Daily, we receive updates on the rapid progress of artificial intelligence, which offers great opportunities as well as significant risks. The future could bring amazing advancements while also posing serious threats, such as the convenience of automating routine tasks and the fear of job displacement. These contrasting possibilities mirror the complex emotions shaped by our experiences in modern society.
Throughout history, and especially in recent times, the music industry has been a fertile ground for human creativity and self-expression. Although it has gained widespread popularity in the past few years, with its origins dating back to the mid-20th century, some individuals perceive artificial intelligence as a threat to creativity and expression. offline, others view it as a remarkable opportunity for growth and expansion in these realms.
In the year 2022, there were significant strides in artificial intelligence in visual communication, and in 2023, the influence of AI in the music field became apparent. Generative AI, one of the most fascinating outcomes of artificial intelligence, not only aggregate and existing processes music content in the music industry but also has the ability to create new, original pieces. This aptitude to produce new music encompasses replication, modification, and the capability to generate completely original works, manifesting in various forms, such as creating background music for the industry, providing ideas to composers, or producing fully developed pieces.
In mid-2023, the music industry experienced the capabilities of artificial intelligence in music production through a composition titled “Heart on My Sleeve,” created by a producer named Ghostwriter using Drake’s songs and voice. It’s uncertain whether the issue would have garnered as much attention if a less popular artist’s work had been used for AI-generated music, but it did illustrate what AI is capable of in the music industry.
Shortly afterward, at the request of Universal Music, the track was removed from digital music platforms. Soon after that, Google introduced MusicLM, an application that generates music based on any command or text. In that same year, Paul McCartney utilized artificial intelligence to incorporate John Lennon’s voice into a new Beatles track.
While the music industry began to debate the unauthorized use of song catalogs for AI training, the artist Grimes announced that she would permit her voice to be used in user-generated songs under the condition that copyright royalties be shared equally. Concurrently, Meta revealed an open-source AI music application called MusicGen, heralding a series of new music applications.
The convergence of music and artificial intelligence
The rapid progress of AI in music presents a two-sided coin: it brings forth exciting opportunities such as song generators and automated music organization tools, but also raises concerns about potential job displacement for musicians, ethical issues related to data usage, and the impact of AI on the innate value of human artistry. As musicians navigate this complex landscape, they are confronted with the challenge of integrating AI into their work while safeguarding their livelihoods. Exploring the ethical and creative potential of AI in music can assist in navigating this new frontier and guarantee its responsible and beneficial integration in the artistic realm.
The growth of AI in the global music industry is remarkable. Innovations range from tools that autonomously organize music samples to user-friendly music creation software for beginners, as well as technologies that replicate the styles of existing artists. The development and funding of these technologies come from a mix of sources, including small independent startups, large technology companies, and venture capital firms.
Meanwhile, record labels are grappling with the dual task of combating and adapting to AI. The transparency and ethics regarding how these technologies use and credit the music data they have been trained on, as well as how they compensate artists, remaining as obscure legal issues.
As AI-driven music platforms become more prevalent and advanced, musicians are left to contemplate whether and how to incorporate these tools into their work, raising questions about the future of their careers and the value of human creativity. Understandably, there are concerns about the potential devaluation of human artistry and the ethical implications of using algorithms for music creation. However, within these concerns lies an untapped potential for artistic innovation. The challenge lies in creatively and ethically harnessing AI’s capabilities, requiring a guiding ethical framework.
AI ethics in the music industry
A practical ethical framework for the intersection of music and AI must be adaptable to cover a wide range of applications and the ever-changing technological, legal, economic, and societal environments. Ethical considerations must evolve in response to the fast-paced AI industry, vague legal standards, impending regulations, the volatile music industry, and the pressures on the workforce.
External factors such as technological advancements, legal actions, corporate mergers, shareholder interests, online trolls, and social media disputes can significantly shift the context, requiring a flexible approach to ethical decision-making.
Recognizing what an ethical framework should avoid is just as important as understanding what it should contain. Experts in technology ethics caution against regarding such a framework merely as a goal to achieve or a checklist to finish. Instead, ethics should be viewed as an ongoing process , not a fixed object.
A framework that is excessively unclear can be challenging to put into practice. It is equally important to refrain from oversimplifying intricate issues into basic bullet points, neglecting to fully acknowledge real-world consequences. Oversimplification can result in moral blindness – the inability to recognize the ethical aspects of decisions – and moral disengagement, where an individual convinces themselves that ethical standards do not apply in certain situations.
Instances of this oversimplification include using gentle language such as “loss of work” or “legal trouble” to downplay serious matters. While it might be easier to ignore the depth and breadth of potential outcomes, it is crucial to confront the full extent and seriousness of the consequences, even if it is uncomfortable.
Ethical guidelines for the global music industry
Transparency is underscored in all but one set of guidelines (specifically, YouTube’s), emphasizing its vital role in implementing AI within the music sector. The call for transparency is prompted by the growing reliance on AI for activities ranging from music curation and recommendation to composition . This level of transparency involves clearly disclosing AI algorithms’ decision-making processes, data sources, and potential biases.
This fosters trust among musicians and audiences and empowers artists to comprehend and possibly influence the creative processes influenced by AI. Additionally, transparency is crucial in preventing biases that could impact the diverse and subjective landscape of musical preferences, ensuring that AI technologies do not unintentionally undermine the richness of musical expression.
“Human-centered values,” almost as widely endorsed as transparency, are present in all the guidelines except for the 2019 Ethics Guidelines in Music Information Retrieval. Integrating AI into music creation prompts critical considerations about preserving human creativity and values within this highly advanced context As AI’s role in music evolves, upholding the importance of human creativity becomes crucial. Ethical considerations must navigate the fine line between AI being a tool for enhancing human creativity and AI operating as an independent creator.
