=Paper=
{{Paper
|id=Vol-2160/C3GI_2017_paper_2
|storemode=property
|title=Biometrics and Artificial Creativity
|pdfUrl=https://ceur-ws.org/Vol-2160/C3GI_2017_paper_2.pdf
|volume=Vol-2160
|authors=Pietro Galliani
}}
==Biometrics and Artificial Creativity==
https://ceur-ws.org/Vol-2160/C3GI_2017_paper_2.pdf
Biometrics and Artificial Creativity
Pietro Galliani1
Free University of Bozen-Bolzano,
Pietro.Galliani@unibz.it
Abstract. I argue that neither explicit user evaluation nor self-directed
exploration of pre-determined spaces of possibilities are viable approaches
for implementing artificial systems whose products are recognizable by
humans as creative and valuable and, at the same time, as genuinely
authored by the artificial system (rather than by the original designer or
by the human users): indeed, self-directed creativity requires critical en-
gagement with a creative community, and for now artificial systems are
not capable of interacting with human creative communities as peers.
I suggest a possible alternative, which might hypothetically be used to
grant some degree of authorship to artificial systems without having
general artificial intelligence as a prerequisite: in brief, artificial systems
could be trained, through the use of biometrics, to generate products
that induce the same types of reactions in humans of recognized creative
works.
As this would not draw conscious human decision-making into the pro-
duction process, there would then be grounds to argue that the products
of such a system would have indeed non-human authorship.
Keywords: computational creativity, authorship, biometrics
-4. Painting for zots, or: on the benefits of alien probing
The time has come again for the Intra-Galactic Painting Competition, and ex-
citement is high as humankind (having finally succeeded in contacting the rest
of the Milky Way community) has been invited to participate for the very first
time. The competition is held once every fifteen galactic years on a randomly
selected planet; and, this time around, the honor of hosting and judging it has
been assigned to the zot, a thoroughly non-anthropomorphic and very influential
species. It is of paramount importance for the future of human civilization that
human artists impress favorably the zot judges, as the zots have been known
to offer highly favorable trade conditions to those species which they regard as
artistically gifted.
But there is a difficulty: in accordance to ancient traditions, the partici-
pants are expressively forbidden from using translation devices to communicate
with their guests until the end of the competition. Humans knows next to noth-
ing about the zots, and what little they know suggests that their psychological
makeup is profoundly different from that of humankind or any other terrestrial
species. Thankfully, the Solar System Federation has obtained access to a col-
lection of some of the most significant works of art of the zot civilization; but
the natures of their contents and the reasons why they are so well-regarded by
the zots are truly anyone’s guess.
The night before the start of the competition, Carol and Bob — two of the
human participants — are discussing about their submissions over a glass of
space ale:
Carol: “I thought a lot about this, and I’m pretty sure I made the right choice
in picking bluethings as the main theme of my work.”
Bob: “Bluethings? What are they?”
Carol: “I’m not sure, to be honest, but they are blue. And spiky. Zots love
them, that’s for certain.”
Bob: “Uh. Seems difficult, painting something without knowing what it is or
what significance it has...”
Carol: “Yes, but I studied their works, and many of their most greatest pieces
are all about bluethings. Well, bluethings and shinythings.”
Bob: “And the shinythings are...”
Carol: “No idea, again, but they are shiny — shiny and round. The zots draw
them a lot too, so they must be pretty important to them. Oh, and I noticed
that whenever a composition contains bluethings, it never contains shiny-
things unless there is a jagged line separating them, so of course I did the
same — it must be a cultural taboo of some sort, and it would not do to
offend our guests. But enough about me, what is your piece about?”
Bob: “Well, it is just a group of children playing board games...”
Carol: “What? But we do not even know if the zots have any notion of child-
hood! And how are they supposed to recognize a board game? I really hope
you won’t lose us the competition...”
Mutatis mutandis, this would not be too out of place as a hypothetical di-
alogue between two computer programs for automatically generating creative
works for human consumption. No artificial system has yet been built which
contains an acceptable model of the overall themes and motivations which drive
human creative production and the appreciation thereof, largely because we our-
selves are not entirely clear on what these themes and motivations are; but a
good number of systems have been built which, much like Carol, generate au-
tomatically works in accordance to the “rules” typical of certain categories of
human creations. There also exist Bob-like systems, which eschew human imi-
tation entirely and operate through the iterative application of rules which have
very little to do with human stylistic conventions; but then, very careful tun-
ing of their parameters and algorithms is necessary if their products are to be
appreciable by most humans beyond their novelty value.
If it is not easy to find a common artistic ground between zots and humans,
it cannot be much simpler to find one between humans and non-sapient, non-
biological, artificial processes; and the fact that such processes are human-made
does not by itself imply that they are human-like in any meaningful sense, no
matter the superficial similarities (or lack thereof) between their results and
other forms of human expression.
