Featured Post from Emory University, Goizueta Business School

AI Art: What Should Fair Compensation Look Like?

Jun 28, 2024

5 min

David Schweidel



New research from Goizueta’s David Schweidel looks at questions of compensation to human artists when images based on their work are generated via artificial intelligence.


Artificial intelligence is making art. That is to say, compelling artistic creations based on thousands of years of art production may now be just a few text prompts away. And it’s all thanks to generative AI trained on internet images. You don’t need Picasso’s skillset to create something in his style. You just need an AI-powered image generator like DALL-E 3 (created by OpenAI), Midjourney, or Stable Diffusion.


If you haven’t tried one of these programs yet, you really should (free or beta versions make this a low-risk proposal). For example, you might use your phone to snap a photo of your child’s latest masterpiece from school. Then, you might ask DALL-E to render it in the swirling style of Vincent Van Gogh. A color printout of that might jazz up your refrigerator door for the better.


Intellectual Property in the Age of AI


Now, what if you wanted to sell your AI-generated art on a t-shirt or poster? Or what if you wanted to create a surefire logo for your business? What are the intellectual property (IP) implications at work?


Take the case of a 35-year-old Polish artist named Greg Rutkowski. Rutkowski has reportedly been included in more AI-image prompts than Pablo Picasso, Leonardo da Vinci, or Van Gogh. As a professional digital artist, Rutkowski makes his living creating striking images of dragons and battles in his signature fantasy style. That is, unless they are generated by AI, in which case he doesn’t.


“They say imitation is the sincerest form of flattery. But what about the case of a working artist? What if someone is potentially not receiving payment because people can easily copy his style with generative AI?” That’s the question David Schweidel, Rebecca Cheney McGreevy Endowed Chair and professor of marketing at Goizueta Business School is asking. Flattery won’t pay the bills. “We realized early on that IP is a huge issue when it comes to all forms of generative AI,” Schweidel says. “We have to resolve such issues to unlock AI’s potential.”


Schweidel’s latest working paper is titled “Generative AI and Artists: Consumer Preferences for Style and Fair Compensation.” It is coauthored with professors Jason Bell, Jeff Dotson, and Wen Wang (of University of Oxford, Brigham Young University, and University of Maryland, respectively). In this paper, the four researchers analyze a series of experiments with consumers’ prompts and preferences using Midjourney and Stable Diffusion. The results lead to some practical advice and insights that could benefit artists and AI’s business users alike.


Real Compensation for AI Work?


In their research, to see if compensating artists for AI creations was a viable option, the coauthors wanted to see if three basic conditions were met:


– Are artists’ names frequently used in generative AI prompts?

– Do consumers prefer the results of prompts that cite artists’ names?

– Are consumers willing to pay more for an AI-generated product that was created citing some artists’ names?


Crunching the data, they found the same answer to all three questions: yes.


More specifically, the coauthors turned to a dataset that contains millions of “text-to-image” prompts from Stable Diffusion. In this large dataset, the researchers found that living and deceased artists were frequently mentioned by name. (For the curious, the top three mentioned in this database were: Rutkowski, artgerm [another contemporary artist, born in Hong Kong, residing in Singapore] and Alphonse Mucha [a popular Czech Art Nouveau artist who died in 1939].)


Given that AI users are likely to use artists’ names in their text prompts, the team also conducted experiments to gauge how the results were perceived. Using deep learning models, they found that including an artist’s name in a prompt systematically improves the output’s aesthetic quality and likeability.


The Impact of Artist Compensation on Perceived Worth


Next, the researchers studied consumers’ willingness to pay in various circumstances. The researchers used Midjourney with the following dynamic prompt:


“Create a picture of ⟨subject⟩ in the style of ⟨artist⟩”.


The subjects chosen were the advertising creation known as the Most Interesting Man in the World, the fictional candy tycoon Willy Wonka, and the deceased TV painting instructor Bob Ross (Why not?). The artists cited were Ansel Adams, Frida Kahlo, Alphonse Mucha and Sinichiro Wantabe. The team repeated the experiment with and without artists in various configurations of subjects and styles to find statistically significant patterns. In some, consumers were asked to consider buying t-shirts or wall art. In short, the series of experiments revealed that consumers saw more value in an image when they understood that the artist associated with it would be compensated.



Here’s a sample of imagery AI generated using three subjects names “in the style of Alphonse Mucha.”
Source: Midjourney cited in http://dx.doi.org/10.2139/ssrn.4428509


“I was honestly a bit surprised that people were willing to pay more for a product if they knew the artist would get compensated,” Schweidel explains. “In short, the pay-per-use model really resonates with consumers.” In fact, consumers preferred pay-per-use over a model in which artists received a flat fee in return for being included in AI training data. That is to say, royalties seem like a fairer way to reward the most popular artists in AI. Of course, there’s still much more work to be done to figure out the right amount to pay in each possible case.