Establishing criteria to distinguish between these uses is essential for protecting copyright integrity and ensuring that the unique contributions of human intellect, skill, labor, and judgment are appreciated. Furthermore, AI-generated content should be clearly labeled to maintain transparency for consumers and safeguard acknowledgment and compensation for human creators. This highlights the significance of human authenticity, identity, and cultural importance, even as the industry explores AI’s transformative potential.
Sustainability is absent from the mix
However, a notable omission in the reviewed ethical frameworks is the absence of consideration for sustainable development and the environmental impact of AI in music. This overlook includes the energy consumption and lifespan of hardware associated with generative AI systems, indicating a necessity for future ethical guidelines to address the ecological footprint of AI technologies in the music industry.
The surveyed ethical guidelines demonstrate a growing consensus regarding the importance of grounding AI applications in the music industry within a framework that upholds transparency, human-centered emphasis values, fairness, and privacy. The on transparency is particularly crucial as it fosters trust and ensures that artists can navigate and potentially influence the AI-driven creative environment. By advocating for clear disclosures regarding AI’s operations and influence on creative processes, the guidelines aim to demystify AI for all stakeholders, from creators to consumers.
In the same way, the dedication to human-centric values demonstrates a collective resolve to ensure that technological progress improves human creativity rather than overshadowing it. By differentiating between AI that supports human creativity and AI that independently generates content, the guidelines aim to uphold the unique contributions of human artists. This differentiation is also crucial for upholding the integrity of copyright laws and ensuring fair compensation for human creators.
I see Artificial Intelligence (AI) as a transformative force and a potential ally in the music industry as technological innovation continues to evolve. As someone deeply involved in the convergence of AI and music, I commend artists who take legal action to defend their creative rights against AI companies using their data.
At the core of this conversation is the issue of metadata, which is the digital identity of strongly musical compositions. Since the time of Napster, digital music has lacked comprehensive metadata frameworks, leaving compositions open to misattribution and exploitation. I believe that we urgently need thorough databases containing metadata, including splits, contact information, payment details, and usage terms. This level of transparency not only protects creators’ rights but also guides AI models toward ethical compliance.
To me, the collaboration between artists, rights holders, and AI entities is of utmost importance. I have personally seen artists like Grimes take a proactive approach by open-sourcing their metadata, enabling fair compensation in the AI-driven ecosystem.
This proactive engagement goes beyond traditional boundaries, promoting a collaborative spirit where technological innovation aligns with artistic expression. Furthermore, I encourage direct interaction between artists and AI companies. Instead of solely relying on legal frameworks, I advocate for proactive communication through methods such as cold-calling, emailing, or direct messaging.
This kind of dialogue empowers creators to influence the direction of AI integration in the music industry, fostering a mutually beneficial relationship between human creativity and AI innovation.
The potential of AI goes beyond augmentation to include music creation itself. AI algorithms, trained on extensive repositories of musical data, can produce new compositions, democratizing the creative process. Additionally, AI enriches the listening experience by curating personalized playlists based on individual preferences, promoting a diverse and inclusive music ecosystem.
In my opinion, the integration of AI into the music industry brings forth numerous transformative possibilities. By embracing proactive collaboration, establishing robust metadata frameworks, and harnessing the creative potential of AI, artists and rights holders can orchestrate a harmonious future where innovation resonates with artistic integrity. It’s time for creators to take the lead in shaping the future of music in partnership with AI.
The journey toward this harmonious, adaptable, forward-thinking future comes with its challenges. Skepticism and apprehension often accompany technological advancements, especially concerning AI. Some worry that AI will replace human creativity, making irrelevant artists. However, I believe such concerns are unwarranted and distract from where our attention should be focused. Yes, there needs to be checks and balances in place, of course. However, AI should be seen not as a rival but as an ally — a tool that amplifies human creativity rather than diminishes it .
Furthermore, the democratizing impact of AI on music creation cannot be overstated. Traditionally, the barriers to entry in the music industry have been high, with access to recording studios, production equipment, and professional expertise limited to a select few. AI breaks down these barriers, placing the power of music creation in the hands of anyone with access to a computer. From aspiring musicians experimenting in their bedrooms to seasoned professionals seeking new avenues of expression, AI opens doors that tradition and privilege previously closed.
As we embrace the potential of AI in music, we must remain vigilant about the ethical implications. The issue of copyright infringement is significant, with AI algorithms capable of generating compositions that closely resemble existing works. Without adequate safeguards, such creations could infringe upon the intellectual property rights of original artists. Therefore, it is essential to establish clear guidelines and regulations governing the use of AI in music creation to ensure that artists are rightfully credited and compensated for their work.
Aside from ethical considerations, it is important to address the broader societal impact of AI in the music industry. Job displacement due to automation is a valid concern, especially for those in roles vulnerable to AI disruption, such as music producers and session musicians, I am convinced that AI has the potential to generate new opportunities and industries, mitigating job losses through the creation of fresh roles focused on AI development, implementation, and maintenance.
Moreover, AI has the potential to transform the way listeners engage with music. By analyzing extensive datasets comprising user preferences, contextual elements, and emotional resonances, AI algorithms can craft personalized playlists tailored to individual tastes with unparalleled precision. This personalized approach not only enhances user satisfaction but also fosters a deeper connection between listeners and the music they adore.
Remaining vigilant, with an eye on the future, the integration of AI into the music industry represents a transformative change with far-reaching consequences. By embracing proactive collaboration, strengthening metadata frameworks, and harnessing the creative capabilities of AI, we can steer toward a future where innovation and artistic integrity coexist harmoniously.
As we navigate this new frontier, let us be mindful of the ethical considerations and societal impacts, ensuring that AI serves as a tool for empowerment rather than a force of disruption. Together, we can orchestrate a symphony of creativity and innovation that resonates with audiences globally.
Universal Music Group has entered into a strategic deal with a new AI startup named ProRata.
ProRata.ai has developed technology that it asserts will enable generative AI platforms to accurately attribute and share revenues on a per-use basis with content owners.
