As tech companies begin to monetize generative AI, the creators on whose work it is trained are asking for their fair share. But so far no one can agree on whether or how much artists should be paid.<\/p>\n
A recent open letter from the Authors Guild signed by more than 8,500 writers, including Margaret Atwood, Dan Brown and Jodi Picoult, urges generative AI companies to cease using their works without proper authorization or compensation. Artists, meanwhile, have brought numerous lawsuits against generative AI vendors like Stability AI, MidJourney, and Microsoft regarding copyright and misuse.<\/p>\n
Some vendors have pledged to establish \u201ccreators\u2019 funds\u201d and other means to pay the artists, authors and musicians whose works they\u2019ve used to develop their generative AI models. Some have even taken the step of actually <\/em>launching<\/em> said funds, which they\u2019ve heralded as a move toward more equitable, sustainable generative AI business models.<\/p>\n So how much can creators realistically expect to make from these funds?<\/p>\n It seems like a simple question. But when you dig into the various compensation policies that have been proposed by generative AI vendors, it\u2019s one that proves exceptionally difficult to answer. Trust us \u2014 we tried. Repeatedly.<\/p>\n Generative AI models \u201clearn\u201d to create images, music, text and more by picking up on patterns in an enormous number of examples, usually sourced from the publicly accessible web. The examples \u2014 typically photos, artwork, audio and text \u2014 are often copyrighted or published under a usage license that vendors disregard, and creators are often not even informed that their works are being used in this way.<\/p>\n While some companies developing generative AI tools argue that they\u2019re justified in training on copyrighted works under the \u201cfair use\u201d doctrine, at least in the U.S, it\u2019s a matter that\u2019s unlikely<\/a> to be settled anytime soon. And legal questions aside, public opinion has largely rallied behind creators, most of whom make a pittance compared to the billions tech and AI companies are raking in.<\/p>\n So vendors including Adobe, Getty Images, Stability AI and YouTube have introduced \u2014 or promised to introduce \u2014 ways creators can share in their generative AI profits. The trouble is, the companies haven\u2019t been clear about how much, exactly, creators can expect to earn. And for creators considering allowing a vendor to train a model on their works, it doesn\u2019t make the decision easy.<\/p>\n Adobe, which trains its family of generative AI models, called Firefly<\/a>, on images from its stock asset library Adobe Stock, says that it\u2019ll pay out a once-a-year \u201cbonus\u201d that\u2019s \u201cdifferent for each contributor.\u201d The first was disbursed<\/a>\u00a0in early September.<\/p>\n Adobe\u2019s bonus is based primarily on the total number of approved images, vectors or illustrations submitted to Adobe Stock standard or premium that were used for Firefly training and the \u201cnumber of licenses\u201d their images generated during a year-long period, a spokesperson told me via email. Future bonuses are set to be calculated from new approved images and downloads, meaning that creators can\u2019t count on metrics in a previous bonus period to predict their next payout.<\/p>\n Image Credits:<\/strong> Adobe<\/p>\n<\/div>\n What\u2019s each individual approved image and license worth? Unclear. Adobe declined to tell us.<\/p>\n All we know for certain is, contributors have to reach a $25 minimum threshold before they can make a withdrawal (with the exception of contributors who received the first bonus payment, who can withdraw at $1 between September 13 and December 12). It can take 8 to 10 business days or more to complete a withdrawal, Adobe says. And, somewhat alarmingly for contributors, the company makes no guarantee that it\u2019ll pay bonuses in perpetuity.<\/p>\n But wait, it gets more complicated \u2014 and opaque.<\/p>\n The Firefly bonus is currently weighted toward the number of licenses issued for an image, the Adobe spokesperson said, which the company considers to be a proxy for the demand and \u201cusefulness\u201d of an image. But to what degree it\u2019s weighted and whether the weighting will change in the future, Adobe wouldn\u2019t say.<\/p>\n Getty Images also plans to pay contributors to its recently-announced<\/a> generative AI tool on an \u201cannual recurring basis,\u201d according to a spokesperson. Content creators will get a \u201cpro rata\u201d (i.e. proportional) share for each asset they\u2019ve contributed to the model training data set as well as a share based on \u201ctraditional licensing revenue.\u201d<\/p>\n We asked for clarification on the licensing bit \u2014 and for more information about the pro rata payments arrangement. Like Adobe, though, Getty Images wasn\u2019t forthcoming about the specifics.<\/p>\n \u201cThere will be a set formula based on a number of different factors, and accordingly each contributor will receive different payments in connection with the tool,\u201d the spokesperson said.