q-A sets for each lesson and sub-lesson are prepared. Consider the PageBuilder sub-lesson as an example (Web Site Building 101). There are only so many questions and answers for that sub-lessson. Likewise all other lessons and sub-lessons have a limited number of Q-A sets to exhaust the subject matter. If MIT's "open courseware" which promises to give the public course preparation materials for 2,000 subjects were then repackaged like the IMP course, it would constitute a giant AI. There are more subjects for "universal knowledge", ie the knowledge dispensed by universities, than the 2,000 of MIT but MIT could be the hub for additions to this courseware from all over the world. No human could answer all of the questions for 2,000 subjects. If the opencourseware robot can do so, it constitutes a giant super-human AI. See <http://www.yahoogroups.com/group/shai-now-feasibility-study>

Remember that all items on human intelligence tests are explictly or implictly Q-A sets. A machine with mastery over universal Q-A sets is an impressive AI.But there is a problem concerning access. The world library system is also a giant AI in a sense. Scan it into the computers of the world and we still are not much further ahead when it comes to accessing it as an AI. Thus the SEARCH ENGINE is the key to accessing universal knowledge. Computer scientists categorize files as "data files" and "program files". Schneider (1998) writes in his computing text that "The term file refers to either a data file or a program file" (p. 17). The data files of the giant library system online can be accessed by a search engine program file but that search engine needs some fine tuning. The TAXONOMY OF KNOWLEDGE which thousands of universities have now worked and reworked countless times gives us a clue as to how such a search engine could develop. Current search engines for the world wide web like the Yahoo! search engine "get lost" in the enormity of world knowledge. But when we approach a university to study or learn from the system of higher education, we are able to find our way around. If our questions have to do with medicine we know where to go for an answer. If they are about geology we know where to go for an answer. If they are about computing we know where to go for an answer. Step by step then we could narrow our question down from universal knowledge to computing knowledge to a question about web site construction via the PageBuilder program. This approach would work FROM THE GENERAL TO THE SPECIFIC while current search engines "get lost" because they work FROM THE SPECIFIC TO THE GENERAL.

Over time "OCW-bot" would put flesh on the bare bones of that taxonomy of perhaps 10,000 courses of higher education and universal knowledge. This "Automatic Professor Machine" would interface with the public via an OCW-bot search engine to take us into the correct faculty and department and course and lesson and sub-lesson. THEN we can be assured that we will find the answer to our question. Such an Automatic Professor Machine available on the world wide web would constitute a "reinventing of teaching and learning" as Dean Magnanti from MIT has been quoted in the footer of the email discussion group:

<http://www.yahoogroups.com/group/mit-opencourseware-discussion>

To keep abreast of developments in "Tomorrows Professor" there is also the Stanford Center for Innovations in Learning (SCIL) and its email discussion group:

<http://www.ntlf.com>
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ARTIFICIAL SENSATION

By now you should be reading in Chapter 2, artificial sensation. And one of the best ways you can learn the subject matter is thorough online searching. What URLs would you like to add to this section (or subsequent chapters)? Just post them to the IMP list and they will be considered for the next round of classes. To start with, do you think all knowledge comes directly or indirectly from sensation? What could "extra-sensory perception" really mean, ie how could it make sense? Does cognitive ability come from the senses or do we have this ability by some other means?
Clearly, the "biomimetic" technologies which allow sense-data to interface directly or indirectly with the human brain are being developed with billions of dollars in expenditures worldwide.  The leading militaries of the world cannot afford to be left behind in the race and DARPA, the Defence Advanced Research Projects Agency is no exception. The philosophical issue has to do with what happens when a machine can take in all sense-data better than any human and logically process the sense-data toward objectives better than any human. A military with such a machine would have a very powerful instrument of war. For further information on such developments refer to:

<http://www.yahoogroups.com/group/ai-arms-race>
Other than the natural language approach to SHAI via the teaching machine as above, one might also consider the SENSORY-LOGIC MACHINE. as a biomimetic-psychomimetic device whether connected to a human brain or not:

<http://www.arpa.mil/dso/thrust/biosci/brainmi.htm>
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