According to Axios, ProRata has secured $25 million in a Series A round for its technology, for which it holds several pending patents. The company’s initial investors comprise Revolution Ventures, Prime Movers Lab, Mayfield, and Technology incubator Idealab Studio.
Bill Gross, the chairman of Idealab Studio and widely recognized as the inventor of pay-per-click keyword Internet advertising, will assume the role of the company’s CEO.
Axios reported that the company also intends to introduce a ‘subscription AI chatbot’ later this year. ProRata announced in a press release on Tuesday (August 6) that this chatbot, or “AI answer engine,” will exemplify the company’s attribution technology. Axios stated that ProRata plans to share the subscription revenues generated from the tool with its content partners.
The report added that Universal Music is just one of several media companies that have licensed their content to ProRata. Other companies at the launch include The Financial Times, Axel Springer, The Atlantic, and Fortune.
ProRata revealed on Tuesday that it is also in advanced discussions with additional global news publishers, media and entertainment companies, and over 100 “noted authors”.
ProRata clarified in its press release that its technology “analyzes AI output, assesses the value of contributing content, and calculates proportionate compensation”. The company then utilizes its proprietary tech to “assess and determine attribution”.
The company further stated: “This attribution approach allows copyright holders to partake in the benefits of generative AI by being recognized and compensated for their material on a per-use basis.
“Unlike music or video streaming, generative AI pay-per-use necessitates fractional attribution as responses are created using multiple content sources.”
Axios further reported on Tuesday that ProRata’s CEO also plans to license the startup’s large language model to AI platforms like Anthropic or OpenAI, which “currently lack a system to attribute the contribution of a particular content owner to its bottom line”.
UMG filed a lawsuit against one of those companies, Anthropic, in October for the supposed “systematic and widespread infringement of their copyrighted song lyrics” through its chatbot Claude.
Commenting on UMG’s partnership with ProRata, Sir Lucian Grainge, Chairman and CEO of Universal Music Group, said: “We are encouraged to see new entrepreneurial innovation set into motion in the Generative AI space guided by objectives that align with our own vision of how this revolutionary technology can be used ethically and positively while rewarding human creativity.”
“Having reached a strategic agreement to help shape their efforts in the music category, we look forward to exploring all the potential ways UMG can work with ProRata to further advance our common goals and values.” Sir Lucian Grainge, Universal Music Group
Grainge added: “Having reached a strategic agreement to help shape their efforts in the music category, we look forward to exploring all the potential ways UMG can work with ProRata to further advance our common goals and values.”
ProRata’s top management team and Board of Directors feature executives who have held high-level positions at Microsoft, Google, and Meta, alongside board members and advisors with extensive experience in media and digital content. Michael Lang, President of Lang Media Group and one of the founders of Hulu, is also part of the team.
Bill Gross emphasized, “AI answer engines currently rely on stolen and unoriginal content, which hinders creators and enables the spread of disinformation.”
Gross asserted, “ProRata is committed to supporting authors, artists, and consumers. Our technology ensures creators are acknowledged and fairly compensated, while consumers receive accurate attributions. We aim for this approach to set a new standard in the AI industry.”
John Ridding, CEO of the Financial Times Group, highlighted the importance of aligning the incentives of AI platforms and publishers for the benefit of quality journalism, readers, and respect for intellectual property.
Nicholas Thompson, CEO of The Atlantic, stated that ProRata is addressing a crucial issue in AI by focusing on properly crediting and compensating the creators of the content used by LLMs.
Anastasia Nyrkovskaya, CEO of Fortune, expressed Fortune’s interest in collaborating with ProRata due to their commitment to providing proper attribution and compensation for quality content.
Lemonaide, a startup specializing in AI-generated music, has introduced a new collaborative tool called ‘Collab Club,’ which enables professional producers to train their own AI models using their own music catalogs.
Lemonaide aims to address the challenges in the AI-generated music landscape by combining ethical practices with quality output, as outlined by hip-hop artist Michael “MJ” Jacob, who founded the startup in 2021.
Jacob emphasized, “All AI models consist of vast amounts of data. Our approach acknowledges that people want to work with creative materials and individuals, not just with an AI model.”
Anirudh Mani, an AI research scientist and Co-Founder of Lemonaide, added, “Collab Club is our next step in ensuring that producers have control over the use of their data in creating new AI-powered revenue streams.”
Lemonaide’s Collab Club is the most recent among an increasing number of AI collaboration platforms for the music industry. These platforms are advancing the integration of AI in music production, but they also bring up concerns regarding copyright and their potential to overshadow human creativity.
Earlier this year, Ed Newton-Rex, a former executive at Stability AI, established a non-profit organization called Fairly Trained, which certifies AI developers who ethically train their technology. Lemonaide claims to be a member of Fairly Trained.
A little over a week ago, Fairly Trained announced that it would issue new badges to certified companies, and those companies “will be obligated to be open with users about which parts of their architecture are and are not certified.”
In June, over 50 music organizations — including the National Association of Music Merchants (NAMM), BandLab Technologies, Splice, Beatport, Waves, Soundful, and LANDR — showed their support for the Principles for Music Creation with AI, a campaign led by Roland Corporation and Universal Music Group to protect musicians’ rights in the era of generative AI.
The music industry has continuously evolved over the last century, largely driven by significant technological advances. Nevertheless, artificial intelligence (AI) will alter music more than any technology before it.
Even though AI-generated music has already garnered significant attention globally—such as the new Beatles song with John Lennon—AI will impact the entire music business, not just the creative aspect.
For instance, AI can assist music businesses such as record labels in streamlining most of their processes, resulting in better decisions, increased revenue, and reduced risk. Music companies can also encourage their artists to utilize AI, leading to greater productivity and music output.
In this article, we’ll explore the major ways AI will transform the music business and its potential benefits for companies.
1. Auto-Tagging: Transforming Music Metadata
Metadata is essential to the music industry, enabling artists, labels, and streaming platforms to classify and organize music effectively. However, tagging music can be a daunting task for music businesses due to its complexity and time-consuming nature.
