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AI's First Copyright: Behind the Breakthrough

The hidden battle for AI creativity rights begins by prompts. From rejected art to data wars, explore the race to define AI's role. The shocking twist? China leads the way, the West WAY behind. EP #55

The first AI copyright in the world goes to a Chinese AI artist, and nobody talks about it or likely even knows about it.

Recognizing the importance and direction of human beings with Generative AI seems evident to those who use it. Why do courts throughout the world reject copyrights for AI-generated art?

In this episode, we explore the complex world of AI-generated art, copyright issues, and the evolving role of human creativity in the age of artificial intelligence.

Our Guest: Debanghsa Sarkar -COO of EclimAI

“At EclimAI, we leverage computer vision and machine learning to build cutting-edge clean tech for smart building systems.

1. Product management: Leading a team of developers to build the most intelligent clean/tech for smart buildings.
2. Research: Working with leading computer vision researchers for incorporating state-of-the-art computer vision algorithms into our software.
3. Operations: Acting as the bridge between the stakeholders in the company, board members, design partners and developers to ensure a successful product launch.”

Prompt Engineer Simulation Discussion between a Data Scientist and a Creative Podcaster


Debangsha Sarkar, COO of EclimAI and a data scientist with a deep technical background, sat across from Declan, a creator of words and art, and the conversation drifts to AI-generated work.

"Imagine," Declan begins, "what if you could recreate the same image with just ten prompts?"

Debangsha chuckled. "As a programmer, I have this itch for perfection. You'll never be satisfied with ten prompts because they will always seem too easy. You'll think, 'What if I try the 11th one and make it a bit better?' Then you'll end up with 600 prompts regardless, in the pursuit of excellence."

Declan nods, understanding the relentless pursuit of perfection. "Even if I had the same image in mind, I could never recreate exactly what you came up with using Midjourney."

This iterative nature of creating with AI tools highlights the unique human touch involved in AI Art. It isn't just about the final product but the journey of creation and the specific choices made along the way.


The Emergence of Prompt Engineering as a Skill


The discussion shifts to the growing field of prompt engineering.

"Some people are good at prompt engineering," Debangsha noted, "and it’s a human skill. It’s learnable."

Declan leans in, intrigued. "So, you're saying that crafting effective prompts is becoming valuable?"

"Exactly," Debangsha replied. "The law should recognize that fact. There is a human skill involved, right?"

Jason Allen’s Théâtre D'opéra Spatial

Declan remembers an artist at a recent art festival in Colorado. "An artist there used 600 prompts to create AI-generated art, open about its AI origins.

The number of prompts signifies creativity and originality. But the legal system is still figuring out how to handle this."

"It's the same with that graphic novel, Zarya at Dawn. The text was copyrighted, but not the AI-created images. The US Office acknowledged the human effort in writing and assembling the book but not creating the images."


Copyright Challenges in the AI Era


Declan adds, "We should be able to detect the creative process in generative AIs. For example, we have semantic and language analyses that can help us understand the expertise in the prompts."

"Tracking the creative process behind AI-generated art could provide a basis for copyright claims," he mused.

Debangsha nods. "Even though AI stores and generates images from latent space, the legal argument is whether AI-generated images are truly original."


The Ethics of Data Scraping and AI Training


The conversation turns to the ethical implications of how AI models learn. "One of the systemic problems is the openness to AI," Declan notes. "Companies scrape data without permission. But how far do we go?"

He draws parallels to other controversial data collection practices, like those by facial recognition companies.

"Shouldn't I be able to learn from it? Couldn't I even pay a fee or be in an educational institution with access to this data instead of closed networks?"

Debangsha points out, "The quality of data used to train AI models is also questionable. Much comes from sources like Reddit, which may not always be reliable."

They agree that we need a more open-source approach that protects creators' rights without stifling creativity.


China's Pioneering Approach to AI-Generated Art Copyright


Their conversation lands on China’s pioneering approach to AI-generated art copyright. Declan shares, "China granted copyright protection to an AI-generated image. The artist used Stable Diffusion and created the artwork through a series of prompts."

Debangsha highlighted, "The court considers the choice of AI provider, detailed prompt engineering, iterative process, and technical adjustments. It recognizes the human creativity involved."

 "This case sets a precedent that acknowledges the expertise and decision-making in AI art creation."

Declan adds, "Unlike the West, where there's little to no protection, China’s model offers valuable insights on fostering a thriving AI art ecosystem while protecting creators' rights."

AI's First Copyright: Behind the Breakthrough

Summary and Key Issues for Freeing Artists to Work with AI as a Tool

Section 1: The Perfectionist's Dilemma in AI Art Creation

The conversation begins with an intriguing question: What if someone could recreate the same image with just ten prompts?

 Debangsha Sarkar, COO of EclimAI and a data scientist with a Master of Data Science and Master of Science - MS Computer Science from the University of British Columbia sees the value of prompt engineering as a learned skill, one that he is not that good at.