But there is one approach to the problem of painting for zots that the artists
of our story failed to consider: they could have attempted to show a variety of
works to zots, measured accurately their physiological reactions, and compared
them to those observed when they are shown well-regarded works of zot origin.
If the zots’ reactions in the two cases were similar, then — regardless of the
the many ways in which their psychological makeup might differ from that of
human beings — there would be reason to suspect that their psychological re-
actions would be also similar; and if instead they were different, it would not be
unreasonable to conclude that their psychological reactions are also different.1
In what follows, I will argue that essentially the same process, with us taking
the role of the zot subjects and our machines taking the role of the human
examiners, provides us with a promising avenue for the exploration of creativity
through artificial means.
-3. Two approaches to artificial creativity
One of the main challenges faced in the study of creativity — and, at the same
time, one of its most intriguing aspects — is the fact that recognizing the prod-
ucts of creative endeavors is a very context-dependent task. To mention a rather
infamous example, a urinal may or may not be considered a creative work de-
pending on whether it is placed in a museum or in its more typical habitat; and,
in the former case, its possible recognition as such presupposes the appreciation
of a complex set of cultural and historical circumstances. A hypothetical alien,
bereft of any knowledge of the history of European artistic movements and of
human biological functions, would presumably find the same object just as con-
fusing in both circumstances; and, while they may notice that the placement of
such an object in a museum is less common than its placement in a bathroom,
they would have little way to infer the significance attributed to the urinal in
the second case.
More prosaically, cross-cultural recognition and evaluation of creative works
is a notoriously difficult enterprise; and it would not be unreasonable to expect
this difficulty to only worsen in the case of works generated by nonhuman, arti-
ficial processes whose structures and behaviours are, after all, vastly dissimilar
from the ones of human beings.
For many products of artificial processes, this is not at all the case. Instead,
the processes they originate from are tailor-built to imitate known forms of
human creative activity, be it musical composition (Loy, 1989), development of
mathematical theories (Colton, 2002), or story creation (Meehan, 1977), and
their performance is evaluated on the basis of the degree up to which their
outputs can pass as genuine human creations. With some partial exceptions (in
particular, Colton’s Painting Fool (Colton, 2012)), these processes do not contain
any attempt to represent the motivations and concerns of a hypothetical, even
1
It is also not entirely impossible that the Zot Empire might take umbrage at the
kidnapping and probing of its citizens, but you cannot make an omelette without
provoking an interstellar war.
vaguely human-like author, contenting themselves instead with exploring, more
or less arbitrarily, a fixed and well-defined “conceptual space” (Boden, 2001)
whose rules have been known to be compatible with the production of valuable
human works.
It is worth emphasizing here that relaxing the constraints of such a system,
for example by allowing it to arbitrarily break out from some of the boundaries
of the target conceptual space, would not in itself make it more creative. For
instance, the fact that the numbering of the sections of the present work starts
from minus four rather than from one is a largely pointless deviation from the
common conventions of writing which does not increase in any sense its quality.
Further changes to this work along similar lines could only make the experience
of reading it more and more frustrating: the subversion of expectations can at
times be used to convey interesting effects, but breaking them at random is
unlikely to improve the quality of the product.
On the other hand, there are also works of generative creativity that cannot
be reasonably described as mere attempts to imitate the superficial features of
human products. These works emerge from processes, often based on notions
from artificial life, which develop and unfold freely and without any expectation
of compliance with the conventions of human genres: as an example of this kind
of approach, we can mention here Reas’ Process Compendium (Reas, 2010). This
very quality, however, makes their evaluation quite problematic. In which sense
can we claim such processes to be creative, when the processes producing other
non-human but similarly aesthetically-appealing phenomena — for instance, the
shapes taken by clouds, or the sound of the sea — are not commonly regarded as
creative? Furthermore, when these artificial processes generate truly compelling
works, it is generally the result of the careful exploration of their parameter
space by part of a human experimenter. But then, could not one argue that this
human experimenter, not the artificial process, is the true locus of creativity, and
that therefore these artificial life-based approaches are simply another medium
for the production of artistic works — an intriguing and largely unexplored one,
certainly, but not one that succeeds in separating the phenomenon of creativity
from the rest of the human experience?
-2. Two loops in human creativity
Many theoretical models of the human creative process have been produced
(Runco and Albert, 1990; Kozbelt et al., 2010), and it is not within the scope
of this work to discuss any of them in detail. One fairly non-controversial ob-
servation, however, is that creative activities involve on one hand the individual
author as they incrementally build and evaluate their works, and on the other the
society in which the author lives as it provides them with established techniques
or conventions and influences their self-evaluation criteria.2
2
A topic which is somewhat controversial, instead, is the relative degrees of influence
of the characteristics of individual author and of those on their their society on the
results of the author’s activity.