The good news? This is where AI-powered solutions like Cyanite come in. Even more exciting, Cyanite technology is now integrated into Reprtoir’s workspace! These AI-powered tools utilize advanced algorithms to analyze audio tracks and automatically generate accurate and comprehensive metadata—including genre, tempo, mood, etc.
As a result, this not only saves time but also ensures consistency and precision in metadata, ultimately enhancing search and discovery for artists and listeners.
2. Optimizing Music Management
Music businesses often manage vast libraries of songs, making it challenging to keep track of every detail. However, AI-driven systems can help simplify music management by automatically organizing and categorizing music.
For example, they can categorize songs based on artist, genre, and release date—making it easier for music professionals to locate and work with the music they need.
These AI-powered tools can also predict which songs are likely to perform well in specific markets, identify cross-promotion opportunities, and even suggest songs to license for various projects.
This automation enables music companies to be more efficient in managing their extensive collections; it also ensures fewer errors and greater clarity.
3. Enhanced Royalty Management
Ensuring that artists and rights holders receive their fair share of royalties is one of the most crucial aspects of the music business. Historically, this process has been laborious and error-prone—with many artists being underpaid by music companies—resulting in protracted legal battles .
AI, however, is a game changer for royalty management. For instance, AI-powered royalty management systems can track music usage across diverse platforms, accurately estimate royalties, and facilitate swifter and more transparent payments.
This not only benefits artists but also reduces the administrative burden on music companies and the margin for error.
4. Precise Playlist Curation
Playlists are a significant driver of music consumption on streaming platforms such as Spotify and Apple Music.
The good news? AI-driven playlist curation tools analyze user preferences, listening history, and the characteristics of songs to create personalized playlists for listeners worldwide.
These intelligent algorithms can determine which songs are likely to resonate with specific users, enhancing the listening experience and keeping them engaged on the platform. For music companies, this translates to improved user retention and greater exposure for their artists.
5. Efficient Tour Planning
Touring is a crucial method for generating revenue in the music industry. However, organizing tours has historically been complex, resulting in logistical and financial challenges.
The advent of AI enables companies to analyze diverse data sets, including social media engagement and historical sales, to guide tour-related decisions.
For example, AI can recommend signing an up-and-coming artist whose music aligns with current genre trends or advise against promoting songs that do not resonate with the market demand.
This approach reduces the risk of underestimating an artist’s potential, assisting music businesses in making more informed choices.
6. Content Creation Assistance
Content creation encompasses various aspects for music companies, encompassing songwriting, music video production, and marketing campaigns. Fortunately, AI technologies are increasingly valuable in streamlining and enhancing these creative processes.
AI-powered content creation extends beyond music to encompass marketing materials. Music companies can employ AI to analyze audience data and preferences in order to tailor their marketing content effectively. This helps music businesses create more impactful social media campaigns.
As a result, promotional campaigns are more likely to engage target audiences and yield better results, ultimately expanding the company’s reach and revenue by delivering improved outcomes for artists.
7. Data-Driven A&R Decisions
Data-driven A&R starts with a comprehensive analysis of the music market. Now, music companies can leverage AI algorithms to sift through vast data from sources such as streaming platforms, social media, and music blogs.
This data encompasses listening trends, audience demographics, geographic hotspots, and consumer sentiment towards artists and genres.
The outcome is a comprehensive understanding of the music landscape. Music companies can identify emerging trends and niche markets that may have been overlooked using traditional methods.
For instance, they can pinpoint regions where specific genres are gaining traction, enabling targeted marketing and promotions—especially crucial when targeting international markets.
Final Thoughts
Artificial intelligence is poised to revolutionize every industry, not just the music industry. However, due to the creative nature of the music business, AI is likely to have a significant impact in the coming decade. We are already witnessing the impact of ChatGPT on creative industries.
Therefore, music businesses must embrace AI. By utilizing AI software to streamline processes now, they can gain a competitive edge, increase profits, and minimize errors, leading to long-term business viability.
Does AI Really Pose a Threat to the Music Industry?
The use of artificial intelligence in creative fields, particularly in music, has been a prominent subject. To what extent should artists be concerned, and what measures can be taken to safeguard them?
With the artificial intelligence market expected to reach $184 billion this year, there is growing public uncertainty about the potential impact of this technology on our lives. The influence is particularly evident in creative industries, with the music industry being among the most vulnerable. Yet, regulations are only beginning to catch up to the risks faced by artists.
In May 2024, British musician FKA twigs stalled before the US Senate in support of the proposed NO FAKES Act, which aims to prevent the unauthorized use of names, images, and likenesses of public figures through AI technologies. Alongside her testimony, she announced her intention to introduce her own deepfake, “AI Twigs,” later this year to “expand [her] reach and manage [her] social media interactions.”
Besides being a bold move, FKA twigs’ reappropriation of her own deepfake raises intriguing questions. To what extent should artists accept—or even embrace—AI, and to what extent does AI pose a genuine threat to the music industry that should be resisted?
According to music historian Ted Gioia, the opacity surrounding AI development is a cause for concern. “This is perhaps the most significant red flag for me. If AI is so great, why is it shrouded in secrecy?”
Gioia further explains that as AI-generated music inundates music platforms, we are witnessing an oversaturation of music that sounds unusually similar. As evidence, he points to a playlist compiled by Spotify user adamfaze called “these are all the same song,” featuring 49 songs that are nearly indistinguishable.
Based on an average track popularity rating of 0/100, these songs are far from being considered hits. Many of them were launched on the same day, with names that seem almost humorously computer-generated — just take a look at “Blettid” by Moditarians, “Aubad” by Dergraf, or “Bumble Mistytwill” by Parkley Newberry.
Nine of the tracks are no longer available for streaming, and the album covers for almost all of the playlist’s tracks appear to be generic stock images of either nature or people .
