Over the past decade, platforms like Facebook, Snapchat, and Twitter have become early adopters of integrating AI to enhance user experience and engagement. These advancements have provided marketers with valuable insights and trends to better connect brands with their audiences in more meaningful ways. Although AI-powered social media enhancements are not a new concept, the rise of generative AI has increased concerns regarding the ability to create AI-altered content that can be harmful or deceptive to the public.
This issue becomes even more critical during election years, where willfully misleading content generated by AI can have significant consequences. In response to the growing concerns over AI-altered content, social media platforms have introduced their versions of AI labels. These labels help users identify content created or modified by AI. Meta’s “AI Info” and LinkedIn’s “Content Credentials” are examples of these initiatives, aiming to inform and protect users.
The issue with labeling AI is that users can’t tell what was created entirely with AI tools versus minor fixes to improve a photo. For marketers and brands, these labels are a mixed bag of potential benefits and pesky pain points. While these labels are meant to help users understand whether or not the content they’re seeing is AI-enhanced, distinguishing between AI-generated content and minor AI-enhanced edits remains difficult. Brands that have incorporated AI into their social media strategies need to comprehend these labels to navigate the benefits as well as stay vigilant about potential ethical challenges.
Understanding AI Content Labels
To understand how these labels are being implemented across social media, we first need to understand who is responsible for how these labels are used and when to use them. Enter The Coalition for Content Provenance and Authenticity (C2PA). The C2PA is an alliance of industry leaders, including Adobe, BBC, Intel, Microsoft, Google, OpenAI, Publicis Groupe, Sony, and Truepic. This coalition, a Joint Development Foundation project, aims to combat misleading information online by establishing technical standards to certify the history and source of media content. Policymakers, industry leaders, and academic experts within the C2PA have developed standards that enable the tracking of the origin and history of content shared on social media, while upholding the rights of freedom of speech granted by the First Amendment. Here are a few examples of how these new standards are manifesting on different social media platforms.
Meta: Previously and contentiously labeled “Made with AI”, this label would appear if any AI tools were used in the work’s creation. Some backlash from users who simply used filters on their photos and received a label, caused Meta to pivot their label from “Made with AI” to “AI Info”, a more accurate representation that the content may be simply modified, as opposed to the entirety of the content being AI-generated. Although Meta is not a part of the C2PA coalition, their new approach follows C2PA specifications that other companies in the C2PA coalition are compelled to follow in labeling content, their new approach aligns with C2PA specifications, which helps Meta’s team determine whether something is wholly created using AI or merely edited with an AI tool.
LinkedIn: LinkedIn’s “Content Credentials” label identifies AI-generated posts, helping professionals discern authentic content from AI-driven contributions. AI-generated images posted on LinkedIn will now include a small C2PA tag in the top right of the in-stream visual. Tapping and expanding the icon will allow users to see more info about the image. These tags will be automatically added, based on the code data embedded into the image, as identified by the C2PA process.
TikTok: TikTok is flagging and automatically watermarking AI-generated content, even if created with a third party. TikTok’s rules already require creators to disclose “realistic” AI-generated content. Content credentials attach “tamper-evident metadata” that can trace the origins of an image and AI tools that were used to edit it along the way. That history can then be viewed by users if they come across a piece of AI-made content on a platform that supports the technology.
YouTube: YouTube is labeling AI-generated videos to ensure viewers are aware of content origins and maintain platform integrity. For most videos, this transparency will appear in the expanded description. However, for sensitive topics like health, news, elections, or finance, a more prominent label will be displayed on the video. Labels may also be applied to videos where creators haven’t disclosed AI usage, particularly for the sensitive subjects listed above. Initially, these labels will appear on mobile, with expansion to desktop and TV in the coming weeks. For creators, the upload flow addition will start on desktop and gradually roll out to mobile.
Trust through Transparency
Building trust is a cornerstone of successful brand-consumer relationships. Consumers today are more informed and discerning, expecting honesty and openness from the brands they engage with. Being transparent about the use of AI in content creation can significantly enhance a brand’s credibility. By clearly marking AI-generated or AI-enhanced content, these labels aim to maintain user trust and ensure that audiences are fully aware of the origins of the content they consume.
For marketers, understanding these labels is essential. It not only helps in maintaining ethical standards but also in fostering a transparent relationship with the audience. As AI technology continues to advance, staying informed about these labels and their implementation across different platforms will be vital for marketers looking to leverage AI’s potential more responsibly.
Key Takeaways for Brands:
These regulations are still fairly new and brands utilizing AI-generated content should actively monitor their content and be prepared to dispute any that are inaccurately applied. Additionally, brands might benefit from having pre-drafted responses ready to address any questions about their use of AI. These responses should clearly explain the brand’s AI creative practices, as well as being prepared to answer questions regarding how your organization is using AI in non-creative places like data and beyond. Here are a few other considerations for marketers and their brands to keep in mind regarding AI-labeled content.
• Stay Informed About AI Labels: As AI technology evolves, so do the standards and practices around AI labeling. Marketers need to stay up to date with these changes to ensure they are using AI ethically and transparently.
• Draft A Plan: Develop a plan to monitor AI-labeled content, including protocols for disputing inaccuracies and pre-drafted responses for any inquiries. Utilize the guidelines and standards set by coalitions like the C2PA to ensure your AI strategies are aligned with industry best practices.
• Embrace Transparency: Use AI labels to your advantage by being open about how and when you use AI in your content. This transparency can help build trust with your audience and differentiate your brand in a crowded market.
• Monitor Platform-Specific Implementations: Different platforms have different approaches to AI labeling. Stay informed about how each platform you use handles AI content to ensure compliance and optimize your strategies.
By staying informed about AI labels, embracing transparency, understanding the nuances and being prepared to respond to queries, brands can successfully manage their AI-driven content and maintain trust with their audience. Ready to craft a social media strategy that leverages the benefits of AI? Hiebing can help. Email Nate Tredinnick at ntredinnick@hiebing.com to set up a call.