Artificial Intelligence: Image Authenticity and New Challenges
THE'artificial intelligence It's radically changing the way we perceive images online. Artificial intelligence is making it increasingly difficult to determine whether a photo is real or generated by an algorithm, creating a new landscape of digital uncertainty.
Until a few years ago, we trusted photos almost automatically. Today, however, we've reached the point where we no longer believe that visual content is real until we have good reason to believe so. The implicit question is always the same: does whoever published this image have a reason to lie?
In this context, the proposal to introduce cryptographic signatures into cameras seems like a possible technical solution to a now global problem. But is it really enough to restore our trust in an ecosystem where the production of AI content is encouraged by the very platforms that are now trying to contain its effects?
Artificial Intelligence and the Crisis of Trust in Images
The crisis of confidence arises from the fact that the’artificial intelligence Generative photography has led to the production of images virtually indistinguishable from reality. Tools like text-to-image models allow you to create perfect, hyper-realistic photos in seconds, completely unrelated to any real event.
This scenario overturns an ancient psychological mechanism: we are genetically predisposed to believe our eyes. As Adam Mosseri observed, it's as if this predisposition has become a flaw that needs to be corrected as we adapt to the new world of generative AI.
The paradox is that the same companies that are warning of the risk today have in recent years pushed hard for the diffusion of security tools artificial intelligence. Meta, for example, has invested heavily in AI systems for content creation and manipulation, contributing to the saturation of artificially perfect images in social feeds.
According to Mosseri, there's a lot of AI-generated content out there that's "fantastic." However, no concrete examples are provided, nor is there any exploration of how this content relates to social media platforms' engagement and retention strategies.
Cryptographic signatures and artificial intelligence: a technical solution?
One of the most discussed proposals is that of the cryptographic signatures applied to real images. The idea is that cameras, at the moment of taking the shot, apply a digital signature that certifies that the photo was actually captured in the physical world and not generated by a scanning algorithm. artificial intelligence.
In theory, this signature could become a sort of certificate of authenticity, verifiable by platforms, browsers, or the users themselves. But several critical questions immediately emerge:
- Who controls the cryptographic keys used to sign images?
- How do you prevent these keys from being hacked, copied, or forged?
- What happens if a photo is even slightly modified (cropped, adjusted for brightness, filters)? Does the signature remain valid or is it invalidated?
- Who decides which camera manufacturers are allowed to generate trusted signatures?
These issues are not only technical, but also political and governance-related. As highlighted by initiatives such as the project C2PA for content provenance, defining global standards requires agreement between companies, institutions and technical communities.
Mosseri also recognizes that simply labeling content generated by artificial intelligence It won't be enough. It will be necessary to provide much more context about the accounts sharing content, including their history, behavior over time, and their relationship with other sources.
Authenticity, imperfection, and the role of artificial intelligence
In a world where the’artificial intelligence It generates perfect images, and the professional look becomes paradoxically suspect. Raw, blurry, unprocessed photos become a sign of authenticity. Imperfection becomes proof, if not absolute, then at least probabilistic, of reality.
Today, sharing occurs primarily through direct messages, with blurry photos and shaky videos of everyday life. The famous "ugly but true" lunch photo is more credible than the perfectly lit photo, because the latter could have been generated in three seconds by an AI model like Midjourney.
But this is not a real victory for authenticity: it is rather a strategic retreat towards the one territory that AI has not yet fully conquered: random human imperfections. When the’artificial intelligence will learn to convincingly simulate even motion blur, noise, and spontaneous errors, this signal will lose further informative value.
At that point, other tools will be needed: robust cryptographic signatures, independent verification protocols, but also a new visual literacy. As many digital media scholars point out, including research cited by Nature, the ability to evaluate the credibility of content cannot be delegated to technology alone.
At the same time, trust is shifting from traditional institutions to so-called "creators." Mosseri observes that we trust creators we admire more than traditional media or institutions. However, these creators operate on platforms governed by proprietary algorithms, which decide what to show, to whom, and when, according to often opaque logic.
In practice, it is the algorithm – also powered by artificial intelligence – to define content visibility, based on constantly changing parameters that no one outside the company really knows.
Artificial Intelligence: Impact on Marketing and Business
THE'artificial intelligence It not only impacts the perception of images, but also redefines marketing, branding, and communication strategies. For companies, this scenario represents a reputational risk, but also a great opportunity to differentiate themselves by focusing on transparency and verifiable authenticity.
From a digital marketing perspective, the overabundance of content generated with artificial intelligence It makes it harder to stand out with truly distinctive messages. Campaigns that are "too perfect" can be perceived as cold or artificial, especially by users who are increasingly aware of the role of AI in content creation.
Companies can therefore rethink their strategies by focusing on:
- Authentic storytelling: show real processes, teams, backstage, imperfect but verifiable content.
- Transparency on the use of AI: declare when the’artificial intelligence It is used to generate or optimize content.
- Verification and reputation: integrate source verification and content certification systems, especially in sensitive sectors (finance, healthcare, public administration).
In terms of customer experience, direct channels—such as WhatsApp, chat, and virtual assistants—are becoming essential. In these spaces, users expect personalized and reliable communication, supported by AI but traceable and consistent with the brand.
The union between artificial intelligence Automation, for example, allows you to better segment your audience, send targeted content, and respond to customers in real time. But it makes it even more crucial to demonstrate that there's a real company behind the channel, with clear processes and defined responsibilities.
For businesses using messaging platforms like WhatsApp Business, this means designing communication flows that combine intelligent automation and human intervention. The goal is to offer a fast and efficient experience without sacrificing trust.
How SendApp Can Help with Artificial Intelligence and Authenticity
In this complex scenario, solutions like SendApp help companies to use the’artificial intelligence strategically and responsibly within WhatsApp Business. The focus is not just on automation, but on building credible and verifiable digital relationships with customers and communities.
With SendApp Official (official WhatsApp API), companies can integrate WhatsApp Business with their CRM systems, marketing automation, and analytics tools. This allows them to orchestrate advanced conversational flows, maintaining control of their data and ensuring an official and recognized communication channel.
SendApp Agent allows you to manage conversations and teams in a structured way, combining bots based on artificial intelligence with human operators. In practice, AI handles frequent responses and initial qualification, while agents intervene in the most sensitive cases, where the authenticity of the relationship is crucial.
With SendApp Cloud, it is possible to activate advanced automation flows: transactional notifications, nurture via WhatsApp, segmented campaigns, reminders and much more.’artificial intelligence It can support message personalization, while the channel remains official, tracked, and consistent with WhatsApp policies.
Thanks to this combination of tools, companies can:
- Integrate AI and automation without sacrificing transparency.
- Building conversational paths that strengthen brand trust.
- Maintain consistency between visual content, messaging, and corporate identity.
For those who want to prepare for a future where the distinction between real and generated content is artificial intelligence It will become increasingly subtle, and the choice of channels and platforms is strategic. Relying on professional solutions like SendApp allows you to build a solid, scalable, and trust-based WhatsApp Business presence.
If you'd like to learn how to integrate AI, automation, and authenticity into your digital conversations, request a dedicated WhatsApp Business consultation and discover how SendApp can support your project, from pilot to international scale.