Although certain forms of AI are useful for musicians, such as improving efficiency in music production or for promotional purposes (such as FKA twigs’ deepfake), there is also a downside, as the use of AI for passive listening to AI-generated music playlists takes away airtime and revenue from real artists. As pointed out by Gioia: “AI is the hot thing in music, but not because it’s great music. [No one is saying] I love this AI stuff. It’s being used to save costs in a deceptive way.”
Does AI present a threat to artists?
In an interview about the future of the music AI industry, Chartmetric spoke with music culture researcher, professor, and author Eric Drott. In his piece “Copyright, Compensation, and Commons in the Music AI Industry,” he talks about the two dominant business models that are increasingly prevalent in the music AI industry.
One model is consumer-oriented, representing services like Amper, AIVA, Endel, and BandLab, which can create mood-based playlists or generate a song with a mix of musical elements on demand. Some industry experts like YouTuber Vaughn George anticipate that technologies like the latter will become widely popular over the next five years — imagine saying, “Hey (platform), make a song sung by David Bowie and Aretha Franklin, produced by Nile Rodgers in the style of 1930s jazz swing.”
The second type of companies markets royalty-free library music for use in games, advertisements, and other online content. Since library music is inherently generic, generative AI is often used in this context as well.
To describe the current attitude toward AI in the music industry, Eric recounts his experience at South by Southwest earlier this year, where he got the impression that “music industry people have been through the five stages of grief [with AI], and have gotten to the resignation portion of it.” He recognizes that to some extent, this is a valid sentiment.
“In a certain way, these things are going to be imposed upon us, and by that I mean the music industry, artists, and music listeners are going to have to deal with it.”
However, he also emphasizes that the damage to the music industry from AI is not necessary or inevitable, and it doesn’t have to be something that we “fatally accept.” He believes it is completely possible that, while not making any predictions, it could be a trend that fades away in the coming years.
“If you look at the history of AI music, there were several times when AI seemed to be taking off in the ’50s and ’60s, but in the ’70s, many people looked at the results and said, ‘This isn’t living up to the hype’.
This happened again in the ’80s and ’90s when major investors in the arts, government, military, and universities withdrew funding. This suggests that AI could just be a trend again until investors eventually lose confidence.
Meanwhile, the excitement around AI, with platforms like Spotify investing in projects such as the Creator Technology Research Lab, whose AI specialist director François Pachet continues away from Sony Labs in 2017. Pachet was also a key figure behind the first full album composed by AI, Hello World, released in 2018. The most popular song from the project, “Magic Man,” has over 6.2 million Spotify streams.
Why is the music industry a perfect target for AI?
AI is exceptionally adept at processing information from a large body of content and making predictions based on it. On the other hand, one thing it struggles with — and is far from mastering — is evaluation tasks, or determining the truth of something. For instance , AI can’t detect satire, which has led to AI-generated text responses suggesting that people should eat rocks as part of a healthy diet.
“Truth is not something that’s easily verifiable. It requires judgment, reflection, experience, and all of these intangibles that they are nowhere near modeling in these AI systems,” says Eric. However, the same problem doesn’t apply to music: “ We don’t play music on the basis of whether it’s true or not. [AI] works really well with music because there is no ‘true’ or ‘false’ valuation.”
Another reason why AI has advanced so rapidly in music is that since the introduction of the MP3, music has become a highly shareable medium. In his study, Eric discusses the existence of a musical creative commons, which is the result of the combined works of musicians from the past and present.
The musical public domain faces a significant vulnerability since it cannot be safeguarded by the current copyright system, which is mainly designed to protect the rights of individuals. This has created an opportunity for AI companies to exploit and utilize the knowledge from the public domain to develop their AI models.
Apart from the more evident creative uses of AI, it also holds substantial potential in trend forecasting, for example, identifying artists who are likely to achieve stardom — a process that has traditionally been quite imprecise in the music industry.
Now, with platforms like Musiio, which was recently purchased by SoundCloud, more accurate predictions can be made using their servers to analyze which music is most likely to become popular. Eric argues that non-hit songs are just as crucial in determining the success of Emerging artists like Billie Eilish, who initially gained popularity on SoundCloud: “[Billie’s] music only stands out as exceptional if you have this entire body of music as the norm against which it defines itself as an exception. Should those artists be penalized if their music is generating data? It’s actually going to end up marginalizing them, in a way.”
Other uses of AI include South Korean entertainment company HYBE employing AI technology known as Supertone to create a digital likeness of the late folk-rock singer Kim Kwang-seok, as well as the company’s announcement of their move to Weverse DM, a platform that enables artists to directly communicate with fans in 2023. It is plausible that these systems are all AI-operated or operated with a significant amount of hidden human involvement by impersonators.
However, the main concern is not the potential losses for big-name artists due to AI advancement. The most at-risk individuals are those working behind the scenes in production or in the “generic music” realm. While this may not be the most glamorous aspect of the industry, it represents a significant source of potential income for up-and-coming artists who can earn part-time revenue by producing backing tracks, loops, or beats.
Eric points out that the distinction between “generic” and “creative” music in this context is a perilous one, particularly concerning the music industry’s overall health.
“The argument I see some people make is that you don’t have to worry if you’re ‘truly creative.’ I think that kind of distinction is intensely problematic because [this is the area] where you develop your craft. So if we’re going to take that away from people [and their means of] earning money on the side, you’re eating your seed corn, so to speak.”
Simultaneously, the United States is witnessing an increasing number of legislative efforts aimed at protecting artists’ interests. Federal laws such as the NO FAKES Act, the No AI FRAUD Act, and the Music Modernization Act have sought to grant artists more control over the use of their voice and likeness, address AI use of artist likenesses, and establish mechanisms for artists to receive royalty payments, although with varying degrees of success. The most robust legislation has been largely enacted on a state-by-state basis, with Tennessee becoming the first state to safeguard artists from AI impersonation in March.
What legal considerations should artists bear in mind?
