Class for 08.04.23~25
This class's key point is that has implications for the aesthetic, ethics and evaluation of human-computer interaction. Second, history of HCI from a tools perspective. And conversational models of the interface: the intersection of AI and HCI . And also, question for today: what problem does Weizenbaum’s ELIZA system address or solve? And then, the answer of AI.
And, the answer of Ethnomethodology. Finally, People often interact with media technologies as though the technologies were people.
Here is related ideas. One is clifford and Nash, “the media equation” Two, Freud, transference
–see also Sherry Turkle on computers as “second selves” and as “evocative objects”
Three, surrealists, “automatic writing” (recall Tristan Tzara’s “recipe”)
Finally, Mannheim/Schutz/Garfinkel, the “documentary method”
If we view objects, technologies and natural phenomenon as if they do, in fact, have goals and intentions, then we will design like an artificial intelligence researcher.
On the other hand, if we view objects, technologies and natural phenomenon as if the just look like they have goals and intentions, then we will design like a tool builder for human “users” or “operators” of our tools.
And we talked about HCI.
History of HCI as tools: people, tools, funding. And then, we talked about where does HCI meet AI. Basic design question: should the computer act like a person? Answer is agents versus “direct manipulation” e.g., Ben Schneiderman versus Pattie Maes (sigchi, 1997)
Question for today is what problem does Weizenbaum’s ELIZA system address or solve?
The artificial intelligence answer: it does (or does not) behave like a human and is therefore successful (or not successful)
The ethnomethodology answer: it is taken to be a like a person in a conversation and thus simply works like most other technologies in a social situation.
And next, we talked about Johnstone’s “algorithm”
•If the last two answers were “No,” then answer “Yes.”
•Else, if more than 20 total answers, then answer “Yes.”
•Else, if the question ends in vowel, then answer “No.”
•Else, if question ends in “Y,” then answer “Maybe.”
•Else, answer “Yes.”
And we thought 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.
*comments*
HCI is amazing~. Surprise~
I'am interested in Johnstone’s “algorithm” Very interesting.
*
2008년 4월 25일 금요일
2008년 4월 12일 토요일
Class for 04.11
Class for 04.11
We have taked together about Alan Turing who founder of computer science, artificial intelligence, mathematician, philosopher, codebreaker, and a gay man.
Turing studied interesting game, “imitation game” (1 of 3) The new form of the problem can be described in terms of a game which we call the ‘imitation game.’
It is played with three people, a man, a woman, and an interrogator who may be of either sex.
The interrogator stays in a room apart from the other two. The object of the game for the interrogator is to determine which of the other two is the man and which is the woman.
It is [the man's] object in the game to try and cause [the interrogator] to make the wrong identification. The object of the game for [the woman] is to help the interrogator.
We now ask the question, ‘What will happen when a machine takes the part of [the man] in this game?’ Will the interrogator decide wrongly as often when the game is played like this as he does when the game is played between a man and a woman? These questions replace our original [question], ‘Can machines think?’
And we though artificial intelligence [AI] the science of making machines do things that would require intelligence as if done by humans. We also talked film AI.
We talked about Hanoi. GPS is what is known in AI as a “planner.” (not global positioning system! it is a computer program for theorems proof, geometric problems and chess playing.
To work, GPS required that a full and accurate model of the “state of the world” (i.e., insofar as one can even talk of a “world” of logic or cryptoarthimetic, two of the domains in which GPS solved problems) be encoded and then updated after any action was taken (e.g., after a step was added to the proof of a theorem).
*comments
I interested in Alan Turing's game. Surpise!
It is very interesting and that is connected AI.
*
We have taked together about Alan Turing who founder of computer science, artificial intelligence, mathematician, philosopher, codebreaker, and a gay man.
Turing studied interesting game, “imitation game” (1 of 3) The new form of the problem can be described in terms of a game which we call the ‘imitation game.’
It is played with three people, a man, a woman, and an interrogator who may be of either sex.
The interrogator stays in a room apart from the other two. The object of the game for the interrogator is to determine which of the other two is the man and which is the woman.
It is [the man's] object in the game to try and cause [the interrogator] to make the wrong identification. The object of the game for [the woman] is to help the interrogator.
We now ask the question, ‘What will happen when a machine takes the part of [the man] in this game?’ Will the interrogator decide wrongly as often when the game is played like this as he does when the game is played between a man and a woman? These questions replace our original [question], ‘Can machines think?’
And we though artificial intelligence [AI] the science of making machines do things that would require intelligence as if done by humans. We also talked film AI.
We talked about Hanoi. GPS is what is known in AI as a “planner.” (not global positioning system! it is a computer program for theorems proof, geometric problems and chess playing.
To work, GPS required that a full and accurate model of the “state of the world” (i.e., insofar as one can even talk of a “world” of logic or cryptoarthimetic, two of the domains in which GPS solved problems) be encoded and then updated after any action was taken (e.g., after a step was added to the proof of a theorem).
*comments
I interested in Alan Turing's game. Surpise!
It is very interesting and that is connected AI.
*
2008년 4월 6일 일요일
Class for 08.04.02~04
Class for 08.04.02
Professor said key points so far. First, when technologies connect or separate people, they become media. Second, tembody social, political, cultural, economic and philosophical ideas and relationships. Third, when a medium is new, it is often used to simulate old media. Fourth, new media do not replace old media, they displace them. Last, people make media and then media make people.
And next, he said today's key points. One is that New media technologies usually reinforce existing social networks or even work to isolate people. For example is e-mail and messenger. Because e-mail and messenger are don't need to meet people. The other is that when new media technologies facilitate new social networks, they simultaneously challenge existing social, political and economic relationships.
