Presentation at re:publica TEN, Berlin

1. D O A N D R O I D S D R E A M O F
E L E C T R I C C O P Y R I G H T ?
D R A N D R E S G U A D A M U Z , U N I V E R S I T Y O F S U S S E X
@ T E C H N O L L A M A
A . G U A D A M M U Z @ S U S S E X . A C . U K

2. A P O L O G I E S

3. A R T I F I C I A L I N T E L L I G E N C E

4. D E F I N I T I O N
An entity with the capacity “to
perceive, understand, predict,
and manipulate a world far
larger and more complicated
than itself”, Russell and Norvig,
1995.

5. N E U R A L N E T W O R K S
• Artificial intelligence approach
based on biological neural
networks.
• Usually based on mathematical
models that use neuron
equivalents.

6. M A C H I N E
L E A R N I N G
“Field of study that gives computers
the ability to learn without being
explicitly programmed”. Arthur
Samuel, 1959.

7. A I A R T

8. A I A R T I N C U LT U R E
• Androids and robots have been
creating art almost since the
beginning.
• Music, poetry, photography,
sculpture, games, dance.
• From Star Trek to Her, from Lost in
Space to Ex Machina.

9. C O M P U T E R
PA I N T E R S
• Early machine art in the 60s.
• Aaron
• e-David
• The Painting Fool
• Ava
• Deep Dream
• The Next Rembrandt

10. S AVA N N A H C O X
“The completed portrait is a rich and intimate study of a man’s unique vision, his
materials, and his inevitably flawed execution of outwardly conveying that internal
vision to others. In short, it documents the human condition. But what if that act
can be perfected through technology? Is it art, or is it science? Or both?”

11. G R A N D
A S P I R AT I O N S
“I'm The Painting Fool: a
computer program, and an
aspiring painter. The aim of this
project is for me to be taken
seriously - one day - as a creative
artist in my own right. I have
been built to exhibit behaviours
that might be deemed as skilful,
appreciative and imaginative.”

12. A U T O N O M O U S
A R T I S T S
The idea is not to have a
computer pretending to be an
artist, as is the case now, but
rather have a creative artist in its
own right through the use of
novel algorithms.

13. AVA

15. D E E P D R E A M

16. D E E P D R E A M
E X P L A N AT I O N
“Instead of exactly prescribing which feature we
want the network to amplify, we can also let the
network make that decision. In this case we
simply feed the network an arbitrary image or
photo and let the network analyze the picture.
We then pick a layer and ask the network to
enhance whatever it detected. Each layer of the
network deals with features at a different level of
abstraction, so the complexity of features we
generate depends on which layer we choose to
enhance. For example, lower layers tend to
produce strokes or simple ornament-like
patterns, because those layers are sensitive to
basic features such as edges and their
orientations.”

18. B E N D AV I E S
“Of course it’s art! There’s no limit to what you can classify as “art.”
The question is only ever whether it’s good art. And people seem to
be very amused by it.”

19. I M I TAT I O N O R C R E AT I O N ?

20. T H E N E X T
R E M B R A N D T
Project by Microsoft research
team that produced a new
Rembrandt painting by a
combination of data mining
existing art and using machine
learning algorithms.

21. W H AT I S G O I N G
O N ?
• Is it really AI? Is it just clever use of
filters?
• Application of learning algorithms
and machine learning.
• Pre-selected levels of abstraction
dependent on parameters.
• Various levels of independence.

22. T H E L A W

23. R I G H T S A N D
R E S P O N S I B I L I T I E S
• This is not a new argument in law,
dates back to Roman laws
dealing with slavery.
• Rights and responsibilities of
subjects that cannot exercise
rights.
• Negligence, contract, tort, we
have ways of dealing with liability.

24. ! M E D I E N G R U P P E
B I T N I K
• Random Darknet Shopper
• Botnet buying random items from the
Darknet using Bitcoins.
• It purchased drugs.
• Police confiscated the bot, then
released.
• Public prosecutor deemed the artistic
work outweighed any possible damage
of purchasing drugs.

25. N O N - H U M A N
R I G H T S
• Movement to grant some rights to
animals.
• Naruto v Slater. PETA sues
photographer on behalf of Naruto to
have him declared as the selfie’s
author.
• “Copyright law is clear: It’s not the
person who owns the camera, it’s the
being who took the photograph.”
Internet Policy Review: http://bit.ly/1O0qZSW

26. U K L A W
S 9(3) “In the case of a literary,
dramatic, musical or artistic work
which is computer-generated,
the author shall be taken to be
the person by whom the
arrangements necessary for the
creation of the work are
undertaken.”

27. U S C O P Y R I G H T
O F F I C E
“In order to be entitled to copyright
registration, a work must be the
product of human authorship. Works
produced by mechanical processes or
random selection without any
contribution by a human author are
not registrable. Thus, a linoleum floor
covering featuring a multicolored
pebble design which was produced by
a mechanical process in unrepeatable,
random patterns, is not registrable.”

28. E U R O P E A N L A W
• In Europe a work is original if it is
“author’s own intellectual creation
reflecting his personality”. Directive
2006/116/EC.
• Choice, selection of elements,
composition, all may prove
originality. (Infopaq, Painer cases).
• Unclear if setting parameters and
algorithms would be enough.

29. O P T I O N S F O R A I
C O P Y R I G H T
• No copyright due to no originality/
creativity.
• No registration.
• Make UK’s approach more widely used,
programmer gets copyright.
• Take a wider approach: “copyright laws . . .
do not expressly require ‘human’
authorship.” Urantia Foundation v.
Maaherra (1997).
• Artificial Intelligence rights?

30. @ T E C H N O L L A M A
A . G U A D A M M U Z @ S U S S E X . A C . U K
The mech shall inherit the Earth