A prominent issue under US musical copyright law is that while there are protections for the actual content of an artist’s musical performances and compositions, their name, image, and likeness (or “NIL”) remain largely undefended. This presents a challenge for artists in terms of controlling potential revenue streams, their reputation, safeguarding intellectual property rights, and preventing privacy violations. followed, Eric suggests that artists should be “very, very cautious” with contractual language that transfers NIL rights.
One falter to the establishment of NIL laws at the federal level is that it introduces a concept of transferability similar to copyright, which could make it easier for exploitative record labels to incorporate this into their contracts. For instance, if an artist has passed away, labels could potentially use AI to legally produce new content from their catalog after their death, even if it goes against their wishes.
It’s also unclear legally how much power artists have to stop their music from being used as material for training artificial intelligence. This is partially due to the secretive nature of music AI. While some AI companies have used their in-house composers to create the foundation for their content, such as what was done in the past for the generative music app Endel, the extent to which AI companies are utilizing music from the public domain is mostly unreported, hinting that the numbers could be higher than what these companies admit.
Publicly, there is a growing number of collaborations between AI companies and major record labels, such as the partnership between Endel and Universal Warner. In 2023, they signed a deal to work together on 50 AI-generated wellness-themed albums. One outcome of this was a series of remixes of Roberta Flack’s GRAMMY Award-winning cover of “Killing Me Softly With His Song” for its 50th anniversary.
Just like the reworking of “Killing Me Softly,” repurposing old recordings for new monetization opportunities is likely to become more common.
While established artists like Roberta and Grimes have been supportive of AI partnerships, it’s the lesser-known artists entering into unfair contracts who are most at risk without legal safeguards. An artist with a large following might have some informal protection through negative publicity if they face contract issues, but smaller artists could encounter career-threatening problems or compromise their principles if they don’t scrutinize the details.
What’s the solution?
Despite the significant influence of AI in today’s world, one thing it can’t replicate is the bond between an artist and their fans.
“We listen to artists not only because we enjoy their music, but also because there’s a connection between the artists and the music,” explains Eric. “A Taylor Swift song performed by Taylor Swift carries a particular significance for her fanbase. So even if [AI] can generate something that’s musically just as good, it wouldn’t have that inherent human connection.”
Another positive aspect is that there is a legal precedent for supporting artists. In a 1942 case involving the American Federation of Musicians and major radio and record companies at the time, the AFM secured the right to a public trust that paid musicians for performing at free concerts across North America. Apart from offering paid work to artists, the ruling also directed value back into the public domain of music.
It’s time to reintroduce the kind of legal decisions from the 20th century that supported artists, asserts Eric. “This was a widespread practice in the past. I think we lost sight of that. Particularly in the US, there’s a notion that these entities are too large or beyond control.”
He proposes that governments begin imposing taxes on AI companies to restore the lost value to the public music domain and compensate for the harm they have caused to the economy and the environment. With these funds, similar to the 1942 case establishing the Music Performance Trust Fund (which still exists), artists could access benefits like healthcare, insurance, scholarships, and career resources.
While AI may have a significant impact on modern industry, there is still hope for the future of the music industry. As long as listeners are interested in creativity and supporting genuine artists, and artists are committed to creating music that pushes creative boundaries, there will be room for ongoing innovation in music.
The audio sector, covering aspects from music creation to voice technology, is undergoing a major transformation spurred by the swift progress in artificial intelligence (AI). AI is altering the ways we produce, modify, and engage with sound, introducing groundbreaking functionalities to industries including entertainment, customer service, gaming, health, and business, among others. This piece explores the present AI-empowered audio technologies and their influence across different fields.
The Emergence of AI in Audio: A Technological Advancement
The incorporation of AI into the audio sector is not merely an improvement of existing tools; it signifies a pivotal shift in how audio is created, edited, and experienced. Software driven by AI can now sift through large datasets, learn from them, and create or alter audio in methods that were previously reserved for human specialists. This has unlocked a realm of opportunities, making high-caliber audio production reachable for a wider audience and fostering new avenues of creative expression.
AI in Music Creation
One of the most thrilling uses of AI within the audio sector is seen in music production. AI algorithms are now capable of composing music, crafting beats, and even mastering tracks. This technology enables musicians and producers to try out fresh sounds and genres, often merging elements that would have been challenging to attain manually.
AI-based tools like AIVA (Artificial Intelligence Virtual Artist) can generate original music based on specific guidelines set by the user. These tools can create compositions across various styles, from classical to electronic, offering musicians either a starting point or a complete composition. Furthermore, AI-influenced mastering services, such as LANDR, provide automated track mastering, rendering professional-quality audio within reach for independent artists and producers.
For those eager to discover the newest AI solutions for sound generation and editing, platforms such as ToolPilot present an extensive range of innovative tools reshaping the music sector.
AI in Entertainment: Improving Audio Experiences
The entertainment sector has consistently led in embracing new technologies, and AI is no exception to this trend. AI-powered audio advancements are employed to enrich the auditory experience in film, television, and streaming services. From crafting immersive soundscapes to streamlining sound editing, AI is essential in heightening the quality of audio in entertainment.
In film and television production, AI assesses scripts and composes soundtracks that align with the mood and rhythm of a scene. This function not only saves time but also allows for more precise control over a scene’s emotional resonance. AI is also utilized in sound design, where it can produce authentic environmental sounds, Foley effects, and character voice modulation.
Moreover, AI is transforming how we access entertainment. Customized playlists and suggested content on platforms like Spotify and Netflix rely on AI algorithms that evaluate user preferences and listening behaviors. This boosts user engagement while introducing listeners to new musical and audio experiences they might not have encountered otherwise.
AI in Customer Support: The Growth of Voice Assistants
AI-driven voice assistants have become integral to customer service, changing the way businesses engage with clients. These voice assistants, backed by natural language processing (NLP) and machine learning, can comprehend and react to customer questions in real-time, ensuring a smooth and effective customer experience.