This class' topic is social networking.
Social networks as science: field. Social network analysis is an 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 an understanding of social networks too. For instant, treatises mix all field. And professor said he's experience.
Social networks as science: field.
Social network analysis is an 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 an understanding of social networks too.
Social network as science: definition. Potential constraints on their behavior. For instance, go to army and network system. Example of network system is genealogical table.
Children connected between mother side and father side.
Social network as science: history. Like J.L. Moreno, kinship (family) studies, see Jeff Tobin, many people stuied social network history. The funny study is Stanley Milgram (1967)
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". The world is small. Because that needed only six-degrees of separation.
This studies are important. We can know patten, and face each other.
And next example is this. 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. Because friends have similar interesting.
Social networks as science: equivalence. “structurally equivalent” means connect to the same people and thus have equivalent positions in the network.
social networks as science: social capital. If you connect separate networks you have bridging capital. If you are central to a network you have bonding capital.
Social networks as science: bowling alone. Sociologist robert putnam claims that united states citizens no longer know or trust their neighbors and thus communities have lost their social capital.
social networks as technology. For instance, email, newsgroups, and weblogs.
In the design of the arpanet (the forerunner to the internet) email was an afterthought!
Search engines: e.g., Google. Google’s Page Rank algorithm gives more weight to popular webpages. A webpage is considered popular if many other webpages link to it.
Compare this to search engines built specially for weblogs, music, movie and so on.
Collaborative filtering and/or recommender systems; e.g., amazon.com’s feature: “People who bought this book also bought...”
Social networks as popular culture. e.g., six degrees of kevin bacon.
Kevin bacon has a bacon number of 0. An actor, A, has a bacon number of 1 if s/he appeared in a movie with kevin bacon. An actor, B, has a bacon number of 2 if s/he appear in a movie with A. And etc. Try this with the internet movie database or, have it done automatically here, at the “oracle of bacon”.
“Fixing” the networks; e.g., Google hacking.
social networks as popular culture. Social software; e.g., friendster, orkut, tribe, cyworld etc. Tunderstand “artificial” social networks we need to rethink the social scientific concepts of “equivalence,” “centrality,” even “node” and “link.”
Social networks as art.
Ben Discoe’s, Friendster Map : Well, you can do that using cyworld.
Mark Lombardi, Global Networks (using pen, pencil, paper), Official Computer Scene Sexchart, Josh On (Futurefarmers), They Rule, Jonah Peretti, Nike Sweatshop Email, Angie Waller, Data Mining the Amazon.
*comments.
Networking is very important field. I studied many things.
*
Professor said key points so far. First, when technologies connect or separate people, they become media. Second, tembody social, political, cultural, economic and philosophical ideas and relationships. Third, when a medium is new, it is often used to simulate old media. Fourth, new media do not replace old media, they displace them. Last, people make media and then media make people.
And next, he said today's key points. One is that New media technologies usually reinforce existing social networks or even work to isolate people. For example is e-mail and messenger. Because e-mail and messenger are don't need to meet people. The other is that when new media technologies facilitate new social networks, they simultaneously challenge existing social, political and economic relationships.
This class' topic is social networking.
Social networks as science: field. Social network analysis is an 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 an understanding of social networks too. For instant, treatises mix all field. And professor said he's experience.
Social networks as science: field.
Social network analysis is an 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 an understanding of social networks too.
Social network as science: definition. Potential constraints on their behavior. For instance, go to army and network system. Example of network system is genealogical table.
Children connected between mother side and father side.
Social network as science: history. Like J.L. Moreno, kinship (family) studies, see Jeff Tobin, many people stuied social network history. The funny study is Stanley Milgram (1967)
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". The world is small. Because that needed only six-degrees of separation.
This studies are important. We can know patten, and face each other.
And next example is this. 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. Because friends have similar interesting.
Social networks as science: equivalence. “structurally equivalent” means connect to the same people and thus have equivalent positions in the network.
social networks as science: social capital. If you connect separate networks you have bridging capital. If you are central to a network you have bonding capital.
Social networks as science: bowling alone. Sociologist robert putnam claims that united states citizens no longer know or trust their neighbors and thus communities have lost their social capital.
social networks as technology. For instance, email, newsgroups, and weblogs.
In the design of the arpanet (the forerunner to the internet) email was an afterthought!
Search engines: e.g., Google. Google’s Page Rank algorithm gives more weight to popular webpages. A webpage is considered popular if many other webpages link to it.
Compare this to search engines built specially for weblogs, music, movie and so on.
Collaborative filtering and/or recommender systems; e.g., amazon.com’s feature: “People who bought this book also bought...”
Social networks as popular culture. e.g., six degrees of kevin bacon.
Kevin bacon has a bacon number of 0. An actor, A, has a bacon number of 1 if s/he appeared in a movie with kevin bacon. An actor, B, has a bacon number of 2 if s/he appear in a movie with A. And etc. Try this with the internet movie database or, have it done automatically here, at the “oracle of bacon”.
“Fixing” the networks; e.g., Google hacking.
social networks as popular culture. Social software; e.g., friendster, orkut, tribe, cyworld etc. Tunderstand “artificial” social networks we need to rethink the social scientific concepts of “equivalence,” “centrality,” even “node” and “link.”
Social networks as art.
Ben Discoe’s, Friendster Map : Well, you can do that using cyworld.
Mark Lombardi, Global Networks (using pen, pencil, paper), Official Computer Scene Sexchart, Josh On (Futurefarmers), They Rule, Jonah Peretti, Nike Sweatshop Email, Angie Waller, Data Mining the Amazon.
*comments.
Networking is very important field. I studied many things.
*
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