6th Summary

Introduction to information technology

April 23th & 25th.
- global school of MEDIA , Class B.






People often interact with media technologies as though the technologies were people.

related ideas
- Clifford and Nash, “the media equation”
- Freud, transference
: see also Sherry Turkle on computers as “second selves” and as “evocative objects”
- surrealists, “automatic writing” (recall Tristan Tzara’s “recipe”)
- Mannheim/Schutz/Garfinkel, the “documentary method”






related points: ethics

related points: aesthetics & teleology

related points: aesthetics & teleology

related points: design




history of HCI (from a tool-building perspective)

history of HCI as tools: people

history of HCI as tools: systems

history of HCI as tools: funding







where does HCI meet AI?
basic design question: should the computer act like a person?
agents versus “direct manipulation”
e.g., Ben Schneiderman versus Pattie Maes (sigchi, 1997)
even “direct-manipulation” interfaces are based on a “conversation” metaphor: the computer responds immediately to each action or command from the “user”
but, there are (at least) two models of conversation
information/intention transmission
inspirations for ai: e.g., Paul Grice, pragmatics
co-construction of meaning
ethnomethodology: e.g., Harvey Sacks, conversation analysis
Boring? ok.. let’s watch some movie related to HCI generally.
hci lesson from “Sleeper”
1) Reliability
2) Personalization
3) if it isn’t broken, don’t fix it
4) intuitive UI design





Cf) Johnstone’s “algorithm”






ethnomethodology: a definition

ethnomethodology
- Ethnomethodology differs from other sociological perspectives in one very important respect:
Ethnomethodologists assume that social order is illusory. They believe that social life merely appears to be orderly; in reality it is potentially chaotic. For them social order is constructed in the minds of social actors as society confronts the individual as a series of sense impressions and experiences which she or he must somehow organise into a coherent pattern.
Simon Poore, http://www.hewett.norfolk.sch.uk/curric/soc/ethno/intro.htm



ref) Lucy Suchman











My Opinion J

: This Week, We talk about HCI.
HCI is human-computer interaction.
Through Interaction between human and computer,
We got many thing. For example, We got information.


First, I think HCI is one thing about chemistry.
In Chemistry, HCI is ‘염산’.
I learned about ‘염산’ in high school, so I think HCI is ‘염산’.
But I know, HCI is ‘Human-Computer Interaction’ now.


Actually, I have many think about HCI,
But I don’t concentrate class very well. Because we have ‘mid-exam’.


Next week, We talk about ‘Computer-aid’.
Aid?
I don’t know anything about ‘aid’.

So I have many expectation. See you next class~

5th Summary

Introduction to information technology
- April 11th. (Class 나)



AI (Artificial Intelligence) : The Founding document.


Who was Turing? : Founder of computer science,
artificial intelligence, mathematician, philosopher, codebreaker, and a gay man.


Alan Turing. (1912-1954)

1912 (23 June): Birth, Paddington, London
1926-31: Sherborne School
1931-34: Undergraduate at King's College, Cambridge University
1932-35: Quantum mechanics, probability, logic
1935: Elected fellow of King's College, Cambridge
1936: The Turing machine, computability, universal machine
1936-38: Princeton University. Ph.D. Logic, algebra, number theory
1938-39: Return to Cambridge. Introduced to German Enigma cipher machine
1939-40: The Bombe, machine for Enigma decryption
1939-42: Breaking of U-boat Enigma, saving battle of the Atlantic
1943-45: Chief Anglo-American crypto consultant. Electronic work.
1945: National Physical Laboratory, London
1946: Computer and software design leading the world.
1947-48: Programming, neural nets, and artificial intelligence
1948: Manchester University
1949: First serious mathematical use of a computer
1950: The Turing Test for machine intelligence
1951: Elected FRS. Non-linear theory of biological growth
1952: Arrested as a homosexual, loss of security clearance
1953-54: Unfinished work in biology and physics
1954 (7 June): Death (suicide) by cyanide poisoning, Wilmslow, Cheshire.





cf 1. Turing’s “imitation game”
cf 2. Walker/Sack/Walker “online Caroline”






☻ Artificial Intelligence: a definition

“... artificial intelligence [AI] is the science of making machines do things
that would require intelligence [as] if done by [humans]” - Marvin Minsky, 1963


☻ Artificial Intelligence: research areas

Knowledge Representation
Programming Languages
Natural Language (e.g., Story) Understanding
Speech Understanding
Vision
Robotics
Machine Learning
Planning
etc.






- planning as a technical problem

We saw Tower of Hanoi.




