This document discusses copyright issues related to works created by artificial intelligence or computer generation. It explores whether AI-generated works deserve copyright protection and who should own that copyright - the programmer, AI system creator, or AI system itself. The document also examines relevant case law and approaches to this issue under US, UK, and European copyright law. Overall it raises challenging questions about originality and creativity standards for copyright as AI and computer generation become more advanced and involved in content creation.

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

2. S P I R I T U A L M A C H I N E S ?

3. C O P Y R I G H T O W N E R S H I P O F
C O M P U T E R - G E N E R AT E D W O R K S

4. W H Y I S I T I M P O R TA N T ?

5. R O B O T I C
W O R K F O R C E
“In the creative economy, advances
in the area of Mobile Robotics may
have implications for making and
craft activities (as industrial robots
with machine vision and high–
precision dexterity become cheaper
and cheaper). Data Mining and
Computational Statistics where
algorithms are developed which
allow cognitive tasks to be
automated – or become data–
driven – may conceivably have
significant implications for non–
routine tasks in jobs as wide–
ranging as content.” NESTA.

6. C R E AT I V E
I N D U S T R I E S
• Procedurally-generated
games.
• Journalistic pieces.
• Art.
• Music.
• Literature.

7. D E E P D R E A M

8. 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.”

9. 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.”

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

11. 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.

12. T H E L A W

13. 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.

14. ! 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.

15. 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.”

16. 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.”

17. 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.

18. R E L E VA N T
C A S E L A W
• Case C-5/08 Infopaq
International A/S v Danske
Dagblades Forening.
• Feist Publications, Inc. v.
Rural Telephone Service
Co., 499 U.S. 340 (1991).
• Acohs Pty Ltd v Ucorp Pty
Ltd [2012] FCAFC 16.

19. 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?

20. 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

21. @ 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