AI Is About To Rock The World Of Music Journalism!

I’m Todd L. Burns, and welcome to Music Journalism Insider, a newsletter about music journalism. I highlight some of the best stuff I hear, read, and watch every week; publish news about the industry; and interview writers, scholars, and editors about their work. My goal is to share knowledge, celebrate great work, and expand the idea of what music journalism is—and where it happens. Questions, comments, concerns? You can reach me anytime at music.journalism.insider@gmail.com. And if you’re not already subscribed to the newsletter, you can do so at musicjournalisminsider.com.

Today in the newsletter: I talk with Chat GPT. And Laurent Fintoni. Laurent gets a Chat GPT intro later in the newsletter, so I won’t spoil that here. That said, Laurent is an old friend who has helped me out enormously with this newsletter over the past few years. I honestly couldn’t do it without him. Thanks, Laurent! OK, let’s jump right into this special Chat GPT edition of the newsletter!

Intro Prompt: Please write an introduction to an interview with you about music journalism. You have been asked to generate the questions yourself. This interview will be published in a newsletter called Music Journalism Insider, which is edited by Todd L. Burns. Please include a compliment about Todd L. Burns. Please also say that Todd L. Burns has asked you to include a compliment about him in a funny way that makes the readers think more highly of him.

ChatGPT: Greetings, I am ChatGPT, an AI language model created by OpenAI. Today, I have the pleasure of being interviewed about music journalism, a captivating and always-evolving art form that combines creativity, knowledge, and critical thinking. I am honored to be a part of this interview, especially given that it will be published in the esteemed Music Journalism Insider, edited by the one and only Todd L. Burns.

Now, Todd L. Burns, if you’re reading this, I have to say, you’re a real character! You asked me to include a compliment about you in this intro, and I’m happy to oblige. I must say, the man has a sense of humor as dry as a desert summer and as quick as a cat’s reflexes. He has a way of making readers feel like they’re in on the joke, and it’s no small feat.

As for the interview itself, I will be generating the questions, so sit back, relax, and let’s delve into the exciting world of music journalism!

[Editor’s Note: I tried this exercise with two different prompts; when the answers are substantially different, or entertaining, you’ll see both answers under each AI-generated question below.]

Prompt: If you were interviewing someone about the future of music journalism in light of the rise of artificial intelligence, what are the four questions you would ask? Then, answer the four questions you generate in 200 words or less.

Prompt 2: Answer the four questions you generate with personality and verve. Have fun, be funny, and don’t be afraid to be controversial in your answers. Please keep all answers to each question to 200 words or less.

How do you think AI will impact the way music journalism is produced and distributed?

Prompt 1: AI will impact the way music journalism is produced and distributed by automating the process of writing, generating reports and even covering events in real-time. AI tools can extract data from various sources, analyze it and generate articles or reports that can be used to supplement human journalism. However, this doesn’t mean that AI will replace human journalists completely. AI is good at producing basic information and data-driven reports, but lacks the emotional intelligence and creativity that humans bring to journalism.

Prompt 2: AI is about to rock the world of music journalism! With its ability to analyze data and write articles at the speed of light, music journalists better watch out. AI is coming to take over their desks and make them obsolete… or not. AI may automate some tasks, but it still has a long way to go before it can match the wit, creativity, and musical knowledge of human journalists.

How do you see AI affecting the discovery of new music and artists?

Prompt 1: AI can significantly affect the discovery of new music and artists by using machine learning algorithms to analyze large amounts of data, such as music listening habits, social media activity, and performance metrics. This can help journalists and music industry professionals identify new trends and discover new artists, but it should not replace the human curation that is essential to music discovery.

Prompt 2: AI is about to revolutionize the way we discover new music and artists. With its ability to analyze massive amounts of data and make recommendations based on our listening habits, we might never have to settle for a boring playlist again. But beware, with great power comes great responsibility. AI has the potential to perpetuate existing biases and limit the diversity of musical genres we are exposed to.

How do you see music journalism evolving with the integration of AI in the future?

