British artist FKA twigs is scheduled to testify before a US Senate subcommittee today, where she will discuss the opportunities and risks associated with AI technology in the creative industry, particularly focusing on the use of AI deepfakes.
FKA twigs expected to present a strong case for AI deepfakes
As reported by Rolling Stone, FKA twigs has submitted a written testimony advocating for the use of artificial intelligence as a creative and commercial tool, provided that artists maintain consent and control over their digital representations.
She reveals plans to deploy her own AI deepfake to manage her social media interactions while she focuses on her artistry.
According to twigs, her AI deepfake has been in development for a year and is designed to mimic her personality and voice, capable of communicating in multiple languages.
This digital version of twigs aims to extend her reach and maintain her online presence more efficiently.
However, the reward comes with great risk, the artist highlighted.
“Our careers and livelihoods are in jeopardy, and so potentially are the wider image-related rights of others in society. You have the power to change this and safeguard the future. That the very essence of our being at its most human level can be violated by the unscrupulous use of AI to create a digital facsimile that purports to be us, and our work, is inherently wrong. It is therefore vital that as an industry and as legislators we work together to ensure we do all we can to protect our creative and intellectual rights as well as the very basis of who we are,” she wrote.
Here is what it takes to generate a song using AI
AI music, an emerging technology, plays a pivotal role in this endeavour. Leveraging artificial intelligence algorithms, AI music can generate and compose unique musical pieces.
By inputting desired emotions or specific musical elements, algorithms interpret and create melodies, harmonies, rhythms, and even complete songs.
Key AI algorithms employed in this field include Markov Chains, genetic algorithms, deep learning, reinforcement learning, and recurrent neural networks, each with its own strengths and weaknesses.
AI music also integrates techniques such as Music Information Retrieval (MIR) and Generative Music Theory (GMT).
MIR analyses existing musical compositions, extracting features to generate new music, while GMT enables the creation of intricate compositions that consider the relationships between different musical elements.
By combining these approaches, AI music achieves creativity and expressiveness, producing compositions that surpass the boundaries of human creation.
