Fairly Trained - Beatoven.ai [PART 3] Ethics of genAI for music
Looking for an ethical tool that uses generative AI for creating music? Check out this profile of Beatoven.ai, a genAI music company that's certified as Fairly Trained.
This article provides a deep dive on Beatoven.ai, one of the companies working on generative AI for music who have been certified as Fairly Trained. It supports the upcoming PART 3 in our 8-part series “Unfair Use? Ethics of generative AI for music”, announced in this INTRODUCTION post on .
This article series is not a substitute for legal advice and is meant for general information only.
Acronyms
DAW - digital audio workstation
TTA - text to audio (more general than music; can include spoken vocals as well as sung vocals & instruments)
Business and feature information is summarized from the company’s websites; LinkedIn; Crunchbase; PitchBook, where available; and publicly available reviews of one or more of these tools. Links are in the References section.
Beatoven.ai
Descriptions:
Fairly Trained: “AI powered royalty free music for content creators”
LinkedIn: “Beatoven AI, a simplified music creator tool that helps you create music for your videos and podcasts.”
beatoven.ai website: “Create unique royalty-free music that elevates your story. Beatoven.ai uses advanced AI music generation techniques to compose unique mood-based music to suit every part of your video or podcast.”
PitchBook: “Developer of a music creator tool designed to offer royalty-free music to the creators. The company's platform uses artificial intelligence to take away the heavy lifting of advanced music theory which helps the creators to compose music, enabling creators to create their royalty-free music with less effort.”
History & Partnerships
Startup Beatoven.ai was launched in 2021, headquartered in Bengaluru.1 They are privately held (early stage VC) with 7 investors, including “Google for Startups”; last financing round was $1.33m in March 2024. They currently have ~22 employees. 2 (Based on their website About page, the entire organization is male-presenting.3)
In 2022 they had 200 active users, 80% in India; as of April 2024, they have 600,000 users worldwide.4 They are mentioned in many online lists of music generators, e.g. 5
Key Features
Their stated goal is to help “YouTubers, advertising agencies and wedding film production houses” create original soundtracks and avoid music acquisition and licensing issues. Their target users include agency/production houses, YouTube creators, podcast creators, indie game developers, audio books, and web3 & metaverse companies who need instrumental background music. Beatoven gives customers “access to royalty-free, affordable, mood-based, premium quality music composed by AI solutions developed by the company”.
As of 2024-05-21, there is no support for adding lyrics to a Beatoven-created song.
Their initial focus was regional (Indian) music. However, the tool supports multiple genres including rock, electronic, and indie. Songs can be created in two ways:
Text-to-music: “Type and describe the background music you need for your audio-video content and our AI technology will do its magic.”
Genre/Emotion: “Choose a genre, emotion and tempo and let our AI technology generate background music for your content.”
Training Data & Technology
Their technology is a combination of music theory and AI (but apparently rule-based, not generative). To create a song, initially a user selected a new project and preferences for genre and mood6. They have since added TTA (text-to-audio) support to allow users to describe the kind of music they want, or they can directly specify genre, emotion, and tempo.
Their website indicates that they ensure that musicians “receive equitable compensation when they contribute their music to Beatoven.ai”.
All of this is consistent with their Fairly Trained certification.
Ownership, Usage Rights, & Pricing
Like many other genAI music tool providers, they retain copyright to all songs created with Beatoven, and allow users to use the songs. “The users will be granted a perpetual license for usage of the soundtracks on their choice of use case. All copyrights for the musical works created on Beatoven belong to the company.”
Use on YouTube is ok, but reselling is not allowed - tracks cannot be registered with a content ID, and they do not permit uploading to a streaming music service such as Spotify, Soundcloud, or Apple Music. From the site: “You can use the music created on beatoven.ai for any of your Video content (youtube); Podcasts; Games; Short films/Trailers; Social media; AI art; Advertisements; Livestreams”.
Beatoven offers 3 plans:7
“Free Trial” - $0/month - No downloads. Create unlimited tracks with full access to instrument selections, volume dynamics, tempos, genres, and emotions.
“Subscription” - monthly cost varies based on number of minutes of downloads (15 min for $6, 30 min for $10, 60 min for $20). Users get all Free features plus license for downloaded music and access to stem downloads. Unused minutes expire and do not carry over to future months.
“Buy Minutes” - $3 per minute, starting at 1 minute. Minutes do not expire. Otherwise, benefits are the same as Subscription.
❓If you’re curious about the ethical posture of the big, well-known firms or smaller players who are not yet certified as Fairly Trained, subscribe (for FREE) to be notified of our upcoming posts (the parent PART 3 article, a post on major un-certified companies, a post on other un-certified companies) and the remainder of the series:
REFERENCES and ENDNOTES
Links to upcoming articles
(coming soon)
Analysis page on 9 genAI music companies who are already certified as Fairly Trained (including this one)
PART 3 - top-level article on Who, What, & When in ethics of genAI for music
Previously-published articles in our 2024 series on ethics of generative AI for music
![[PART 2] Unfair use? GenAI music ETHICAL RISKS & CHALLENGES](https://substackcdn.com/image/fetch/w_140,h_140,c_fill,f_webp,q_auto:good,fl_progressive:steep,g_auto/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Ff43d4635-1899-4964-b093-ced7dda4c29e_1600x1066.jpeg)
![[PART 1] Unfair use? Ethics of generative AI for music - WHY & FOR WHOM](https://substackcdn.com/image/fetch/w_140,h_140,c_fill,f_webp,q_auto:good,fl_progressive:steep,g_auto/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fc06537a2-b301-4907-8b78-0aefdbdf57cf_1001x902.png)
![[INTRO] Unfair use? The ethics of generative AI for music](https://substackcdn.com/image/fetch/w_140,h_140,c_fill,f_webp,q_auto:good,fl_progressive:steep,g_auto/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F163f723a-f4fc-4701-84a8-3a81cad85775_4896x3264.jpeg)
End Notes
“These 5 Indian AI Companies Are Making Sam Altman Eat His Words”, by Rahul Bansal, 2024-04-11
“This music-tech startup uses AI to create original soundtracks, solve music acquisition problems”, by Minakshi Sangwan, 2022-03-23
 | A guest post by
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Hi Karen, I read the first two parts of your Ethics in Generative AI for Music with great interest. Although I've been writing about developments in GenAI for a while, my focus was not on Ethics. I'm also an avid listener and music enthusiast, so this topic has a specific appeal for me. I have a few points to ponder after I read your first "deep-dive" article on beatoven.ai:
1) If a tool did not use Deep-Learning and neural-net-based technology but used a "symbolic" formulation (doubtful if this is possible since Symbolic AI was more or less abandoned after the early failures in the 70s to contrast the very optimistic view on AI in the 60s), would we still have ethical concerns? To put it more clearly, if it did not use any music to train it but relied on "algorithms" a human has formulated in order to produce "passable" music, how would the ethical concerns look like?
2) I believe a global agreement on properly marking AI-generated material is one of the building blocks of ethical generation. I am not sure if there is any work on standardising the label format etc.
3) Let us assume for a moment that the global AI companies agreed to properly compensate all of their source creators, including any work created through their models, would we still have an ethical problem? Let me use an analogy: If an LLM is trained with non-copyrighted material (e.g. anything 75+ years old according to U.S. law) would there be any ethical issues?
I'm not offering any solutions or reaching any verdict, but just trying to enlarge the scope of the ethics argument to move away from White=Ethically sourced and Black=Unethically sourced.
Please continue the very useful deep-dives you've been performing on these tools, for people who may not have time or opportunity to try out all these tools (and more being introduced every day).