Let’s take a closer look at the possibilities of using AI in creative industries.
Artificial Intelligence is slowly and steadily becoming a part of people’s imaginations and has even seeped into the realm of art. From writing symphonies to painting pictures, even creating patterns in software, algorithms are walking into the conception. But how are these algorithms changing art and music:
AI’s entry into creativity started with the machine learning and neural network – systems that simulate the learning patterns of the brain. These algorithms are fed massive inputs of data; therefore, it is possible to make sense of patterns, learn from cases, and invent. In the creative arts, it applies in the sense that it can design new music, art and design from the information fed into the system.
In the context of this research, algorithms are seen as the new age composers that have replaced the traditional composers.
AI is proving to be useful in the generation of new music pieces as it creates works of art that can easily be passed off for human authored music. Applications such as AIVA (Artificial Intelligence Virtual Artist), and JukeDeck are capable of using deep learning to produce brand new tracks of music. These AI composers learn from thousands of classical and modern music pieces and thereby understand different facets of music like the theory of the same, rhythm, harmony and even the passions that content LIImAX in music they compose.
One of the examples of how outstanding AI is as a composer is the song “Daddy’s Car” developed by Flow Machines from Sony company. The input was a dataset of Beatles songs and the algorithm provided this generation which has the feel of 1960’s pop music. Such is the retro and innovative at the same time, the work of an AI, which can both translate specific styles and generate new ones.
Yet the implementation of AI to music brings up copyright and ownership issues. If a machine produces a piece of music then who benefits from it? There are two positions in the case of the algorithm, and they are that of a co-composer and co-composer as tool. Such discussions are defining the legal and ethical boundary of artificial intelligence in music and disrupting the concepts of creativity and authorship.
It is not only in galleries but also in digital marketplaces that AI generated art has a prominent place in visual arts. One of the most common methods of creating art is using Generative Adversarial Networks (GANs). These algorithms involve two neural networks – the generator and the discriminator - which operate together to create images. While the generator generates images, the discriminator evaluates them resulting in an endless cycle of improvement and refining.
Prominent artists such as Refik Anadol and Mario Klingemann have utilized GANs to produce strikingly beautiful abstract works that challenge conventional perceptions of visual language. For instance, Anadol primarily works with data feeding it into AI systems to generate smooth flowing real-time graphics which are projected on large screens. His work straddles across both data science and visual art making it an immersive experience that is as much about technology wonderment than it is simply beautiful.
Furthermore, NFT market has successfully capitalized on AI generated art where digital artworks are transacted via blockchain platforms. The use of Ai by artists or creators helps in producing pieces which are innovative in nature but digital scarcity tends to increase their worthiness for money-makers.
The rise of AI-powered creativity poses a crucial question: will algorithms replace human artists, or will they serve as collaborators? While AI can mimic styles, generate novel compositions, and even produce visually striking art, it lacks the human experiences, emotions, and intentions that often drive artistic expression.
