Artificial intelligence creates art and music
If you’re a student at Carnegie Mellon, you might know about the university’s role in artificial intelligence. Although an undergraduate degree in AI hasn’t been offered until last year, Carnegie Mellon has had faculty and students involved in AI for decades. From 1956, when the first AI program was created, to the inspiration for Baymax in Big Hero 6, to the development of self-driving cars in Pittsburgh, Carnegie Mellon has been key to developments in this field.
Now, Carnegie Mellon is once again influencing the future of AI by looking into how machine learning can be used as a tool for generating art. Students of the Art and Machine Learning course have been able to create works of art from their code, even a script for traditional Chinese opera and accompanying music. But that’s only a sample of the AI arts initiatives and courses in the works, including a partnership with New York Live Arts.
Still, this avenue of creation comes with many new questions, and not as many answers. Who actually owns the rights to AI-generated art — the artist behind the concept or the programmer behind the code? What are the copyright implications for machine learning datasets that contain copyrighted works? And how will an artist’s role change in the coming years as this technology begins to creep into creative fields?
Unfortunately, we might need to wait a while for those answers, according to Brett Ashley Crawford, professor of arts management and director of the Arts Management and Technology Lab here at Carnegie Mellon. “We’re still in the first generation of artists working in these spaces… people are learning as they go to market,” Crawford said in a university press release. “There aren’t best practices or public policies yet.”
But one thing is clear: While it’s highly unlikely that robots and AI will ever replace humans, as is often feared, artists will need to look into incorporating technology into their work as time progresses. According to Crawford, “Many artists are going to have to either work with coders or learn to code.”
So, instead of taking away jobs, we can look at the use of AI tools as a new opportunity for artists. These opportunities would encourage interdisciplinary work, bringing together designers, artists, and programmers into the creative space. It also means that we might see a growth of electronic and time-based media, utilizing the power of data analytics and machine learning.