Voice assistants such as Amazon’s Alexa, Apple’s Siri, and Google’s Assistant are now built into various devices, from smartphones to smart speakers. They can execute tasks like responding to inquiries, creating reminders, and controlling smart home appliances. In customer support, AI-powered voice bots manage routine questions, allowing human agents to concentrate on more complex issues.
AI-driven voice technology is also being implemented in call centers to enhance efficiency and customer satisfaction. These systems can evaluate the tone and sentiment of a caller’s voice, enabling them to respond more empathetically and suitably to the circumstances. This level of personalization and responsiveness establishes a new benchmark for customer service across various sectors.
AI in Gaming: Crafting Immersive Audio Experiences
The gaming sector has long been a frontrunner in adopting new technologies, and AI fits right in. AI-powered audio is utilized to devise more immersive and interactive gaming experiences. From adaptive soundtracks that respond to gameplay activities to lifelike environmental sounds, AI is significantly improving the auditory experience in gaming.
One of the most important breakthroughs in AI-driven audio for gaming is the generation of procedural audio. This technology facilitates the on-the-fly creation of sound effects influenced by the player’s actions and the game environment. For instance, the sound of footsteps may vary based on the type of surface the player is traversing, or the intensity of a battle soundtrack can escalate as the player becomes engaged in combat.
Moreover, AI is being employed to enhance the realism and responsiveness of voice acting in video games. AI-powered voice synthesis can produce dialogue that responds to the player’s selections and actions, resulting in a more personalized and immersive gameplay experience. This technology also enables developers to craft a wider variety of complex characters, as AI can generate voices in different languages and accents.
The healthcare sector is another area reaping substantial benefits from AI-enhanced audio technologies. In the field of audiology, AI is utilized to create sophisticated hearing aids that can adjust to various sound environments in real-time. These devices apply machine learning algorithms to eliminate background noise, improve speech clarity, and even adapt to the user’s preferences over time.
Additionally, AI plays a vital role in voice therapy and rehabilitation. For those with speech difficulties, AI-driven software can offer immediate feedback on pronunciation and intonation, aiding them in enhancing their speech gradually. These tools are particularly advantageous for individuals recovering from strokes or surgeries, providing a tailored and accessible method of therapy.
In the wider healthcare domain, AI-powered voice analysis is being leveraged to diagnose and monitor numerous conditions. For instance, AI algorithms can examine voice recordings to identify early indicators of neurological disorders like Parkinson’s disease or Alzheimer’s. This non-invasive diagnostic approach presents a novel method to track patient health and recognize potential issues before they escalate.
AI is also making notable strides in the business realm, especially concerning meetings and communication. One of the most promising uses of AI in this arena is audio summarization. AI-driven meeting summarizers can autonomously create succinct summaries of meetings, highlighting crucial points, decisions, and action items.
These tools are particularly useful in remote work settings, where team meetings are frequently recorded and shared. AI summarizers help save time and ensure that important information is conveyed effectively and clearly. AI-powered meeting audio summarizers provide an innovative solution for businesses aiming to improve their meeting efficiency.
In addition to meeting summarization, AI is also being utilized to enhance transcription services. AI-driven transcription solutions can accurately translate spoken language into text, simplifying the process for businesses to document meetings, interviews, and other critical discussions. These tools are essential in industries like legal, media, and healthcare, where precise documentation is paramount.
The education sector also benefits from AI-enhanced audio technologies. AI is being tapped to develop personalized learning experiences through audio content, such as podcasts, audiobooks, and interactive voice-based educational tools. These resources can adjust to the learner’s pace and preferences, providing a more engaging and effective educational experience.
For instance, AI-based language learning applications can deliver real-time feedback on pronunciation and grammar, assisting learners in enhancing their language abilities more rapidly. Additionally, AI can formulate customized study plans based on a learner’s progress, ensuring they receive appropriate content at the optimal times.
Beyond personalized learning, AI-powered audio tools are also working to improve accessibility within education. For students with disabilities, AI-driven text-to-speech and speech-to-text technologies can make educational materials more available, enabling them to interact with content in ways tailored to their needs.
As AI continues to evolve, its influence on the audio industry is set to expand. We can look forward to further advancements in areas like voice synthesis, real-time audio processing, and individualized audio experiences. These innovations will not only enhance current applications but will also unlock new possibilities for how we produce and engage with sound.
A particularly thrilling possibility for the future is the emergence of AI-driven audio content creation tools that can collaborate with human creators. These tools could analyze a creator’s style and preferences, providing suggestions and generating content that complements their work. This collaborative approach could usher in entirely new genres of audio content that merge human creativity with the capabilities of AI.
One area that shows promise for growth is the fusion of AI with other emerging technologies, like virtual reality (VR) and augmented reality (AR). AI-enhanced audio could significantly contribute to the creation of immersive sound environments for VR and AR applications, improving the sense of immersion and authenticity for users.
As AI continues to evolve, we might witness the emergence of AI-based tools capable of understanding and producing music and audio that is indistinguishable from content created by humans. This could pave the way for a future where AI not only serves as a tool for audio creation but also actively engages in the creative process.
For a more comprehensive exploration of the ways AI is transforming the audio industry, the EE Times article offers valuable perspectives on the latest trends and innovations.
The Ethical Considerations and Challenges
While the progress in AI-based audio technologies is remarkable, it also raises various ethical issues and challenges that must be addressed. A major concern is the risk of misuse, particularly with the creation of deepfake audio. As AI becomes increasingly capable of replicating human voices, there is a heightened possibility that this technology could be exploited to generate fraudulent or misleading audio recordings.
This concern is especially pertinent in fields like politics, business, and journalism, where the credibility of audio content is crucial. To mitigate this risk, developers and researchers are working on solutions to detect and thwart the misuse of AI-generated audio. Nevertheless, as technology continues to develop, keeping ahead of those who might exploit it will be an ongoing challenge.
