At Many to many David Weinberger notes that people appear to be using fewer human stop words when searching – “search engines are training us how to talk to them”. He suggests that SMS abbreviations might be an example of the same trend. Humans trained by the machines.
In Norwegian, at least, a lot of the abbreviations are as much about creating one’s own identity as about obeying the machine. In Norway kids text in dialect rather than in officially sanctioned Norwegian. Leet, too, is more an expression of human identity than a way of speaking as machines speak, wouldn’t you say?

Actually I never use abbreviations in SMSes. I use the built-in T9 recognition engine and teach it my language instead. With a better phone I even work to achieve correct capitalisation and punctuation, and I’ll often spend extra money on a longer message rather than abbreviate things. None of my friends send me abbreviated messages either, it’s a sociolect, or perhaps an age-iolect.

Unfortunately even the apparently improved recognition of my new phone seems to think that “kill” is a more likely interpretation of 5455 than “Jill”, but I tend to talk it into accepting that me, I prefer “Jill”.

4 thoughts on “machine language

  1. weez

    And rather than Elouise Oyzon, it keeps wanting to turn me into elusive ozone. (Which would make for a nifty super hero name).

  2. Jill

    Sounds kind of cool… Actually I was just SMSing and noticed plenty of lazy capitalisation or non-capitalisation so I guess I’m not as strict as I’d claimed…

  3. Henning

    T9 is brilliant except for one rather annoying thing, namely that it cannot “learn” that you for instance write “Jill” more often than “kill” (I hope you do). You can`t even manipulate the list manually -> for instance move Jill up one place and kill one down. It is strange that this feature is not here yet. Each time I buy a new cellphone I expect this functionality to be there, but it hasn`t so far.

  4. Jill

    Actually, I just discovered that my new phone (Sonyericsson Z600) seems to have an improved T9 recognition thing – Jill’s at the top of the list now! Either it just puts “my words” up at the top automatically or it worked out I write Jill more often than kill.

    It still won’t let me delete those new words I taught it that are wrong. You know, when you press OK too soon and the spelling’s all wrong… Oh well.

Leave a Reply to Henning Cancel reply

Recommended Posts

Triple book talk: Watch James Dobson, Jussi Parikka and me discuss our 2023 books

Thanks to everyone who came to the triple book talk of three recent books on machine vision by James Dobson, Jussi Parikka and me, and thanks for excellent questions. Several people have emailed to asked if we recorded it, and yes we did! Here you go! James and Jussi’s books […]

Image on a black background of a human hand holding a graphic showing the word AI with a blue circuit board pattern inside surrounded by blurred blue and yellow dots and a concentric circular blue design.
AI and algorithmic culture Machine Vision

Four visual registers for imaginaries of machine vision

I’m thrilled to announce another publication from our European Research Council (ERC)-funded research project on Machine Vision: Gabriele de Setaand Anya Shchetvina‘s paper analysing how Chinese AI companies visually present machine vision technologies. They find that the Chinese machine vision imaginary is global, blue and competitive.  De Seta, Gabriele, and Anya Shchetvina. “Imagining Machine […]

Do people flock to talks about ChatGPT because they are scared?

Whenever I give talks about ChatGPT and LLMs, whether to ninth graders, businesses or journalists, I meet people who are hungry for information, who really want to understand this new technology. I’ve interpreted this as interest and a need to understand – but yesterday, Eirik Solheim said that every time […]