Executing Things @ Aarhus University Guest speaker for undergraduate course: Language + Code

1. Execu&ng
Things
Winnie
Soon
@
Aarhus
University
19.Apr.2016

4. Execu&on
“like
poetry,
the
aesthe&c
value
of
code
lies
in
its
execu+on,
not
simply
its
wriHen
form”
(Cox,
McLean
and
Ward,
2000,
n.p)

5. Execu&on
The
code
is
interac&ng
with
the
user,
itself,
its
environment,
and
the
systems
it
has
access
to
via
many
mul&-­‐layered
and
mediated
interfaces
that
are
available
to
it.
Many
of
the
components
are
predetermined,
but
through
the
combina&ons
of
interac&ons
combined
with
the
dynamism
and
unpredictability
of
live
ac&on,
the
result
is
far
from
fixed
as
a
whole.
(Cox,
McLean
and
Ward,
2004
p.
164)

6. Love
LeHer
Generator
(1952)

7. Love
LeHer
Generator
(1952)
“My
–
(adj)-­‐(noun)-­‐(adv)-­‐(verb)
your-­‐(adj)-­‐(noun)”
“You
are
my-­‐
(adj)-­‐(noun)”
“Yours-­‐(adv)
M.U.C”

8. If
I
wrote
you
a
love
leHer
would
you
write
back
(and
thousand
of
other
ques&ons)
By
Winnie
Soon
and
Helen
Pritchard
-­‐
2016,
Electronic
Literature
Collec&on,
Volume
3
-­‐
2015,
Ar&s&c
Research,
Kunsthal
Aarhus
@
Denmark
-­‐
2013,
Digital
Futures,
Victoria
and
Albert
Museum
@
London,
UK
-­‐
2012,
Microwave
Interna&onal
New
Media
Arts
Fes&val
@
Hong
Kong

9. If
I
wrote
you
a
love
leHer
would
you
write
back
(and
thousand
of
other
ques&ons)
The
network
asks
us
‘If
I
wrote
you
a
love
leHer
would
you
write
back?’
in
this
work.
Computa&onal
code
draws
thousands
of
ques&ons
from
online
maHer
into
the
exhibi&on
space.
The
ques&ons
are
gathered
in
real-­‐&me
from
the
social
media
site
TwiHer
and
encoded
to
speech.
Listening
is
a
form
of
decoding,
and
in
this
work
the
machine
constantly
undergoes
the
process
of
edi&ng,
encoding
and
decoding
texts.
What
happens
when
wriHen
texts
of
the
network
are
converted
to
speech?
How
does
it
feel
to
listen
to
the
ques&ons
of
a
machine,
when
these
ques&ons
are
our
familiar
tweets?

10.
Execu&ng
queries

11. A
simplified
model
of
Thousand
Ques&ons
Sohware:
Thousand
Ques&ons
TwiHer
Query:
keywords
=
“?”,
EN,
no=x,
recent
Tweets,
who,
&me,
id….
Voice
+
Visual

12.
What
cons&tutes
unpredictability
through
execu&ng
live
queries?

13.
1.
Random
events

14. A
thinking
model
of
TwiHer
random
input

15.
2.
Noise
and
unpredictability

16. Informa&on
Theory

17.
3.
Operators

18. Query
Put
simply:
query=?+hello+-­‐world

19. Rela&onal
operators
• ==
• >
• <
• !=
• >=
• <=

20.
4.
Inexecutable
query

22.
Inexecutable
query

23. Unpredictable
manifesta&on
Sohware:
Thousand
Ques&ons
TwiHer
Query:
keywords
=
“?”,
EN,
no=x,
recent
Tweets,
who,
&me,
id….
Voice
+
Visual

24.
how
do
code
and
language
differ
how
are
they
similar?