Drawing from his experience as a programmer, he knows the inherent drive for perfection that many creators feel:

"As a programmer, I have this itch for perfection. You will never be satisfied with ten prompts because it will always seem too easy to you.

And it will say, what if I try the 11th one and I can make it a little bit better, and you will either make it or break it and then you like, let's try the 12th one.

Maybe this will be a little bit better. Maybe the color doesn't look good here. So I think you are going to end up with 600 prompts anyway."

This insight underscores the iterative nature of creative work, even when using AI tools. Debangsha argues that refining and perfecting an AI-generated image is a skill in itself, one that requires human input and decision-making.

"Even if I had the same image in mind that this is the image I want to make with Midjourney, I can never recreate that image that Jason came up with."

This statement recognizes the unique human touch that goes into creating AI-generated art. It's not just about the final product but also about the creation journey and the specific choices made along the way.

Section 2: The Emergence of Prompt Engineering as a Skill

The discussion shifts to the growing field of prompt engineering, a new skill set that has emerged with the rise of AI art generation tools:

"Some people are good at prompt engineering, and it's a human skill. It's a learnable skill. It's not a skill people are born with. You have to learn it. And some people are good at it."

This highlights the human element in AI art creation. Developing effective prompts that yield desired results is becoming a valuable skill.

Human input should be recognized and valued in discussions about copyright and creativity:

"I think the law should accept that fact. Take at least take that into consideration that, hey, there is a human skill involved, right?"

  • Case Study: Colorado Festival:

    • An artist used 600 prompts to create AI-generated art.

    • "He was very open about stating that it came from AI"​​.

    • Discusses whether the number of prompts signifies creativity.

    • Questions about originality and human expression in AI art.

    • Legal precedents and the necessity of human input for copyright.

  • Other Legal Cases:

Human Skill in AI Art:

  • Prompt Engineering as a Skill:

    • It’s a learnable skill, not innate.

    • Some people excel in it, highlighting the need for legal recognition of the skill.

    • "Some people are really good at prompt engineering, and it's a human skill."​

Section 3: Copyright Challenges in the AI Era

There are complex copyright issues surrounding AI-generated art, including  two distinct but often confused copyright debates:

1. Can artists who use AI tools copyright their creations?

2. Are AI companies infringing on existing copyrights by using images to train their models?

While Jason Allen's work does not get a copyright by the US Copyright Office, the graphic novel Zarya at Dawn gets a copyright for the words and formatting of the book.

However, Midjourney's images were not copyrighted. The US Office recognized the human effort in writing and assembling a book but not the work required to create the images.

"The imagery was from AI, but she wrote it and formatted the book. So they let her copyright the book and the words human created.

But I could take her images. So the pictures in the book were not copyrighted."

This case highlights the nuanced approach that copyright law is taking toward AI-generated content. It recognizes human contributions while grappling with the status of AI-generated elements.

"We should be able to detect the process within these generative AIs. For example, we have semantic analysis. We have language analysis where you can understand the expertise in the question."

Tracking the creative process behind AI-generated art could provide a basis for copyright claims, allowing artists to demonstrate their expertise and creative input.

Technical Aspects of AI Art:

Section 4: The Ethics of Data Scraping and AI Training

The final part of the discussion focuses on the ethical implications of how AI models gather data. The acceptance of companies scraping data without permission to train their models is a barrier to copyright protection:

"One systemic problem was this openness to AI, which I like, but they just scraped without permission. But how far do we go?"

There are parallels to other controversial data collection practices, such as those employed by facial recognition companies like Clearview AI.

The conversation touches on the tension between the desire for open access to information and the need to protect intellectual property rights.

“Shouldn't I be able to learn from it? Shouldn't I be able to pull it in? Couldn't I even pay a fee or be in an education institution where those teachers could get it?"

This quote shows the dilemma faced by the AI industry and society: balancing the potential for learning and innovation with the need to respect copyright and compensate creators fairly.

The quality of data used to train AI models is also questionable since much of it comes from sources like Reddit, which may not always provide the most reliable or high-quality information:

"Especially most of the stuff that came from Reddit... You know, most of it is garbage. It's like people venting about stuff they don't know about. And all of that went inside ChatGPT."

So, what is the transformative impact of AI on creative industries and intellectual property rights? Hopefully, a more open-source approach that doesn't stifle creativity while also protecting the rights of creators:

"And that's my hope. Let's make it a little more open-source so we don't leave all that creativity behind. While Siloing information, information and IP copyright conflicts."

Numerous challenges arise as AI continues to reshape the landscape of creativity and copyright. Finding a balance between innovation, protection, and fair compensation will be crucial in harnessing AI's full potential.

China's Pioneering Approach to AI-Generated Art Copyright: What the West Can Learn

As legal battles rage and paywalls rise in the West, China has taken a groundbreaking step in recognizing copyright for AI-generated art.