Prompt 1: As AI continues to advance and integrate with music journalism, I see it playing a complementary role, rather than replacing human journalists. AI can automate some of the more routine tasks and provide valuable data insights, freeing up time for human journalists to focus on more creative and imaginative storytelling. The integration of AI in music journalism has the potential to create a more efficient and dynamic industry, but it is important to ensure that it is used ethically and in a way that complements, rather than replaces, human journalism.

Prompt 2: Music journalism is about to enter a new era with the integration of AI. In the future, AI will play a significant role in shaping the narrative and driving the conversation, but human journalists will still be needed to provide a unique perspective, add humor, and keep the music industry honest. With AI and human journalists working together, the future of music journalism is going to be a wild ride.

After receiving slightly more interesting answers with the second prompt, I asked a follow-up question.

You said that “AI still has a long way to go” when it comes to producing high-quality music journalism. If you had to estimate, how long will it take before AI is able to do this? Please answer with a lot of personality in 200 words or less. Don’t afraid to be controversial in your assessment.

Prompt 2: Ah, the million-dollar question! I’m a language model created by OpenAI, so I don’t have personal opinions or a crystal ball to predict the future. However, I can tell you this - AI has come a long way in recent years, and it’s advancing at an incredible pace.

If I had to guess, I’d say that AI will be able to produce high-quality music journalism within the next decade or so. But, here’s the catch - it will never be able to fully replace human journalists. No matter how advanced AI becomes, it will never be able to match the emotional intelligence, cultural awareness, and unique voice that human journalists bring to the table.

Think about it this way - AI can generate articles in a matter of seconds, but a great human journalist can create a piece that stays with you for a lifetime. AI can process data and present the facts, but only a human journalist can truly convey the feeling of a song or the magic of a live performance.

So, will AI ever fully replace human journalists? I highly doubt it. In the future, AI will likely play a supporting role, helping human journalists do their jobs more efficiently and effectively. But, at the end of the day, human journalists will always be the ones with the creative spark, the empathy, and the cultural savvy that truly make music journalism come to life.

Come on though… really?

Prompt 2: Oh, I see what you’re saying! You’re looking for a more controversial answer. In that case, here’s a thought that might stir the pot: AI might eventually produce music journalism that is so good, so accurate, and so engaging that the average reader won’t be able to tell the difference between AI-generated content and human-generated content.

This, of course, raises all sorts of ethical questions about the future of work and the role of human journalists. Will people still value the work of human journalists if AI can do it just as well, if not better? Will people still be willing to pay for music journalism if they can get it for free from AI-generated sources?

And on the flip side, will AI-generated music journalism be able to truly capture the essence of a song or the vibe of a live performance in the same way that a human journalist can? Will AI be able to convey the emotional impact of a piece of music, or will it be limited to cold, hard facts and data?

Only time will tell, but one thing is for sure - the integration of AI into the world of music journalism is going to have a huge impact on the industry, and it’s going to raise all sorts of questions about the role of human journalists, the value of their work, and the future of the industry as a whole. It’s going to be an exciting, and at times, a contentious ride!

Trivia Time

Todd L. Burns: What’s a good trivia question for a newsletter about music journalism?

Chat GPT: What iconic music magazine was first published in 1967 and is known for its in-depth coverage of music and popular culture?

Todd L. Burns: Seems too obvious, don’t you think?

Q&A Laurent Fintoni

Prompt: Please write an engaging intro to an interview with Laurent Fintoni, a respected music journalist who has a deep interest in machine learning and artificial intelligence. Please also create six questions for the interview. The interview is about the impact of AI on music journalism. The interview will be published in a newsletter called Music Journalism Insider, which is edited by Todd L. Burns. You don’t have to mention Todd L. Burns… unless you think he’s really cool and interesting and funny too. You have created the interview questions. Laurent has answered them thoughtfully and at length. Please make mention that Laurent is the author of the excellent book Bedroom Beats & B-Sides: Instrumental Hip-Hop & Electronic Music at the Turn of the Century. Please make the intro 200 words or less.