<\/p>\n Image Credits:<\/strong> Getty Images<\/p>\n<\/div>\n Getty Images competitor Shutterstock, which also offers<\/a> a set of generative AI tools and sells its metadata and stock images to partners including OpenAI, distributes one-off payments via its Contributors Fund. The twice-a-year payouts are proportional to a creator\u2019s contributions to Shutterstock\u2019s content library, and creators receive additional compensation if new content produced by Shutterstock\u2019s AI generators includes their work.<\/p>\n \u201cContributors will receive a share of the entire contract value paid by customers licensing data sets,\u201d Shutterstock writes<\/a> on its website. \u201cContributors whose content was used to train [models] will be compensated for the role their IP played in the development of the original models, as well as through royalty payments tied to future generative licensing activity.\u201d<\/p>\n What\u2019s the exact proportion, though? And what might that \u201cadditional compensation\u201d look like? It\u2019s anyone\u2019s guess.<\/p>\n The best estimate we have is from stock photographer Robert Kneschke, who took it upon himself to survey<\/a> 58 other photographers how much they were paid from Shutterstock\u2019s Contributors Fund and factor in the size of their portfolio to calculate averages.<\/p>\n Kneschke\u2019s survey found that the average revenue from the Contributors Fund was $0.0078 per image while the median was $0.0069 per image. Assuming those numbers are accurate, a photographer with around 2,000 images would make roughly $15 \u2014 not exactly an earth-shatting amount.<\/p>\n Incredibly, those are the most concrete generative AI compensation schemes we were able to find. The others are more\u2026 theoretical.<\/p>\n When Stability AI announced Stable Audio<\/a>, a model that generates music and sound effects given a text description, the AI startup said that it would \u2014 through its partnership with stock audio library AudioSparx \u2014 let musicians share in the profits generated by Stable Audio. All they\u2019d have to do is join AudioSparx and opt to participate in the initial model training or decide to help train future versions of Stable Audio.<\/p>\n A few weeks later, the details of that revenue sharing scheme still being hashed out, according to AudioSparx EVP Lee Johnson.<\/p>\n \u201cWe haven\u2019t yet received any earnings report from Stability AI, and it\u2019s \u2018early days\u2019 still in terms of understanding the revenue that will be generated,\u201d Lee told TechCrunch. \u201cAs such, it remains to be seen what sort of earnings the average contributor can expect to earn.\u201d<\/p>\n Image Credits:<\/strong> Stability AI<\/p>\n<\/div>\n Lee went on to say that contributors can expect to receive a share of the earnings generated by Stable Audio on a \u201cresidual, recurring\u201d basis as long as they\u2019re opted-in to participate in model training.<\/p>\n \u201cOnce we receive the first earnings report from Stability AI and are able to fully understand the various metrics and details of the information they\u2019ll provide, we\u2019ll then have the necessary information in hand to fully determine how to allocate the earnings to each of the participating artists,\u201d Lee said. \u201cThere\u2019s ongoing discussion between AudioSparx and Stability AI about some of the issues related to the metrics and earnings reporting and so this is all still very much under development.\u201d<\/p>\n Elsewhere on the generative AI music front, YouTube, which in August unveiled<\/a> a generative AI partnership with Universal Music Group, said that it plans to develop a structure that ensures music rightsholders get paid for their training data contributions. But when contacted for content, YouTube said that it\u2019s in the \u201cvery early days\u201d of building monetization models that take generative AI into account.<\/p>\n \u201cA big part of that will be done by collaborating with our partners across the music business,\u201d a YouTube spokesperson said.<\/p>\n Tellingly, none of the generative AI vendors we spoke with would give a dollar amount the average creator can expect to see after forking over their creations for model training.<\/p>\n Some vendors blamed the absence of data on the newness of the tech and business model. Others said that the range would vary too widely to give a useful figure.<\/p>\n But for creators \u2014 particularly those dependent on contract income to make ends meet \u2014 those are arguments that are likely to ring hollow.<\/p>\n Some startups are attempting to be more transparent \u2014 and creator-focused \u2014 from the get-go. Braia<\/a>, which trains its art-generating AI strictly on licensed images, has a revenue sharing model that rewards data owners based on their contributions\u2019 impact, allowing artists to set prices on a per-AI-training-run basis.<\/p>\n So far as we can tell, though, as things stand now, few vendors are making an especially compelling case that it\u2019ll be worth artists\u2019 whiles if they opt in to generative AI model training. At best, they\u2019re offering hazy promises of future riches \u2014 and hazy promises don\u2019t pay the rent.<\/p>\n<\/p><\/div>\nVague terms<\/h2>\n
![\"Getty](\"https:\/\/techcrunch.com\/wp-content\/uploads\/2023\/09\/aibeta-uxmock-styledjpg.jpg\")
<\/p>\nNo dollar amount<\/h2>\n
![\"Stable](\"https:\/\/techcrunch.com\/wp-content\/uploads\/2023\/09\/00.png\")
<\/p>\nTough luck, creators<\/h2>\n