Hybrid Intelligence
Machine as Creative Partners
Humans are the natural maker; we enjoy the freedom of making things. However, in the context of automation, machines challenge humans’ role in fabrication. It wastes the human’s unique skills and makes people disconnect to real-world materials. To address this issue, researchers proposed the hybrid workflow, which starts from studying how humans work and combining both human and machine specialties in the fabrication process. It allows us to maintain craftsmanship and input more humanity into digital crafts.
The Hybrid fabrication values humans’ muscle memory and tactile skill in crafting process. What if we extend the hybrid idea for intangible processes, like creativity? Can machines work beyond assistant but also act as a creative partner? Can we create “Hybrid intelligence,” which combining machine and human intelligence to create works that either could not do on its own?
Hybrid fabrication is a collaboration between humans and machines that increases the efficiency of fabrication or humanity texture in works while reintroducing humans back into the loop. What if we extend the hybrid idea for intangible processes, like creativity? Can machines work beyond assistant but also act as a creative partner? Can we create “Hybrid intelligence,” which combining machine and human intelligence to create works that either could not do on its own?
Hybrid intelligence can optimize working efficiency and reduce uncertainty, like AI working with human drivers in autonomous vehicles. To let human and AI system working together harmoniously, researchers focus on how to eliminate the difference between human perception and machine judgment. If the machine perceives object differently with humans dose on the road, it could cause terrible traffics. While certain tasks require low uncertainty, others like art actually want risks. Risk sometimes could drive the creative process. Nowadays, robust computing becomes innovative tools for artists, and the unstable result brings by the machine learning algorithm empower us to create something beyond our imagination.
Machine perceives and interprets the world in a very different way. Tom white made a perception engine to present how the machine sees the world. Furthermore, he also invites people to interpret the image again, finding out that each people see different things. His project brings out opportunities that we could use the machine learning algorithm to open up a gap in human perception.
When scientists dominate the AI research, several artists open up a conversation about AI in an art context and take distinctive perspectives on this technique. They want to leverage the machine’s ability and use that to push the creativity boundary. Anne Ridler generated tons of artificial tulip by the AI and categorized the result by hand, which present the human aspect that sits behind machine learning. In Scott Eaton’s work “Figures and Form,” he combined the trendy algorithm with traditional practices of drawing and sculpture. The work presents the result of the interaction between Scott’s hand skill and AI tools. The computational power to achieve tasks that human can never reach before, such as generate tons of different images within a short time. The new type of human-AI collaboration inspires artists to envision other possibilities in visual presentation.
AI in music
Besides visual art, artists are also seeking ways to break the predictable pattern in the music field. Olafur Arnalds and Holly Herndon both ‘raise’ their own custom AI assistants, and ‘taught’ them into the personal music assistant which could inspire and collaborate with them. Once Olafur played a chord, that chord goes into the software, which manipulates it and then sends it out as rhythmical textures to other pianos. Instead of control every note, Arnalds can hit one key and get a multitude of unanticipated notes to form the customized AI assistant.
To explore the unknown territory, Holly created “Spawn.” Spawn is an AI system that can compose the surprising and ingenuity music, which could be very different from Holly’s style. With Spawn’s assist, Holly could prevent producing music that repeating her previous works. Not only Spawn learned form Holly, but Holly also learned from Spawn’s intelligence. The meaning behind the AI assistants is not to create an algorithm that makes music; it creates an instrument that artists can play with and broaden the possibility of the music.
AI in writing
With the development of natural langue process, AI could also use in the poetry and screenplays. AI-generated text is the central part of Ross Goodwin’s work. He trains the machine with text-base data and takes the camera to capture the image as input. Once the device received the photo, it could transfer the image into text. According to Goodwin, the AI-generated text are far from our normal conversation, but it does provide intriguing results. Such as “A body of water came down from the side of the street. The painter laughed and then said, I like that, and I don’t want to see it.” However, in the short film Sunspring, those ridiculous scripts become something serious with the actors’ interpretation. The play embodies the collaboration of humanity and machine algorithm.
AI in performance art
In Sougwen Chang’s Drawing Operations series, the live performance presented the collaboration between an artist and a robotic arm. During the performance, the robot perceives the artist’s drawing gestures, interpreted the information, and create its own drawing. It looks like the robotic arm is mimic the artist style, but it actually responds to the artist by its own drawing. The interaction between artist and robot arm encourages humans to change or adapt their behavior to the system. The unexpected machine feedback could trigger the artist thinks outside of the comfort zone and opens up to new ideas. On the other hand, machines can also adapt their behavior based on what humans are doing, but it is a different kind of learning than what humans do.
Some people might be scared by the art-making machine because art-making is the most human action in our history. Once we claim that machine could make art, what left for human? There are some perspectives we can think about in this scenario. First, there’s a difference between cognition and consciousness. Machines may have cognition after we fed tons of data to them, they can understand and interpret the message, but does it means they have consciousness? The spectrum between those two things is something we’re still debating.
Second, the essence of art is expressing feelings or making statements, and artists can explain the works and themselves. In the context of human-machine collaborate art, only human can interpret the generative result. Moreover, the partnership is also part of the human interpretation; the true partners can reject choices and could contribute to the concept, not only result. In reality, the machine can provide inspiring ideas and lead artist to surprising results, however, in the end, artists still have the final call, and the human interpretation completes the story.
Finally, “Algorithms are hugely powerful these days, but they’re only as good as what they’re trained on,” Anna Ridler said. In her point of view, the machine enables her to do things she wouldn’t normally be able to do, and she also enables the machine to do things it wouldn’t know how to do.
Along with human history, we always want to make something new, and this urge push human towards progress. We keep making advanced tool since the industrial revolution to shape how we work, and in many cases increases efficiency, but it sometimes constrains thoughts. AI, on the other hand, empowers us computing, understanding the data we collected and provided us to new ways of seeing. Jennifer Sukis once said, “Art is how we explore who we are and who we want to become as AI changes the picture of daily life.” With the new perspective brought by AI, we can keep on exploring the unknown territory in both technology and humanity with hybrid intelligence.