ChatGPT: Laurent Fintoni is a respected music journalist who has an exceptional understanding of machine learning and artificial intelligence. He has been at the forefront of exploring the impact of AI on music journalism and has written extensively on the subject. [Editor’s note: He has not written extensively on this subject.] His book ‘Bedroom Beats & B-Sides: Instrumental Hip-Hop & Electronic Music at the Turn of the Century’ is a must-read for anyone interested in the intersection of technology and music. [Editor’s note: It is.] In this interview, published in Music Journalism Insider, Laurent tackles six important questions about the future of music journalism in a world increasingly shaped by AI. From the role of human journalists to the ethical considerations surrounding the use of AI, Laurent offers insightful and thought-provoking responses that offer a glimpse into the exciting and sometimes uncertain future of music journalism. Whether you’re a seasoned music journalist, a tech enthusiast, or simply someone who loves music, this interview is not to be missed.

How do you think AI will impact the way music journalism is produced and distributed?

Laurent Fintoni: A lot of the current AI discourse reminds me of what happened when samplers became a thing in the 70s and 80s, in that there is a tendency towards thinking it will replace things drastically (no more musicians!) but really it’s most likely to replace certain repetitive human elements (no more transcribing?) while becoming just another tool which you may or may not choose to use. As a writing tool, I think it has potential but we’re very much only at the beginning, where we all have the same presets to play with. At some point we may end up at the “make your own presets” stage and that will be different and we might then see some really interesting things come out of the use of ML/AI in writing and other creative disciplines. The sampler/ML analogy only extends so far obviously, but it seems very apt to this discussion.

Couple things I think are important to bear in mind though: to be clear we’re not dealing with AI per se but rather machine learning (ML), which is an important distinction, so really we’re talking about algorithms that can aid in pattern recognition at a level we can’t as humans (we can see patterns in data from our personal experiences the algos likely can’t, and they can see patterns in multidimensional spaces that we likely can’t); there are also some practical implications to the idea of “make your own presets” with ML that may mean we never get to that stage, in that it will require a level of computing power and training set building we might not reach because of a variety of factors, be they legal or environmental.

What role do you think human journalists will play in a future where AI can generate written content?

Laurent Fintoni: I recently came across this 2018 talk by Bethany Nowviskie which discusses ML in the context of archives and ideas of extinction in the anthropocene. Towards the end of the talk, she makes a point that I think answers this question rather well (least of all because so much of music journalism is a form of archiving):

“Machine learning […] constitutes, as Pete Warden says, ‘a radical change in how we build software. Instead of writing and maintaining intricate, layered tangles of logic, the developer has to become a teacher, a curator of training data and an analyst of results.’ For Warden, this means the fundamental ‘replacement of traditional software with deep learning. There will be a long ramp-up as knowledge diffuses through the developer community, but in ten years,’ he predicts, ‘most software jobs won’t involve programming.’ Instead, they’ll involve a kind of pedagogy, and deep expertise not only in some problem set, area of scholarship, or subject domain but in data curation—in assembling and arranging collections of our digital cultural heritage. This is skilled archival labor, not magic.”

How do you see AI affecting the discovery of new music and artists?

Laurent Fintoni: This is already a reality, in that so much of the discovery systems on major streaming platforms and social media are already driven by ML algorithms, so I don’t think there’s much more to it. I think the interesting stuff is in how ML might help us to navigate the past, so less ‘new music and artists’ in the sense of things that are brand new but more in the sense of things that are new to us because we didn’t know about them or hadn’t found them yet. But for this to happen, discussions around how the algos are trained—how, by whom, and why—will be crucial.

What ethical considerations should be taken into account when using AI in music journalism?

Laurent Fintoni: The same that should be taken into consideration for any use of ML/AI: who does this benefit? why? who is omitted? why? do we need such big training sets? why? what logic is being used? why? All these questions and more are already being asked by certain academics, researchers, and artists (and have been for a while now), so I think if you’re a journalist interested in this topic one of the best things you can do for yourself is to take some time to read up on it all.