Thus, without making any strong commitment to any theory of creativity,
we can reasonably recognize at least two distinct feedback loops as having a role
in the creative process:
1. The internal loop, through which the author evaluates the products of their
own activity and uses the results of such evaluations to direct their future
activity;
2. The external loop, through which the very criteria used by the author to
evaluate their own work are updated by such means as the observation of
other people’s reactions to the author’s works or the author’s own evaluation
of others’ works.
Fig. 1. Human creativity: internal and external loop.
These two loops are necessary components of any genuinely creative process:
indeed, the activity of an author bereft of the internal loop would be nothing
but mere automatic reaction to external stimuli, whereas an author bereft of the
external loop would lack any means for updating their own evaluation criteria,
and would thus have no way out of their solipsistic cycle of self-evaluation and
optimization according to a pre-defined, static ideals.
But this poses a serious problem for artificial creativity. Building an artificial
agent with an external loop towards a human creative community of richness
comparable to that of the loops linking humans authors to it would appear
to require endowing the artificial agent with human-comparable cognitive and
linguistic abilities; and this, despite the advances of artificial intelligence, still
remains an unsolved task. Do we have to give up, and accept that artificial
creativity requires general-purpose artificial intelligence?
Maybe not. A potential alternative solution, perhaps, might be to piggyback
on the evaluation functions of human users, for instance by having them rate
the quality of the artificial agent’s products and attempting to incrementally
improve the average quality of its solutions. This is the approach exemplified by
much interactive evolutionary art, from Dawkins’ Biomorphs (Dawkins, 2003)
to Draves’ Electric Sheep (Draves, 2005). However, in this case, it is not at all
clear that the artificial agents involved — as opposed to the systems composed
by these agents and the human evaluators — may be considered in any sense
creative.
Indeed, the locus of agency — and, therefore, of creativity — of such systems
does not lie within the artificial process, but instead solidly within the human
beings evaluating its products. If the human users wanted the process’ results
to become dull and uninteresting, they could easily succeed; and if they wanted
them to improve, they could only succeed up to the degree to which they can
correctly evaluate the quality of partial improvements on the current product.
The machine takes part to the internal loop, but not to the external loop, whereas
the human evaluators take part to the external and to the internal loop; thus,
the artificial agent appears to be taking a role more akin to that of a tool (if a
somewhat unpredictable one) than to that of a creator. Nevertheless, interactive
evolutionary algorithms show much promise: by providing human authors with a
vast repertoire of themes and possibilities that they might not necessarily have
developed autonomously, these algorithms are very well-suited for performing
the role of creativity-enhancing tools.
Fig. 2. Interactive evolutionary art. Note that the human users are part of both the
internal and the external loops, whereas the machine is only part of the internal loop.
-1. Artificial creativity through biometrics
In the previous section, I suggested that interactive evolutionary art is not usu-
ally quite an example of artificial creativity because the onus of evaluating the
results of the algorithm lies entirely with the human user. But a natural ques-
tion at this point would be: how does this differ anyway from the way in which
the creations of a human author are evaluated by their community? The an-
swer, in short, is that peer evaluations do not generally rob human authors of
their autonomy, because human authors are not typically in thrall of their peers.
They instead listen to their opinions and motivations, arguing — occasionally
quite vociferously — about their validity or lack thereof, and more than oc-
casionally rejecting them altogether. It might not be incorrect to claim that,
nonetheless, this implies that authorship is in some sense shared between the
direct creator and the community whose teachings and overall opinions affected
their choices; but, in any case, it is clear that while human authors do generally
seek the approval of their public, their activity is up to some not insignificant
degree self-directed — they face their critics as peers, not as slaves. This is not
the case for generative programs, whose activity is entirely determined by their
users’ evaluations, by random or pseudo-random events, and by the possibilities
and preferences inherent to their programming. The first two kinds of influences
mentioned cannot be reasonably compared to a human author’s own autonomous
decisions; and as for the third one, it constitutes a true case of artificial author-
ship only insofar as such possibilities and preference have not been designed by
the programmer with the express purpose of causing the program’s products to
be of a certain specific quality.
Our imaginary critic is, thus, not entirely wrong, and we have to retract to
some degree the overly strong claim made in the previous section: an interactive
evolutionary system can indeed be granted authorship, but only up to the mea-
sure in which its behaviour is not a function of the user’s evaluations, of random
events, or of the designs of its own author. This, however, does not resolve all
our problems: indeed, what we would ideally want to have would be an artificial
creative system whose products were “human-like” enough for us to evaluate and
appreciate. This puts us in the same situation of the zots mentioned in Section
-4: we want works of value to us, and we want them out of entities which are
almost entirely unlike ourselves, whose choices we do not want to have to micro-
manage, which lack any even vaguely accurate model of ourselves, and which are
not capable of communicating with us as equals. How can they possibly succeed?
