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The world was taken by surprise when OpenAI launched the customer-focused ChatGPT 2 years ago. Since then, a lot of people and companies have incorporated it into their daily lives. GPT has seen rapid development, and the different use cases have become practically endless.

Personally, I found the most practical use in coding assistance. Before the new ChatGPT that enabled users to upload input files, it was able to provide general code that I could adjust to meet my personal objectives. This took away the annoying part of programming that forces the user to reread and write the code after receiving endless amounts of error messages, from simple syntax errors to more complex error messages. Last year I celebrated Sinterklaas with my family, and my mother experimented with creating personal poems for me and my brother using ChatGPT. While it was riddled with mistakes and was linguistically weak, it was fun to read. If we were to repeat it this year, I think we would less likely be able to distinguish a funny poem written by GenAI or my mother.

Since then, the capabilities of GPT models have exceeded those of their ancestors. I have used AI in my bachelor thesis to find synonyms or help me rewrite my text more clearly, often using figures of speech I would not have come up with. My research topic was related to the workflow of music creation and the influence of GenAI. Playing with tools like Udio AI and Suno AI and asking them to generate a song as if a classical Dutch song was sung by Surinamese people or creating personal birthday songs were a lot of fun.

Even though these tools are amazing and make us more productive, we should all be wary of the flip side of the coin. We learn from the process of not knowing and finding out, especially if you let your thoughts rest for a moment. But these GPT models take away the hurdles and provide us with the knowledge that could result in us becoming lazy.

To conclude, I believe GenAI can enrich our personal and professional lives but we have to be careful in how much we let these tools decide how our lives are going to look like.

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In the last couple of years, the world has seen the steep development curve of artificial intelligence, especially in the generative form. The transition from research to the commercial market takes place as we speak. A real-life example of this is the festival R², organised by Reinier Zonneveld (Veenhoven, 2024). He has developed AI software and played a back-to-back with his digital counterpart on the festival. The implementation of generative AI in creative industries such as music composition resulted in the creation of multiple tools. Examples of these are Suno AI and Udio AI. These tools allow the user to generate music with one simple text prompt.

A Dutch newspaper wrote an article about these apps, criticising that with these apps users are able to create songs in a matter of minutes, resulting in a flood of music that is well composed but misses the uniqueness a real artist can bring to the table. Famous artists feel threatened by these tools not only because of the competition they bring but also because of copyright infringement issues(Hijink, 2024).

While these applications use training data to develop their algorithms, it is often not allowed to use artist names in the prompt; however, with the right prompt query and a bit of luck, you can create similar songs to mimic the style of Taylor Swift by using descriptive words such as “pop, alternative folk, emotional, female vocals”(Hijink, 2024). In the United States, a bill is introduced in the US Congress that would require companies to share the training dataset with the Register of Copyrights before launcing tools with generative purposes. While its intention is not to ban training on copyrighted music completely, it should put a responsibility on these companies to provide information on the massive amounts of training data that is used and usually kept private(Robins-Early, 2024).

Personally, I think that these tools are awesome and that artists should not feel threatened by them but should embrace them in their music creation process. These tools can spark creativity and shorten the amount of time spent on components that can be replaced by AI, such as mastering the music. Another benefit of co-creating music with AI tools is that they can create different complementing music progressions that would otherwise be lost. Besides the process of music creation, I believe that people will prefer human-made music since music is a way of expressing emotions, and the experience of going to a concert of your favourite artist would not feel the same. Finally, for beginning artists and enthusiasts, these tools lower the barrier set to creating professional music.

References:

Hijink, M. (2024, May 17). Voor 2 cent per ‘liedje’ perst AI de popmuziek uit. NRC. https://www.nrc.nl/nieuws/2024/05/17/voor-2-cent-per-liedje-perst-ai-de-popmuziek-uit-a4199269
Robins-Early, N. (2024, April 9). New bill would force AI companies to reveal use of copyrighted art. The Guardian. https://www.theguardian.com/technology/2024/apr/09/artificial-intelligence-bill-copyright-art

Reinier Zonneveld, techno-dj. (2024, April 10). NPO Radio 1. https://www.nporadio1.nl/fragmenten/kunststof/9bc5c481-8048-4408-9e9b-99fd8befcbed/2024-04-10-reinier-zonneveld-techno-dj