- story generation as planning

James Meehan, "The Metanovel: Writing Stories by Computer", Ph.D. diss., Yale University, 1976.




- problems with story generation: missing common sense

Examples of Tale-spin’s missing common sense (w/real human) (from Meehan, 1976)
Answers to questions can take more than one form.
Don’t always take answers literally.
You can notice things without being told about them.
Stories aren’t really stories if they don’t have a central problem.
Sometimes enough is enough.
Schizophrenia can be dis-functional.




- story understanding as a plan recognition problem

- story understanding as a plan recognition

demo: micro-sam
Richard Cullingford,
“Script application: computer understanding of newspaper stories,”
Ph.D. diss., Yale University, 1977.



- question answering as a problem
ELIZA as a “solution”



- Institute of Artificial Art Amsterdam

Huge Harry
epilogue A.I. Neo



















J My Opinion

This Week,
We talk about AI (Artificial Intelligence).


We saw Alan Turing’s Game.
I think it is very interesting and surprise game.
I want to play that game.
It is very interesting!

And Turing’s inventions are very wonderful.
I think, He may genius.
His life is “a life full of ups and downs.”





And, We talk about many thing.
But I don’t remember many thing because I’m very busy. (mid-exam… next week ㅠ_ㅠ)

I’m going to study. I’m sorry that summary is very shabby.

See you next Friday (april 18th).

4th Summary

Introduction to information technology (4/2)
Class – 나




KEY POINT
: New media technologies usually reinforce existing social networks or even work to isolate people.
Example : 고립된 사람들, 방안에서 Key board 만 두드리는 사람들 etc.
: (But) When new media technologies facilitate new social networks, they simultaneously challenge existing social, political and economic relationships.





OUT LINE
: Social Networks as Science ; field – (cf). 간 학제 / 학제 간
Technology
Popular Culture
Art
Cf. network : know “each other”


☞Social Networks as science : field
: Social Network analysis is and interdisciplinary social science, but has been of especial concern to sociologists;

: Recently, physicists and mathematicians have made large contributions to understanding networks in general (as graphs) and thus contributed to and understanding of social networks too.




○Social Networks as science : definition
- social actors : people
- the links : relationships

; important consequences
; opportunities
; potential constraints on their behavior
; the patterning of links among actors
; uncovering the antecedents and consequences of recurrent patterns




○Social Networks as science : history
: J.L. Moreno (1934) Friendship choices between 4th grade boys (triangles) and girls (circles)
: Stanley Milgram (1967) “The Small World Problem,” Psychology Today
Milgram sent 60 letters to various recruits in Wichita, Kansas who were asked to forward the letter to the wife of a divinity student living at a specified location in Cambridge, Massachusetts. The participants could only pass the letters (by hand) to personal acquaintances who they thought might be able to reach the target - whether directly or via a "friend of a friend".
: “six-degrees of separation” (*degree : step)
: Mark Granovetter, “The Strength of Weak Ties”
Sometimes acquaintances are more valuable than friends (e.g., when one is looking for a job).
- weak relationship > strong relationship




○Social Networks as science : Social Captipal




○Social networks as science: bowling alone




☞ Social networks as technology
: email, newsgroups, and weblogs
: in the design of the arpanet (the forerunner to the internet) email was an afterthought!









★Social Network as sicence : Equivalence
: Centrality
: Bridges (to the another network)
: Social Capital
: Bowling alone






Introduction to information technology (4/4)
Class – 나




☞ Social Networks as popular culture
: six-degrees of Kevin Bacon
: Bacon Number ; definition
Cf. Kevin bacon has bacon number of 0.

♬ Oracle of bacon (; oracle : 예언자)
Cf. MOVIE “Matrix”




0. “Fixing” the networks : e.g., Google hacking try the query “miserable failure” at google.com

Vizster
1. Dynamin / visualization
Cf. Danah (she major “political Science”.)




☞ Social Networks as art
0. Ben discore’s Friendster Map : well, I can do that using cyworld.


*Visualizing (social) Networks
Map : visualization


*artificial intelligence













My Opinion J

This Week, We talk about “NETWORK”.
It is very interesting topic, so I really concentrated this class.
But I don’t understand anything about “NETWORK”, because It is interesting and difficult topic.

April 9th, We have no class, because April 9th is election day.
So I don’t go to the school.
And I will reading a book.
(About ‘Introduction to information technology’ Equal understand media.)

Mid exam is coming up. (already next week i_i)
I’m so tired, so I write my opinion a little. Sorry.

See You Friday~