User:Max/rwm/bridge

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Max 6.5 (B [+])


Steve's notes


You are developing a method of research – involving notation, synopsis and reflection. You have identified an area of research which informs your practice based research and the texts you are working with make a clear relation to your research. I can see your understanding growing the more you read and write. So read and write more! You may also benefit from re-reading key texts and making new notes so that your understanding grows deeper. Keep building the resource you are establishing. Good to see notation system and bibliography in place. These are the grades = DISTINCTION 10 (A+) MERIT 9 (A) VERY GOOD PASS 8 (A-) GOOD PASS 7 (B+) PASS 6 (B) NEAR PASS 5 (C) FAIL 4 (D)


A brief introduction to Predictive Text

The first text message was sent in 1992 from Neil Papworth, a former developer at Sema Group Telecoms. Mobile phones did not have keyboards at the time, so Papworth had to type the message on a PC. Papworth's text — "Merry Christmas" — was successfully sent to Richard Jarvis at Vodafone. Most early GSM mobile phones did not support sending SMS (Short Message Service) text messages and only Nokia supported the sending of SMS text messages. Like often with new technology the initial growth was slow.

0.4 SMS were sent per month per person / customer in 1995. In the year 2000 customers sent 35 SMS per month. Then in 2007 for the first time there were more text messages than phone calls per month.

Writing text messages on mobile phones was always hard. Because the available space on a mobile phone is very limited keyboards are not very convenient. A mobile phone in the early days had 9 number-keys, the first common method of commercial texting was "multi-tap", which means that each key displayed three to four letters. For example the key "3" holds "D", "E" and "F". To select the letter "E" you would have to tap two times the number-key "3". "Multi tap" was not very efficient.

In the 90s Tegic Communications developed a system/technology to simplify keying: T9. T9 stands for Text on 9 keys and was one of the first predictive text technologies. Instead of selecting each letter by tapping multiple times on the number keys with T9 the word gets formed by a single keypress for each letter. The groups of letters on each key are connected to a dictionary of words and the telephone looks up in this dictionary what words can be built out of the typed sequence. For example pressing "4663" will typically be interpreted as the word "good" (alternatives like "home", "hood" and "hoof" are also valid interpretations of this sequence). By offering words it speeds up the process of writing texts. It was also possible to extend the dictionary with individual entries and phones could learn to adapt to the user (= feedback loop, Norbert Wiener).

Full keyboards on mobile phones was first introduced in 1997 with the Nokia 9000i Communicator. It became a popular feature in the late '90s to early '00s.

In 2007 Apple introduced the iPhone which had a multi-touch interface with a virtual keyboard. Other companies followed soon. The virtual keyboards supported auto-correction, later also auto-completion. In 2014 with iOS 8 then Apple introduced the predictive text keyboard QuickType. It is a row with three words (word proposals) above the virtual keyboard. The more you use QuickType, the smarter it will get as it learns your style of writing and choice of words. Very similar predictive text keyboards exist on Android and Windows Phone devices.

Orwell.png

Orwellian Version - A brief introduction to Predictive Text

Neil Papworth sent the first text message in 1992. Mobile phones did not have keyboards at the time, because of this Papworth had to type the message on a PC. Papworth has sent the text "Merry Christmas" successfully to Richard Jarvis at Vodafone. Most early GSM mobile phones did not support sending SMS (Short Message Service) text messages and only Nokia supported the sending of SMS text messages. Like often with new technology the initial growth was slow. -cite-

In 1995 customers sent 0.4 SMS per month. In 2000 customers sent 35 SMS per month. In 2007 for the first time customers wrote more SMS than made phone calls.

Writing text messages on mobile phones was always hard. Because the available space on a mobile phone is very limited keyboards are not very convenient. A mobile phone in the early days had 9 number-keys. The first common method of commercial texting was "multi-tap", which means that each key displayed three to four letters. For example the key "3" holds "D", "E" and "F". To select the letter "E" you would have to tap three times the number-key "3". As you can imagine "Multi tap" was not very efficient.

In the 1990s Tegic Communications developed a system/technology to simplify keying: T9. T9 stands for Text on 9 keys and was one of the first predictive text technologies. Instead of selecting each letter by tapping multiple times on the number keys with T9 you form the word by a single keypress for each letter. The groups of letters on each key are connected to a word dictionary and the phone compares the pressed sequence with the dictionary to make you suggestions which words can be built. For example pressing "4663" will typically be interpreted as the word "good". But there are also alternative valid interpretations of the sequence like "home", "hood" and "hoof". By suggesting words T9 speeds up the process of writing text. T9 could also adapt to the user, it was possible to extend the dictionary with individual entries.

Full keyboards on mobile phones was first introduced in 1997 with the Nokia 9000i Communicator. It became a popular feature in the late '90s to early '00s.

In 2007 Apple introduced the iPhone which had a multi-touch interface with a virtual keyboard. Other companies followed soon. The virtual keyboards supported auto-correction, later also auto-completion. In 2014 with iOS 8 then Apple introduced the predictive text keyboard QuickType. It is a row with three words (word proposals) above the virtual keyboard. The more you use QuickType, the smarter it will get as it learns your style of writing and choice of words. Very similar predictive text keyboards exist on Android and Windows Phone devices.

A few words about my recent work / research

In my work Love Letters (currently a working title) I will take use of these current predictive text algorithms to generate text messages. In the (eventual) performance there will be two phones lying side by side. One phone belongs to me, the other one belongs to my girlfriend. Both phones are turned on and ready to use. The display will show a text message application. A primitive robotic arm will formulate a text message by clicking self-acted on one the three word suggestions offered by the phone over and over. After a certain number of words, the robot will send the compounded text to the second phone which then starts answering the same way.