What Can We Draw From This?

We’re still in the early days of generative AI, and IP issues abound. Notably, the New York Times announced in December that it is suing OpenAI (the creator of ChatGPT) and Microsoft for copyright infringement. Millions of New York Times articles have been used to train generative AI to inform and improve it.


“The lawsuit by the New York Times could feasibly result in a ruling that these models were built on tainted data. Where would that leave us?” asks Schweidel.


"One thing is clear: we must work to resolve compensation and IP issues. Our research shows that consumers respond positively to fair compensation models. That’s a path for companies to legally leverage these technologies while benefiting creators."


David Schweidel


To adopt generative AI responsibly in the future, businesses should consider three things. First, they should communicate to consumers when artists’ styles are used. Second, they should compensate contributing artists. And third, they should convey these practices to consumers. “And our research indicates that consumers will feel better about that: it’s ethical.”



AI is quickly becoming a topic of regulators, lawmakers and journalists and if you're looking to know more - let us help.


David A. Schweidel, Professor of Marketing, Goizueta Business School at Emory University


To connect with David to arrange an interview - simply click his icon now.

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David Schweidel

David Schweidel

Professor of Marketing & Goizueta Chair in Business Technology

Marketing analytics expert focused on the opportunities at the intersection of marketing and technology

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Using a novel machine learning technique developed at Goizueta by Lee, they were able to identify the effect of increasing or reducing the workforce. The contrast between physicians and nursing staff is stark, says Tushe. “When you have fewer nurses on duty, capacity and patient throughput drops by an order of magnitude—far, far more than when reducing the number of doctors. Our results show that for every additional patient the nurse is responsible for, service speed falls by 17%. That compares to just 1.4% if you add one patient to the workload of an attending physician. In other words, nurses’ impact on productivity in the emergency department is more than eight times greater.” Boosting Revenue Through Reduced Wait Times Adding an additional nurse to the workforce, on the other hand, increases capacity appreciably. And as more patients are treated faster, hospitals can expect a concomitant uptick in revenue, says KC. “It’s well documented that cutting down wait time equates to more patients treated and more income. Previous research shows that reducing service time by 15 minutes per 30,000 patient visits translates to $1.4 million in extra revenue for a hospital.” In our study, we calculate that staffing one additional nurse in the 7am to 7pm emergency department shift reduces wait time by 23 minutes, so hospitals could be looking at an increase of $2.33 million per year. Diwas KC This far eclipses the costs associated with hiring one additional nurse, says Lee. “According to 2022 U.S. Bureau of Labor Statistics, the average nursing salary in the U.S. is $83,000. Fringe benefits account for an additional 50% of the base salary. The total cost of adding one nurse during the 7am to 7pm shift is $310,000 (for 2.5 full-time employees). When you do the math, it is clear. The net hospital gain is $2 million for the hospital in our study. Or $470,000 per 10,000 patient visits.” Incontrovertible Benefits to Hiring More Nurses These findings should provide compelling food for thought both to healthcare administrators and U.S. policymakers. For too long, the latter have fixated on the upstream costs, without exploring the downstream benefits of nursing services, say the researchers. Their study, the first to quantify the economic value of nurses in the U.S., asks “better questions,” argues Tushe; exploiting newly available data and analytics to reveal incontrovertible financial benefits that attach to hiring—and compensating—more nurses in American hospitals. We know that a lot of nurses are leaving the profession not just because of cuts and burnout, but also because of lower pay. We would say to administrators struggling to hire talented nurses to review current wage offers, because our analysis suggests that the economic surplus from hiring more nurses could be readily applied to retention pay rises also. Sokol Tushe 23PhD, Muma College of Business The Case for Mandated Ratios For state-level decision makers, Lee has additional words of advice. “In 2004, California mandated minimum nurse-to-patient ratios in hospitals. Since then, six more states have added some form of minimum ratio requirement. The evidence is that this has been beneficial to patient outcomes and nurse job satisfaction. Our research now adds an economic dimension to the list of benefits as well. Ipso facto, policymakers ought to consider wider adoption of minimum nurse-to-patient ratios.” However, decision makers go about tackling the shortage of nurses in the U.S., they should go about it fast and soon, says KC. “This is a healthcare crisis that is only set to become more acute in the near future. As our demographics shift and our population starts again out, demand for quality will increase. So too must the supply of care capacity. But what we are seeing is the nursing staffing situation in the U.S. moving in the opposite direction. All of this is manifesting in the emergency department. That’s where wait times are getting longer, mistakes are being made, and overworked nurses are quitting. It is creating a vicious cycle that needs to be broken.” Diwas Diwas KC is a professor of information systems & operations management and Donald Lee is an associate professor of information systems & operations management. Both experts are available to speak about this important topic - simply click on either icon now to arrange an interview today.

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