This move raises the question: Can innovation survive in a world of fear and uncertainty, especially when some actors behave as if copyright rules don't apply to them?

Let's examine China's approach and potential implications for the global AI art landscape.

The First AI-Generated Image to Receive Copyright Protection

In a landmark case, China has granted copyright protection to an AI-generated image. Here are the critical details of this groundbreaking decision:

  1. The Creation Process:

    • The artist used Stable Diffusion, an AI image generation tool.

    • They created the artwork through a series of prompts.

    • The image goes on social media with a watermark claiming ownership.

  2. The Legal Dispute:

    • A defendant used the image on their website without attribution or credit.

    • The court ruled in favor of the plaintiff (the human creator), declaring them the rightful owner of the copyright.

  3. The Court's Reasoning: The court considered several factors in its decision:

 a) Choice of AI Provider: The selection of the AI service was deemed an artistic choice.

b) Detailed Prompt Engineering: The creator used approximately 30 prompts and over 120 negative prompts, demonstrating significant human input.

c) Iterative Process: The artist adjusted prompts based on outputs, showing an ongoing creative process.

d) Technical Adjustments: The creator sets and resets technical parameters to refine the image.

"Prompt engineering is a skill, an art, and a science. It does not just come out of an AI model."

This case sets a precedent for recognizing the human creativity involved in AI art creation, particularly prompt engineering.

This ruling offers valuable lessons for AI artists seeking copyright protection:

  1. Document Your Process: Keep records of your prompts and the iterative steps you take.

  2. Demonstrate Human Input: Show how your expertise and decision-making shaped the final product.

  3. Use Watermarks: Mark your work to establish ownership.

China's Stance on AI and Copyright

China's approach to AI-generated art copyright is nuanced:

  1. Human-Centric: Chinese courts do not recognize AI models as creators. They view AI as a tool, with human input being the source of creativity.

  2. Protection for Human Creators: The copyright is granted to the person who employs their skills in using the AI tool, not to the AI itself.

While China is pioneering in protecting AI-generated art, it's also mindful of existing copyrights. A recent case involving an AI-generated image of Ultraman, a Japanese superhero, demonstrates this balance:

This ruling clearly sends a message to AI companies about the importance of respecting existing copyrights even as they push the boundaries of innovation.

Contrast with Western Approaches

Note the stark contrast between China's approach and that of Western countries:

"If you create any AI image in the US right now in Europe, you have little to no protection. There is no copyright, so anyone can take it. And unlike in China, they can do what they want to do."

This lack of protection in the West raises concerns about the potential stifling of innovation and creativity in AI art.

What we can learn from China’s First AI Copyright

The  global AI community could benefit from following China's example:

  1. Recognize Human Skill: Acknowledge prompt engineering and AI art creation expertise.

  2. Case-by-Case Evaluation: Assess copyright claims based on the level of human input and creativity demonstrated.

  3. Protect Innovation: Offer copyright protection to encourage the development of AI art skills.

"My goal is let's follow China because what they said makes sense. They also said it didn't apply to anyone with an AI prompt. By each case, it will show prompt engineering follow-up of prompts that create something that takes the image."

China's approach to AI-generated art copyright offers a balanced perspective that recognizes human creativity while embracing tech innovation.

China's model provides valuable insights into how we might foster a thriving AI art ecosystem while protecting the rights of creators.

Other nations must now develop similarly nuanced approaches that encourage innovation while respecting intellectual property rights in this rapidly evolving field.

What We Both Learned on this Podcast

  1. Skill in Prompt Engineering:

    • Creating AI art requires extensive trial and error.

    • Recognition of prompt engineering as a skill is crucial.

  2. Legal Recognition and Copyright:

    • The legal system is slowly adapting to AI-generated content.

    • Human input is essential for copyright, but the definition of creativity remains debated.

  3. Ethical Data Use:

    • Scraping data for AI training raises significant ethical and legal questions.

    • The industry is grappling with balancing innovation and intellectual property rights.

  4. Open Source vs. Proprietary Systems:

    • The trend towards proprietary systems could stifle creativity.

    • Advocacy for more open-source practices to foster innovation.

Practical Applications for AI-Generated Art Creators:

  1. Enhance Your Prompt Engineering Skills:

    • Practice and refine prompt techniques to improve AI art outputs.

    • Learn from experts and invest time understanding how different prompts affect the results.

  2. Stay Informed About Legal Issues:

    • Keep up with the latest legal precedents regarding AI-generated content.

    • Be transparent about using AI in your creations to avoid legal issues.

  3. Ethical Considerations:

    • Be mindful of the sources of your data and ensure ethical use.

    • Engage in discussions and advocate for fair use practices.

  4. Embrace Open Source:

    • Contribute to and use open-source platforms to foster a collaborative and innovative community.

    • Share your techniques and learn from others to push the boundaries of AI art.