Emerging Business Models to Reward Artists and IP Owners in AI Training and Mimicry

The New Paradigm: Intellectual Property in the Age of AI

In a groundbreaking legal development, The New York Times has initiated a federal lawsuit against OpenAI and Microsoft, citing copyright infringement. The crux of the issue lies in the alleged use of “millions” of the newspaper’s articles to train chatbots like ChatGPT, developed by OpenAI​​​​. This lawsuit highlights the burgeoning conflict between traditional copyright laws and the innovative methodologies employed in AI development, particularly in the context of training machine learning models.

A Billion-Dollar Concern: The Scale of Copyright Infringement

The New York Times’ action underscores the immense value and potential financial implications of copyrighted content in the AI era. The newspaper contends that the infringements could amount to billions of dollars, reflecting the significant economic stakes involved in such practices​​. This scenario is not isolated to The New York Times; it is a harbinger of a broader trend where individual creators and large content publishers alike are grappling with the implications of their work being used to feed the voracious data appetites of AI models.

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The Ripple Effect: Broader Implications for the Industry

The lawsuit filed on December 27, 2023, aims to cease the practice of using published materials for training AI models. This legal move is not just about one company; it signals a pivotal moment for the tech industry at large, questioning the ethical and legal boundaries of utilizing existing creative works to build and enhance AI technologies​​.

The Intersection of AI and Intellectual Property: A New Frontier

The advent of AI in creative sectors, particularly with AI text-to-image generators like DALL-E 2, Stable Diffusion, and Midjourney, has ushered in a new era of debate and uncertainty for artists, designers, and illustrators​​. These AI tools, trained on massive datasets of text and images, have raised concerns about style appropriation and the potential redundancy of traditional artistic roles​​.

The Screen Actors Guild’s Stand for Performers’ Rights

In response to the rapid evolution of AI, SAG-AFTRA has taken significant steps to protect actors’ likenesses from exploitation​​. The guild’s negotiations with the AMPTP (Alliance of Motion Picture and Television Producers) have focused on ensuring fair compensation and consent for the use of actors’ images, particularly in the context of AI-generated content​​. This fight has been about ensuring that performers, from background actors to Oscar winners, have a say in how their likeness is used on screen and are not replaced by digital replicas just for cost-cutting purposes​​.

Compensating Visual Artists in the Age of AI

The use of artists’ works to train AI tools has led to proposals for new compensation models. Video collage artist Erik Winkowski emphasized the need for artists to either be compensated when their works are included in AI training datasets or have the option to opt-out entirely​​. This approach was echoed in the policy shift by DeviantArt, where artists now have to opt-in to allow their artwork to be used for AI training, responding to community backlash against automatic inclusion​​. Similarly, Shutterstock plans to integrate DALL-E’s text-to-image generator and compensate creators whose work was used in AI training​​.

https://www.euronews.com/next/2022/12/30/dalle-2-stable-diffusion-midjourney-how-do-ai-art-generators-work-and-should-artists-fear-

Comprehensive Business Models for Equitable Compensation

1. Revenue Sharing and Licensing
   
   • Getty Images and AI-generated Content: Getty Images exemplifies a revenue-sharing model where artists receive a percentage of profits from AI applications using their work.
   • Music Industry’s Licensing with Streaming Services: The music industry’s approach with platforms like Spotify, where royalties are paid based on usage, can be a model for compensating visual artists in AI applications.
     
2. Blockchain-Based IP Tracking
   
   • KodakOne’s Blockchain Platform: This platform uses blockchain to manage image rights, ensuring photographers are compensated for their work’s usage.
   • Ascribe for Digital Art: Ascribe allows digital artists to track ownership and usage rights, a model that could be adapted for AI training dataset contributions.
     
3. Creator-Centric Platforms
   • Patreon for AI Contributions: Adapting platforms like Patreon, artists could directly contribute to AI datasets and receive a share of generated revenues.
   • HitRecord’s Collaborative Model: This model, where artists share profits from collaborative projects, could be adapted for AI, with artists contributing to datasets and sharing in AI-generated content profits.
     
4. Consent and Compensation Provisions
   
   • SAG-AFTRA’s Actor Protections: SAG-AFTRA’s negotiations ensure actors’ consent and compensation for the use of their likenesses in AI applications.
   • Visual Artists’ Rights Act (VARA) in the U.S.: VARA provides artists with rights against work distortion. A similar principle could ensure artists’ control over their work’s use in AI, with fair compensation.
     
5. Usage-Based Royalty Systems
   
   • Micro-Royalty Systems: Implementing micro-royalty systems where creators are compensated each time their work is accessed or used by an AI, akin to pay-per-view models.
     
6. Artist Participation in AI Development
   
   • Artists as AI Co-Developers: Inviting artists to participate in the development process of AI tools, allowing them to influence how their work is used and ensuring a portion of AI-generated revenues.
     