What happens if human interaction is removed from originally emotion driven actions? The "output" of the performance might be a text of an intimate conversation, constructed by personalized phones and dictionarys we use every day to communicate.

The work deals with the increasingly automatization of our communication and the the constructed reflection of our identity in our communication devices.


McLuhan

“Our new electric technology that extends our senses and nerves in a global embrace has large implications for the future of language”


In his famous book “Understanding Media: The Extensions of Man” Marshall McLuhan examines the impact of media on societies. He states that every new technology changes our somehow our society. One example he gave is the railway which "did not introduce movement or transportation or wheel or road into human society, but it accelerated and enlarged the scale of previous human functions, creating totally new kinds of cities and new kinds of work and leisure." (McLuhan, Understanding Media, p. 8).

The medium itself has more fundamental and long-lasting effects than the more overt content (to which people normaly direct their attention). It follows that the dominant medium of a particular age, like print, radio or television has a huge impact to human relations.

The media also changes the way we communicate and in turn, this has effect on human relations (Mc Luhan, Understanding Media, p. 33, beginning of chapter 3). As I wrote earlier in the paragraph "Predictive Text", it was in 2007 as for the first time users of mobile phones preferred writing a text message (hot medium) instead of making a phone call (cool medium). McLuhan thinks "the oral man's inner world is a tangle of complex emotions and feelings" (Mc Luhan, Understanding Mediap. 50), whereas the in more literary societies the "practical man has long ago eroded or suppressed [feelings and emotions] within himself in the interest of efficiency and practicality" (Mc Luhan, Understanding Media p.50). The authorization, provided by the new technology in mobile phones, to write text messages efficient and without hurdles pushed the human communication in the in the western world one step further to "efficiency and practicality".


While media circulates it changes our society and our communication. Also the media itself changes and also if it interfers with a new technology (what Marshall McLuhan uses as a synonym for media I think). It is like a loop that feeds back from society to the medium. So every change in the media landscape or in the perception and participation of the people towards a medium, will have an effect on the medium itself. The fact that we prefer to send a text message instead of making a phone call will have consequences to other media (and societies).


Norbert Wiener

While McLuhan saw kind of feedback loops in human societies, Norbert Wiener (who defenitly influenced Marshall McLuhan) wrote about the similarities of circulations in "the animal and the machine". (The book I am reffering is "Cybernetics: Or Control and Communication in the Animal and the Machine", published in 1948.)

"Feedback is everywhere in biology, from neural circuits to hormonal pathways to gene expression loops, maintaining homeostasis or amplifying signals like those that control embryo development" (Agapakis, 2011). Norbert Wiener began to see the connections between control theory and biology when trying to build systems for shooting down airplanes during World War II. Feedback was necessary to constantly figure out how far off the system was from the plane and adjusting accordingly.

"Feedback means that certain processes, having both a beginning and ending point, should be able to receive new input about their surroundings throughout their duration" (Gallowy, Protocol, p. 59). His research in the '40s was very important for all following developments in the filed of computer machines. Also the predictive text technology is full with feedback loops. Every typed letter, every choosen word feeds back to the system to update the next possible words. In this way the machine adapts to the user and becames more and more autonomous.

Human communication becomes mediated, automated and predictable.


Redundancy and Claude Shannon

By assigning biological processes to computer machines, Norbert Wiener suggested to calculate interim results twice or even more often "for the sake of redundancy" (Gleick, The Information, ch. 4) to prevent errors. So redundancy is important for keeping the information decodable without loss – or redundancy helps to keep the information (especially when it is exposed to noise).

„Every natural language has redundancy built in; this is why people can understand text riddled with errors and why they can understand conversation in a noisy room“ (Gleick, The Information, ch. 1).

Claude Shannon, the father of information theory, worked up a theory which exposes the informative content (= entropy, Shannon, A Mathematical Theory of Communication, 1948) in messages. Shannon worked at a telephone company and was concerned "with questions of efficiency in sending messages down communication channels such as telephone lines" (Pickering, Cybernetic Brain, p. 148). Therefor he worked on making information and redundancy in messages measurable (Gleick, The Information, ch. 1).

In ordinary language, redundancy serves as an aid to understanding. When I write a message then I have the ordinary amount of redundancy of this particular language. „As a simple example in English, wherever the letter q appears, the u that follows is redundant" (Gleick, The Information, ch. 7). So we have redundancy in the language itself. I now wanted to extend the theme of redundancy to the whole message / to the meaning of a message. Becuase originally I understood Shannon wrong and thought that he is talking about the meaning of a message, but he is more talking about the redundancy of the language / the alphabet itself. But I see now, that this theme is not fitting into this essay. So I am willing to remove it and instead researching how meaning is given to a message or sense is produced. I am not sure if someone has ever answered this question.


Bibliography

  • Gleick, The Information, A History, A Theory, A Flood. New York, Pantheon Books; 2011.
  • McLuhan, Understanding Media, The Extension of Man. Cambridge, Massachusetts: The MIT Press; 1994.
  • Pickering, The Cybernetic Brain, Sketches of Another Future. Chicago, The University of Chicago Press; 2010.
  • Wiener, Cybernetics: Or Control and Communication in the Animal and the Machine. Cambridge, Massachusetts: The Technology Press; 1948.


Personal notes to ignore

Norbert wiener

boston arm

hearing glove / seeing glove


Keywords:

hot cold

participation

redundancy


1500 words


read: Cybernetic Brain


1) Explain my work

2) compare it make bridges to


McLuhan > Media circulates and changes the society

Wiener > Feedback Loops, systems adapt and learn (iPhone dictionary)

Shannon > Redundancy / Messages

Also Norbert Wiener talks about the importance of redundancy: „ In any case the computers, being human, made errors, so the same work was often farmed out twice for the sake of redundancy.“

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