Editorial
Amid the tumult of the pandemic, a quiet breakthrough was taking place in the home of a young New York City-based artist: the first AI-assisted graphic novel.
Last year, Kris Kashtanova’s "Zarya of the Dawn" became the first work of its kind to receive a U.S. copyright, sparking significant debate in creative communities concerning artist recognition, compensation and ownership. And while the U.S. Copyright Office (USCO) later reversed its decision, the implications of this milestone unearthed an ethical quagmire for visual artists, photographers and the platforms they host images on.
These types of developments posed a real challenge to Shutterstock, an image-based platform with over 2.2 million contributors and one of world’s largest stock photography databases. After all, AI-generated images, like those used in Kashtanova’s book, could cut deeply into its market share — especially if the average person could generate original artwork on their own or with the help of a disruptive startup.
The company was at a fork in the road: it could either stick to its business model or embrace disruption. It was already sitting on a treasure trove of data well-suited to feed and improve generative AI systems. So, unlike its competitor, Getty Images, Shutterstock chose the latter, launching its own AI image generation platform this January.
In the next decade, many other organizations will find themselves in a similar position. And as counterintuitive as Shutterstock’s embrace of an emerging technology that will disrupt its business may seem, I think it’s actually what being digital is all about.
Why Shutterstock Isn’t Waiting to Break Into the AI Game
You may have already heard about them: DALL-E 2, Stable Diffusion, Midjourney and others. At their core, these technologies are complex image generation tools that have been trained on large visual data sets from photography to paintings to digital artwork. An overly simplistic description is that it can create — with some imaginative prompting — new images that are a synthesis of everything in their training data.
Up until recently, these tools had limited adoption. They posed a steep barrier to entry for people who weren’t tech-savvy. They also sourced from large public domain archives and data sets scrapped from the internet at large, which introduced a level of inherent bias and variability that could sometimes produce unrealistic, and even offensive, results.
There has also been justifiable fear around the impact this technology could have on creators. Naturally, contributors are concerned about how they might get paid if their images are being used (in aggregate) to generate this kind of imagery. Not to mention the legal landmines that lie ahead as this technology continues to outpace legislation. Capitol Hill hearings, lawsuits and press statements from industry moguls are likely to heat up over the coming years.
Which bring us back to Shutterstock. Despite all of these obstacles, the platform has undertaken great pains to address each one. It has promised creators a pathway toward monetization through a “Contributor Fund,” which will directly compensate Shutterstock contributors if their work was used in the development of generative AI models. Leveraging its partnership with research organization Open AI, Shutterstock has delivered an accessible version of Open AI’s wildly popular DALL-E 2 AI system. Shutterstock’s stockpile of curated content will also go a long way toward ensuring users are able to generate imagery relevant to their search queries.
From a long-term perspective, the fact that it is calling attention to the need for an ethical approach to monetization will enable it to curry favor with its users, shape public discourse, and steer the industry through the troubled waters of copyright litigation to come.
Related Article: Generative AI Results Should Come With a Warning Label
Key Takeaways From Shutterstock’s Embrace of Emerging Tech
The stock imagery industry is at a crossroads. But rather than standing still, Shutterstock made the leap into the future, demonstrating its commitment to exploration and evolution in the process.
Other digital organizations can do the same by integrating the following strategies into their own playbooks:
1. Adopt a test-and-learn methodology
Shutterstock is on the leading edge of emerging technology because it is actively choosing to craft hypotheses, test them and evaluate the results. This iterative process is a crucial capability for organizations that want to be truly digital and differentiated, both when it comes to effective management of its existing products and the cultivation of innovative thinking. It allows companies to consider how, or if, those products and experiences deliver strong value to their users in today’s rapidly changing digital landscape.
2. Engage with empathy
Shutterstock isn’t just cutting ties with the longstanding relationships it's built with the over 80,000 artists in its creator community. It is asking, “How might we compensate the people whose work goes into the creation of digitally generated artwork in a fair way?” That’s how you build trust and a strong community of users. Acknowledge the change in the world, the challenges that come with it, choose a direction, learn and pivot as needed. Be transparent and human-centered along the way.
3. Avoid knee-jerk reactions
Shutterstock isn’t reacting to the world of AI-generated artwork with hostility or dismissal. That’s not always typical. Remember the Recording Industry Association of America’s (RIAA) war against P2P file sharing of digital music? Anyone with a Spotify account knows how that one turned out. Instead, Shutterstock is actively embracing a technology that could bankrupt its business with an attitude of curiosity and learning.
Related Article: What Agile Leadership Means in a Digital World
Digital Companies Need to Be the Future They Want to See
A company that waits around to see what happens won’t be the one that leads the industry.
Take Blockbuster, for example. The rental giant is often characterized as being slow to the punch on business models that could replace its own, like mail-in and streaming services. In fact, Blockbuster had an opportunity to acquire its disruptor Netflix early on — but instead, it laughed Netflix out of the room. When the company finally began to lose ground, its board members opposed efforts to flesh out Blockbuster’s digital business. It’s this kind of mindset that has the potential to capsize an $8.4 billion-dollar company at its peak.
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The truth is: Once-in-a-lifetime innovations like generative AI for images have just as much power to help your company as they do to disrupt it. Part of being a digital company is acknowledging that fact and welcoming change — not digging in your heels.
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