Another ethical issue is the effect of AI on job opportunities within the audio sector. As AI tools grow more proficient at performing tasks traditionally fulfilled by humans, there is a risk of job losses, especially in areas like sound editing, music composition, and voice acting. While AI has the potential to boost productivity and create new creative avenues, it’s vital to ensure that its integration is managed to support the workforce, providing opportunities for skill enhancement and collaboration rather than replacement.
Moreover, the growing dependence on AI in audio and voice technologies raises data privacy concerns. Many AI-driven tools require extensive access to data to function efficiently, including voice samples, listening preferences, and personal information. Ensuring that this data is managed in a secure and ethical manner is critical, especially as these technologies become increasingly intertwined with our daily routines.
The Role of Collaboration Between Humans and AI
In spite of these challenges, one of the most exciting possibilities of AI in the audio sector is the potential for collaboration between humans and AI. Rather than overshadowing human creativity, AI can act as a formidable tool that complements and enhances the creative process. This collaborative framework enables artists, producers, and professionals to push the limits of what is achievable, exploring new genres, sounds, and techniques that were previously out of reach.
For instance, in music production, AI can help generate fresh ideas, streamline repetitive tasks, and experiment with various styles and arrangements. This allows musicians to concentrate more on the creative parts of their work, viewing AI as a collaborator instead of a rival. Similarly, in voice acting, AI can create synthetic voices that enrich human performances, adding diversity and depth to the audio landscape.
In professional environments, AI-based tools like audio summarizers and transcription services can take care of the more routine aspects of communication, allowing professionals to dedicate their focus to strategic and creative endeavors. This collaborative dynamic not only enhances productivity but also encourages innovation, as humans and AI work in tandem to achieve results neither could reach alone.
Looking Ahead: The Future Soundscape
As we gaze into the future, the incorporation of AI into the audio industry is expected to accelerate, presenting both opportunities and challenges. The upcoming decade could witness the emergence of entirely AI-driven music labels, virtual bands made up solely of AI-generated voices and instruments, and tailored audio experiences that adjust in real-time according to the listener’s emotions, surroundings, and preferences.
In the area of voice technology, we may encounter AI voice assistants that are even more conversational and intuitive, able to engage in intricate dialogues that mirror human interaction. These advancements could revolutionize the ways we communicate with our devices and with one another, in both personal and professional settings.
The potential for AI in health-related audio technologies is also extensive. AI-based diagnostic tools may become commonplace in audiology, facilitating early detection and intervention for hearing-related concerns. In addition, AI-driven voice analysis could be utilized to monitor and evaluate a wide array of health conditions, offering a non-invasive, real-time method for assessment.
In fields like gaming, merging AI with audio could result in unmatched levels of immersion and interactivity. Soundtracks that adapt in real-time to player actions, environments that respond audibly to even the smallest interaction, and characters that modify their voice based on narrative decisions are just a few of the possibilities ahead.
In the realms of business and education, tools powered by AI will keep enhancing communication, making meetings more effective, improving remote learning experiences, and ensuring essential information is available to everyone, regardless of language or ability.
Conclusion: Welcoming the Sound of AI
The influence of AI on the audio, music, and voice sectors is significant and wide-ranging. From music creation to customer service, gaming, healthcare, business, and education, AI is changing the manner in which we produce, engage with, and experience sound. As AI technology progresses, we can anticipate even more innovative uses and opportunities in the future.
For anyone interested in understanding the current state of AI in audio, the HubSpot article provides an informative overview, while the EE Times offers a more detailed technical examination of the newest trends. Whether you work in the industry or are simply intrigued by the future of sound, these resources present valuable insights on how AI is reshaping the audio landscape.
The realm of music education is experiencing a revolutionary transformation due to the rise of Artificial Intelligence (AI). This technology is not merely a concept for the future; it is a present phenomenon that is influencing how we learn, instruct, and engage with music. In this blog post, we will delve into the many ways AI is changing music education to be more personalized, interactive, and available than ever before.
Tailored Learning Experiences: AI can evaluate a student’s playing style, strengths, and weaknesses to create customized lesson plans. This tailored method ensures that learners receive instruction that specifically pertains to their needs, making the learning process more effective and efficient.
Interactive Learning Tools: The era of one-dimensional music education is behind us. AI-enhanced applications and software provide interactive experiences, offering immediate feedback on various performance aspects such as pitch, rhythm, and technique. This is especially advantageous for beginners who are starting to grasp the complexities of musical performance.
Virtual Music Instructors: AI-driven virtual tutors are revolutionary, particularly for those lacking access to live teachers. These tutors can walk students through lessons, provide corrective feedback, and respond to questions, making music education more accessible to a broader audience.
Enhanced Music Creation: For aspiring composers, AI can suggest chord progressions, melodies, and harmonies. This serves as a useful tool for understanding music theory and the intricacies of composition.
Music Recognition and Analysis: By dissecting musical pieces, AI assists in recognizing patterns, styles, and structures. This not only supports learning but also fosters an appreciation for the complexity and beauty found in various musical forms.
Inclusive Music Creation: AI-powered tools have unlocked new opportunities for individuals with disabilities, allowing them to create and learn music in ways that were previously unachievable. Techniques such as motion tracking and eye tracking ensure that music creation is accessible to everyone.
Gamification of Education: Numerous AI-driven music learning platforms use gamification to make the process more enjoyable and engaging. This method is particularly effective in encouraging younger learners to practice consistently.
Insights for Educators Based on Data: AI provides important insights into a student’s progress, allowing educators to adapt their teaching methods to better suit their students’ needs.
Immersive AR and VR Learning Experiences: The application of augmented and virtual reality in music education creates engaging environments, transforming the learning experience into something more interactive and captivating.
Global Collaboration: AI promotes international collaboration, granting students access to a range of musical viewpoints and high-quality education regardless of their geographical location.
Conclusion
AI in music education is more than just a trend; it is a transformative catalyst. By providing personalized, efficient, and accessible learning options, AI enriches the music education journey. This is an exciting period for both music learners and educators as we explore the limitless possibilities that AI brings to the field of music.
