Will generative AI challenge authenticity in social media?
Generative AI tools are moving into social media platforms, enabling greater productivity and creativity while blurring the lines between authentic and synthetic. Younger generations are likely poised to drive its adoption—and disruption.
Many people follow online content creators, and some may aspire to join them. Social platforms are now trying to make it easier for more people to realize such aspirations by integrating generative AI content creation tools into their services. This could empower more creators and drive a new boom in user-generated content, while also challenging the authenticity and “humanness” of social media.
In the United States, Generation Z and millennials are already using generative AI more than older generations. Deloitte’s 2023 Connected consumer survey found that younger generations are experimenting with generative AI tools much more than their older counterparts: 31% of American Gen Z and 20% of millennials report having used or experimented with generative AI, versus only 9% of older generations.1
Younger generations also engage with social media more frequently2 and, as they enter the labor force, more are leaning into the creator economy. In the United States, ,millennials aged 31 to 40 are the largest group of content creators (full-time, part-time, and hobbyist).3 Just behind them, a quarter of US Gen Zs have said they plan to become social media influencers: professional, full-time content creators.4
Social platforms are now integrating generative AI tools, looking to make it easier for professional and aspirational content creators to realize their ideas.5 These tools aim to support greater creativity, productivity, and engagement for creators and advertisers. But they could also enable a glut of cheap, derivative content while challenging human-to-human authenticity.
Amplifying creativity and content creation
Content creation tools are one of the largest use cases for consumer generative AI, behind companions and general assistants.6 Some third-party providers have been offering generative AI content creation tools that support creators.7 Now, more social platforms are launching their own offerings, enabling content creators to use natural language text prompts to generate photorealistic images or apply visual styles to an existing image8, add background images and videos, or change backgrounds and scene elements in an image.9 With these capabilities, visual media is becoming more fluid and customizable, and producing it is becoming easier.
By enabling rapid development of content, generative AI can help creators work through ideas more quickly, and potentially make it easier for less-capable creators to generate higher-quality content. It could also enable top creators to become much larger, leveraging tools like generative AI dubbing and analytics to reach more global audiences.10
There still seems to be a “secret sauce” to human creativity, but generative AI is probing its depths. How models are implemented can determine how creative–or derivate–their outputs are. If generative AI models are designed with a lower creative “temperature,” the degree of randomness allowed in responses,11 or if they overly select for creative styles that are known to boost engagement metrics on the platform, they could narrow content diversity. Still, generative models seem to be revealing the dials of creativity.
By making it easier to create higher-quality content, these tools could lead to much greater competition among creators, opportunities for brands and advertisers, and moderation overhead for platforms. Social content could become even more of a commodity—cheaper to produce but harder to differentiate. This could put more pressure on creators to stand out and show their authenticity. Or it could directly challenge the value of authenticity on social media, causing platforms to shift their content strategies.
Will synthetic personalities challenge authenticity?
For creators and brands, authenticity has been a valuable currency in social media.12 However, some forms of synthetic media could challenge this authenticity, and perhaps disrupt the currency itself.
Generative AI can be used to create convincing virtual replicas of people, their voices, and mannerisms.13 One popular streamer made an AI clone of herself and then charged a fee for users to interact with it (fans could pay more to talk to the real person).14 Chinese e-commerce services have been using synthetic influencers to continuously livestream product reviews.15 Some providers are building synthetic versions of famous celebrities and deploying them into social platforms where users can interact with them as if they were real.16 Some are unlicensed fakes.17 Despite the science fiction nature, it doesn’t take much to wed a language learning model to a 3D model and build a synthetic personality.18
Social media will likely enter a rich period of experimentation and innovation with generative media and synthetic personalities.
There are already companies enabling digital twins and synthetic personalities and developing ways to secure rights for such digital likenesses.19 As these tools advance, they may soon become indistinguishable from their “real” counterparts. Could there be an uncanny valley in between–a period when synthetic media is just real enough to be creepy? Anecdotally, there is some resistance to synthetic personalities on social media in that they lack authenticity and human relatability. But recall that chatbots and companions are already the most popular consumer applications of generative AI.20 And younger generations are also equally engaged with video games, which have been populated by synthetic nonhuman players for decades.
As generative AI outputs become more refined, the authenticity and “humanness” that has defined much of social media could come under pressure. Some providers are introducing tools for creators and advertisers to watermark generative content, and for services to reveal any generative fingerprints.21 Ultimately, the evolving tastes of audiences will likely determine the acceptance of synthetic media. This could follow the same generational lines that have driven so much change in media and entertainment. Will younger generations, experimenting with generative AI and used to cavorting with game nonhuman players, be more open to a new kind of authenticity that includes synthetic personalities? How will Alphas, the kids of millennials, navigate and adopt generative content? Right now, creativity and authenticity–and even socialization–seem to be expanding to include more than humans.
Some considerations
Who holds the rights—and liability—of generative content?
Generative AI in content creation could make it more challenging for creators to attest and defend ownership of their content. If a generative copilot owned by the platform is used to produce successful content, who owns the rights to that content? Who is liable for it?
How should creators use generative AI tools?
Generative AI can help bring ideas to life quickly while enabling rapid iteration on concepts. However, relying on them completely is unlikely to lead to differentiation, and could undermine authenticity. To move from commodity content to premium, creators may find the best path is to collaborate with models early in their workflows, refine the results with their own expertise, then leverage generative AI audience analytics and targeting capabilities.
What is the right balance of natural content with generative AI and synthetic media?
Social user-generated content platforms are dependent upon creators but have been challenged to unlock economics that work for all parties. Generative AI could reduce the cost of content creation while raising the cost of moderating it all. Providers may feel drawn to bring more of their own generative content and synthetic influencers into their products, but this can risk alienating human users and turning away advertisers. This is an emerging area of experimentation that can take the pulse on authenticity and reveal the lines between real and synthetic.