One possible answer, the one this work has been driving towards, is the fol-
lowing: if an artificial process could measure human involuntary reactions to
high-quality works of human creativity, it could then — at least in principle —
iteratively update its products3 while attempting to increase the degree of simi-
3
Far more ambitiously, if we wished for the machine to eventually become capable of
generating valuable works without constant biological feedback, we might attempt
to make it optimize its production algorithm through some form of genetic program-
ming, rather than its individual products. In essence, this would be equivalent to
having the machine attempt to iteratively build a model of the features of humankind
larity between our responses to them and our responses to the above-mentioned
human works.4 This would put the agency in the creative process firmly out
of the reach of human consciousness, thus leading to the situation depicted in
Figure 3: the machine is now taking part in the internal loop of creation and
self-evaluation, but also — through the monitoring of the involuntary reactions
of its human users, which now are not making decisions in its place — in the
external loop of interaction with the larger human community.
Fig. 3. Interactive evolutionary art through biometrics: now both the human and the
machine are part of both loops.
0. Conclusion
In this work, I discussed some of the difficulties inherent to the problem of
creating non-human agents which are capable of creating novel and valuable-
to-humans works without relying exclusively on human decisions (made either
at implementation time or at execution time); and I suggested a possible ap-
proach based on the use of biometrics. There already exist works of generative
which are relevant to our appreciation, or lack thereof, of its products. Starting from
the perspective of Figure 3, this would amount to pushing the human users entirely
out of the internal loop of creation and self-evaluation.
4
In order to prevent plagiarism, we might also want to add the additional requirement
that the algorithm’s products should be sufficiently different from all the human-
made examples used to find the human physiological responses to high-quality work.
This might or might not be necessary, depending on the specific characteristics of
the algorithm; it could be also be the case that such a program would not be likely
to produce any given example anyway.
art which rely on biometrics, such as for example (McGee et al., 2011; Fan and
Weber, 2012; Haill, 2014) or — insofar as emotion detection goes — Colton’s
Painting Fool (Colton, 2012). But to my knowledge, the reason for using bio-
metrics in most such systems resides more in allowing users to visualize artistic
representations of their internal states than in measuring the similarity between
the users’ current internal states and the internal states of humans experiencing
high-quality works as a metric for self-optimization. Colton’s Painting Fool is
somewhat of an exception, as it can detect the mood of the scene and produce a
work which reflects it (see (Colton et al., 2008) for details): this is much closer
to the kind of approach described to this work, and a valuable starting point for
further research along these lines.
Bibliography
Margaret Boden. Creativity and knowledge. Creativity in education, pages 95–
102, 2001.
Simon Colton. Automated theory formation in pure mathematics. Springer, 2002.
Simon Colton. The painting fool: Stories from building an automated painter.
In Computers and creativity, pages 3–38. Springer, 2012.
Simon Colton, Michel F Valstar, and Maja Pantic. Emotionally aware automated
portrait painting. In Proceedings of the 3rd international conference on Digital
Interactive Media in Entertainment and Arts, pages 304–311. ACM, 2008.
Richard Dawkins. The evolution of evolvability. On growth, form and computers,
pages 239–255, 2003.
Scott Draves. The electric sheep screen-saver: A case study in aesthetic evolution.
In Applications of Evolutionary Computing, pages 458–467. Springer, 2005.
Yuan-Yi Fan and Rene Weber. Capturing audience experience via mobile bio-
metrics. In Proceedings of the 18th International Conference on Auditory
Displays (ICAD 2012), pages 214–217. Georgia Institute of Technology, 2012.
Luciana Haill. Ict & art connect: Revelations by flicker, dreamachines and elec-
troencephalographic signals in art. Available through researchgate, 2014.
Aaron Kozbelt, Ronald A Beghetto, and Mark A Runco. Theories of creativity.
The Cambridge handbook of creativity, pages 20–47, 2010.
Gareth Loy. Composing with computers: A survey of some compositional for-
malisms and music programming languages. In Current Directions in Com-
puter Music Research, pages 291–396. MIT Press, 1989.
Ryan McGee, Yuan-Yi Fan, and Reza Ali. Biorhythm: a biologically-inspired
audio-visual installation. In Proceedings of the International Conference on
New Interfaces for Musical Expression, pages 80–83, 2011.
James R Meehan. Tale-spin, an interactive program that writes stories. In
IJCAI, volume 77, pages 91–98, 1977.
Casey Reas. Process compendium. http://reas.com/compendium text/, 2010.
Mark A Runco and Robert S Albert. Theories of creativity. Sage Publications,
Inc, 1990.