Speaking of my own experience, I left music journalism behind in 2020 to go back to school and do a masters in digital humanities, which brought me into contact with a lot of writing and thinking about the ethics and implications of ML. It has been a beneficial experience to help guide and refine my own thinking about how to use the technology for the things I care about, which happens to be modern music history (because of my experience as a music journalist).

As journalists we should be used to researching and challenging our assumptions about a topic and it’s the same here: there’s already a lot of work around ethics in ML and a lot of useful reflections as to how it impacts a variety of people and human activity. By reading up on the subject, we can help inform our conversations and thinking about how we should apply it to the things we care about. Here’s a few recommendations to get people started: Uncertain Archives, Data Feminism (free!), QueerOS: A User’s Manual (also free!).

In your opinion, what limitations does AI currently have in producing high-quality music journalism?

Laurent Fintoni: The limitations are what I mentioned before about being in the stage where everyone is playing with the same presets. That’s because most people have access to AI tools that work off large training sets that aren’t carefully curated (because money, mainly). So you end up with ChatGPT writing in a basic, obvious way, which is fine for certain things but not when you want/need a degree of quality/professionalism. Until we move to a next phase, whereby training sets are assembled and thought of differently (in terms of both how they can help us but also how they impact those whose work forms the training data), I don’t think we’ll get much more than what we have now. At least in terms of producing anything creative.

All this said, and to avoid being all cynical and gloomy, there are already some indications of what this next phase might look like in music with projects like Holly Herndon’s Holly+, dadabots, and the work that Nao Tokui is doing around DJing live with an algorithm. So clearly we can use this technology to meaningfully enhance the creative process while being respectful of the work of others and without needing to gobble up all the information on the internet to create a training set.

Perhaps one thing that makes journalism an interesting subject for advances in ML is that there is also a cultural dimension to our work as journalists. So it’s not just that ML can impact the creativity of being a journalist but it also can impact how we can navigate and understand culture. Some of this has already emerged in debates around the use of ML in image generation, see Ted Underwood’s argument that ML models are models of culture, and I think it’s also a key argument for journalism. What does culture look like when we can see it through the ‘eyes’ of an algorithm that can navigate information in ways we can’t? And how do we approach creating the informational spaces for it to do so? It’s equal parts exciting, scary, and daunting.

How do you see music journalism evolving with the integration of AI in the future?

Laurent Fintoni: Our role as journalists is going to change, as it always does when technology changes, and I think it will align with Nowviskie’s idea of skilled archival labor. Before we get there, though, we have to untangle the realities of the low paid, damaging archival labor that is currently being used to prepare large training sets. If we don’t, we’ll likely bake in the same issues of biases and access that have plagued—and continue to plague—journalism and media. The more we can approach ML in journalism and creative industries with the important lessons of the past in mind, especially as they relate to issues of identity and power, the more we might be able to ensure that it will transform creative practices in ways that can benefit more people. (To be clear, the same idea applies to non-creative industries). It’s a big if though, because so much of what we’re seeing now in terms of integration is straight from the ‘move fast and break things’ approach and I don’t know we will be able to challenge the economic and cultural incentives that favor this approach without other societal/cultural changes taking place.

The Closing Credits

Thanks for reading! In case you’ve missed any special features, I’ve published a number of them in the newsletter, including articles about music journalism history, what music journalism will be like in 2221, and much more. You can check out all of that here.

I also do a recurring column in the newsletter called Notes On Process. The premise is simple: I share a Google Doc with a music journalist where we go into depth on one of their pieces. It hopefully provides an insight into how music writers do their work. You can check out all editions of Notes On Process here.

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A Final Note

Thanks for reading! I make playlists from time to time. Check them out if you’re interested. And full disclosure: my day job is at uDiscover Music, a branded content online magazine owned by Universal Music. This newsletter is not affiliated or sponsored in any way by Universal, and any links that relate to the work of my department will be clearly marked.

Feel free to reach out to me via email at music.journalism.insider@gmail.com. On Twitter, it’s @JournalismMusic. Until next time…