Collaboration between humans and AI systems
Involving AI systems in
the creative proccess
Artistic views on the use of AI
AI-based technologies are already massively shaping our world, and the speed of their development creates an urgency to understand them. In 2019, the Ars Electronica Futurelab developed several installations for the exhibition Understanding AI at the Ars Electronica Center. The approach taken by Ars Electronica contained two elements that were also characteristic of the Futurelab: On one hand, the Ars Electronica Futurelab developed installations with the aim of making the complex topics of machine learning and neural networks understandable. At the same time, it created art projects that might raise unexpected questions and cast a critical eye on the uses of AI in our societies. The object was—as Ali Nikrang put it—“to illuminate and demystify the technology.” This also required installations that could make transparent how the various methods of training an AI system actually work and what kinds of biases—gender, ethnic, or others—can arise from this, which in turn may affect, for instance, recruiting systems of companies or selection mechanisms in education.
The exhibition also shows Ars Electronica’s method of diving deep into a system, filtering out the key aspects of that system and its implications, and then creating insights in form of installations, interventions or artworks, that open up the spaces necessary for forming one’s own informed, inspired and critical opinion, ideally to join the discourse about one’s own perspective towards the meaning of it for the future.
An artistic view on issues regarding the use of AI of course also includes looking into the implications of AI systems for concepts of creativity and for the specific works of artists. Ali Nikrang made creative intelligence to his key research field and approaches the question: „Can machines create?“ In recent years, there has been a great deal of academic interest in the application of the new, much more efficient generation of neural networks (called Deep Learning) applied to creative tasks such as creating texts, images or music with fascinating results. Technically speaking, Deep Learning models can only learn the statistical patterns of the data. Thus, they often can learn relationships in the data that human observers have not been aware of, and thereby serve as a new source of inspiration for human creativity. The Ars Electronica Futurelab’s research focuses not only on the technological aspects of AI in creative and artistic applications, but also on new ways of interaction and collaboration between humans and AI systems. The team regards it as an important factor to find the right balance to integrate new technologies in cooperation with us humans.
2019
An exhibition presenting the most important technical aspects of artificial intelligence as well as concrete examples of how they are used. Visitors can discover how machines and their sensors “perceive” the world in comparison to humans, what machine learning is, or how automatic facial recognition works, and also learn about various social and ethical issues.
read more2019
An artificially intelligent algorithm completed Gustav Mahler’s unfinished Tenth Symphony by feeding OpenAI’s model MuseNet with the first ten notes of the musical theme of Mahler’s 10th Symphony. After the generated melody had been orchestrated by Nikrang by hand for an orchestra, the project Mahler-Unfinished was performed by the Bruckner Orchestra Linz at the Big Concert Night at the 2019 Ars Electronica Festival
read more2020
An interactive AI-based music composition system that aims to create an intuitive interface between human artists and an AI-based composition system, where human users and the AI system can discover the potential of a musical idea (given to the system by the users or initialized by the system itself) in a collaborative way. The interaction takes advantage of the benefits of artificial creativity, together with the ability to control and personalize the output of the system by human users.
read more“Algorithmic Apperception investigates ways to admit artificial systems into [physical] space [and] to enable machines to not only sense their environment but make sense of it. ... A meaningful combination of obtained features in conjunction with a sociological and cultural understanding assures natural interaction, simplicity and intuition.”
Otto Naderer
Key Researcher at Ars Electronica Futurelab
Born in 1982 in Linz, Austria. Key researcher for Algorithmic Apperception. Otto Naderer realizes projects with an emphasis on enabling machines’ capabilities of perceiving and interpreting their surroundings. Joined Ars Electronica Futurelab’s Creative Engineering team in 2006 after an internship during his bachelor’s program in computer science.
Credit: Peter Holzkorn
Credit: vog.photo
“ ... the key point when it comes to AI is the paradigm shift. So far we have mainly used technology for automation. ... There can only be one way for us to live together with technology. It is not about what technology can do. It is about what human[s] can do with technology. We must find democratic and, above all, ethically clean solutions before we allow technology to operate autonomously in our midst. That is the challenge in connection with so-called artificial intelligence.”
Peter Freudling
Lead Producer at Ars Electronica Futurelab
Born in 1976 in Innsbruck, Austria. Lead producer and artist. He joined the Ars Electronica Futurelab during his studies of industrial design at the University of Art and Design Linz. As a researcher in the Virtual Environments group, he helped to create several projects in the field, including the CAVE at the Ars Electronica Center.
“Instead of modeling our technologies after our self-image as human beings, I would strive to make systems think more like animals, which are in fact possibly much smarter than we are. When I was a child I got deeply interested in nature and with fascination studied the behavior of insects. Learning from nature helps us ‘think outside the box,’ which is badly needed in the world of innovation.”
Anouk Wipprecht
Born in 1985 in Beemster, Netherlands. Fashiontech designer, engineer, and innovator. Work with wearable robotics and research on behavioral aspects of interactions of body-based electronic design. Created “Agent Unicorn,” a health tech device monitoring brainwaves of children with ADHD, during a SPARKS residency at the Ars Electronica Futurelab in 2016.
Credits: Hep Svadja
Credit: tom mesic
“I feel it’s important that we think about what humanity means as we continue to innovate because it is my observation that more and more humans tend to view and treat everything like a tool; even other people.”
Sarah Pektus
Roboticist and illustrator. Together with her partner, Mark J. Koch, she creates wearable devices and robotic entities. Residency at the Ars Electronica Futurelab and the European Space Agency (ESA) in 2017 in the “Digital Art and Science Network.” Residency at the Leiden Observatory and the Ars Electronica Futurelab as part of the “European ARTificial Intelligence Lab” in 2021.
“For the moment, neural network based AI systems are used as tools rather than counterparts. They can serve as a new source of inspiration for human creativity by opening up new perspectives and detecting connections in the data that human observers might have not been aware of. Even more, they can be helpful for deepening our understanding of our own creativity.”
Ali Nikrang
Key Researcher at Ars Electronica Futurelab
Born in 1980 in Teheran, Iran. Classical musician and AI researcher. Studied computer science at the Johannes Kepler University Linz and composition with a focus on new media at the Mozarteum University Salzburg. Diploma in piano performance from the Mozarteum. Member of Ars Electronica Futurelab since 2011. Key researcher for Creative Intelligence.
Credit: vog.photo
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