The linguistic future of the Internet 231
technology? Great claims have been made for its use in accessing e-
mail,bookingtickets,receivingnews,gambling,playinggames,and
so on, but – to take just one example – how many text games will it
be possible to play? Having explored this possibility myself, on be-
halfofanelectronicpublishingfirm,theanswersarenotpromising,
with rather simple-minded multiple-choice games pushing the sys-
temtoitslimits.Doubtless,asthetechnologydevelops,awholenew
domain of restricted language will emerge, as people adapt their
messages to fit the screen, and make use of new software options.^8
But as I write, some commentators are already casting doubts on
the long-term future of WAP, despite its strengths. Ironically, be-
causeabbreviationsavestimeandmoney,thelinguisticinnovations
brought about by this technology are likely to outlast its demise.
Applied Internet linguisticsA further dimension to the linguistic variety promoted by the new
technologies relates to the content they carry. As with traditional
written expression, the medium will influence the general character
of the language to be used – whether it is information, education,
entertainment, edutainment, advertising, buying and selling, on-
screen guides, teletext services, or any other domain. Within these
broad categories, subject-related domains (science, religion, law,
etc.) will doubtless evolve computer-mediated varieties along sim-
ilar lines to those which emerged in traditional speech and writing.
I would also expect to see more specialized varieties, as organiza-
tions develop intranet systems and use them for their individual
purposes,suchasconferences,brainstorming,voting,andin-house
editing. And I would expect to see a huge increase in the range of
‘applied’ varieties, as different professions gain more confidence in
computer-mediated technology, and start to develop its potential
for their individual purposes. The Internet has already begun to be
used in this way.
(^8) For example, a typical phone is able to predict likely words from the keystrokes entered,
using a stored list of 10,000 or more pre-programmed words.