7. Legal Reforms and Policy Initiatives
   
   • Policy Advocacy for Artists’ Rights: Advocacy for legal reforms to extend existing copyright laws to cover the use of works in AI training, ensuring artists’ rights are protected under the new technological conditions.
     
8. Educational and Community Outreach Programs
   
   • AI Literacy Programs for Artists: Developing programs to educate artists about their rights and the implications of AI on their work, fostering informed decision-making about participating in AI training datasets.
     

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Competing Opinions of Industry Experts

Concerns Over Copyright Infringement and Compensation

Collective Sentiment of Creative Professionals

• Perspective: Many authors, artists, and other creative professionals are concerned about AI’s impact on intellectual property. They believe AI technologies are negatively impacting their work, particularly when their creations are used without permission to train AI systems.
• Key Concerns: There is a call for clear regulation on AI’s use of copyrighted material, with many in the creative industry feeling that AI companies owe them compensation for using their work without permission.
• Representative Comments: Creative professionals have submitted comments to the Copyright Office expressing fears of AI being a “plagiarism machine” and potentially causing “irreparable damage” if not regulated properly.
• Source: Marks Gray, P.A.
  

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Hilary Hahn & Carol Reiley – DeepMusic.ai

• Hilary Hahn: Grammy-winning violin soloist.
• Carol Reiley: Tech entrepreneur and co-founder of DeepMusic.ai.
• Perspective: They view AI as a bridge between art and science, enhancing rather than replacing creativity. Their startup, DeepMusic.ai, focuses on linking artists with AI to create compositions beyond human capabilities.
• DeepMusic’s Vision: The startup aims to give artists a seat at the table in shaping new AI tools for musicians, working on shifting ideas around authorship, legal rights, intellectual ownership, and business models.
• Source: Stanford Institute for Human-Centered AI
  

Legal Challenges and Ownership Questions

Legal Perspective

• Perspective: The rise of AI-generated art raises various legal challenges regarding intellectual property, particularly in terms of copyright ownership in artistic creations such as drawings, paintings, and sculptures.
• Key Questions: When an AI algorithm creates artwork, it raises questions about who is the actual creator – the party that owns the AI algorithm or the one that rendered the final artwork.
• Source: The Recorder

These diverse opinions and perspectives highlight the ongoing debate and complexity surrounding AI’s integration into the creative world, especially concerning intellectual property rights and the balance between enhancing creativity and protecting artists’ livelihoods.

CDO TIMES Bottom Line: Navigating the AI-Creativity Conundrum

The intersection of AI and intellectual property rights presents a complex challenge requiring innovative solutions. The recent actions by The New York Times, SAG-AFTRA, and the artistic community reflect a growing awareness of the need to protect creators in the digital age.

The discourse surrounding AI’s impact on the creative industries and intellectual property rights is multifaceted and evolving. As we’ve seen from the varied expert opinions, this topic straddles a fine line between innovation and preservation, rights and opportunities, and fear and optimism.

1. Balancing Innovation with Protection: The key challenge lies in balancing the innovative potential of AI in enhancing creativity against the need to protect the traditional rights and livelihoods of artists. AI’s capacity to extend the boundaries of artistic expression is undeniable, yet this should not overshadow the necessity of safeguarding the intellectual property rights of creators whose works contribute to AI’s development.
2. Regulatory and Ethical Considerations: There is a pressing need for clear regulatory frameworks that define the extent and manner of AI’s interaction with copyrighted material. Ethical considerations must be at the forefront, ensuring that AI’s use of creative works respects the original creators’ rights and compensates them fairly.
3. Economic Implications for Artists: The economic implications for artists in an AI-dominant landscape are significant. The industry must develop models that not only recognize the contributions of artists but also ensure that they are not economically disadvantaged by the proliferation of AI-generated content.
4. Collaborative Futures: The future lies in fostering collaboration between AI technologists and artists. By giving artists a seat at the table in the development of AI tools, the industry can ensure that these technologies are shaped in ways that respect and enhance human creativity, rather than supplanting it.
5. Educational and Awareness Initiatives: Raising awareness and educating both creators and consumers about the implications of AI in the creative sector is crucial. Understanding the legal, ethical, and economic aspects of AI-generated content will empower creators to make informed decisions about their participation and rights.
6. Redefining Artistic Creation: As AI blurs the lines of authorship and creation, there’s an opportunity to redefine what it means to be a creator in the 21st century. This redefinition involves recognizing the collaborative nature of AI-generated works and reassessing how we view creativity and originality in the digital age.
7. Forward-Looking Policies: It is vital for policymakers, technologists, and creatives to work together in developing forward-looking policies that anticipate future technological advancements. These policies should aim to protect artists’ rights while also encouraging innovation and exploration in the arts through AI.

In our opinion, as AI continues to reshape the creative landscape, it’s essential that its development and application are guided by principles of fairness, respect, and collaboration, ensuring a future where technology and creativity coexist in harmony.

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