Redefining Content Moderation in the Era of Synthetic Content

By 2026, up to 90% of online content may be synthetically generated. At the same time, governments worldwide are introducing stringent new online safety regulations that all online platforms will have to follow. 

For Trust and Safety teams and platform executives grappling with these challenges, this isn't just an abstract problem—it's an imminent crisis.

Content moderation is at a crossroads, and many are already buckling under the weight of their current moderation loads. With the incoming avalanche of synthetic content, AI seems like the obvious solution. But will it be the silver bullet we're all hoping for?

If you’re someone who’s worked in tech, especially in online safety teams, for the past few years, you know this: There are no silver bullets.

We believe that the future of content moderation lies not in AI alone, but in a symbiotic relationship between human expertise and AI capabilities. And this isn't just an incremental improvement - it's a fundamental reimagining of how we approach online safety.

In this article, we'll explore the challenges facing content moderation and present a vision for human-AI collaboration. We'll examine how this approach can improve accuracy, protect moderator well-being, and increase efficiency. 

The Moderation Tightrope: Balancing AI & Human Solutions

Trust & Safety teams are grappling with a perfect storm of challenges. They're struggling to secure adequate budgets, racing to stay ahead of emerging risks, and constantly seeking improved content moderation strategies. Many think the choice is simple: either invest in a team of human moderators or rely on automated tools.

However, the challenge for T&S teams isn't choosing between human moderation and AI - it's finding the right balance between the two.

Human moderation is costly, inflexible, and complex. 

As platforms scale, so do the costs associated with human moderation. Many choose to offshore this work, but managing remote teams and ensuring a full contextual understanding of policies introduces its own set of challenges.

In the early days of social media and online marketplaces, content moderation was primarily a human endeavor and almost exclusively reactive. Large teams of moderators manually compared written policies with user-generated content to identify and remove potentially harmful material.

Believe it or not, this is still the paradigm many T&S organizations rely on today. Especially for smaller and newer platforms. 

But relying solely on human moderation is no longer feasible, and not just for reasons of cost and scale, and complexity. 

Human moderation introduces biases, suffers from language coverage complexities, and often lacks cultural and demographic context. Much of this is due to insufficient training and/or budgets to counter the high turnover in such roles  Moreover, constant exposure to potentially harmful content takes a severe toll on moderators' mental health and wellbeing.

Current AI solutions often fall short of their promise. 

Many teams lack the technical resources and expertise to effectively implement and integrate AI or automation systems. Even when successfully deployed, these systems often generate large numbers of false positives and negatives, ironically increasing the human workload they were meant to reduce.

The largest platforms have managed to automate significant portions of their moderation processes out of sheer necessity. In theory, these automated systems can handle the bulk of content moderation, with humans stepping in to manage edge cases and perform quality control.

However, most platforms aren't operating at this scale. They're left struggling with off-the-shelf AI solutions that are difficult to integrate, lack contextual understanding, and fail to align with platform-specific policies, thereby requiring teams to change the way they want to moderate their platform. Developing in-house AI solutions is only feasible for the tech giants and the most technologically advanced up-and-comers, leaving smaller platforms in a difficult position.

Co-Pilot Moderation: Maximizing Human Potential with AI

The good news? AI classifiers are improving rapidly. We're starting to see advanced systems that can enforce unique content moderation policies from the outset, reducing false positives and negatives, and requiring less fine-tuning.

But this doesn't mean content moderation will soon be an entirely automated process. The inherent complexity and numerous gray areas in content moderation will always require some amount of human judgment. To tackle the emerging user safety threats posed by AI, platforms must adopt a truly hybrid approach.

Reimagining the Role of AI in Content Moderation

Instead of viewing AI as a replacement for human moderators, we need to start thinking of it as a co-pilot. Here's how this hybrid human-AI content moderation process could work:

1. AI-Powered Initial Screening: AI technology rapidly scans vast amounts of content, flagging potential issues based on predefined criteria.

2. Human/AI Review of Flagged Content: AI and Human reviewers have different strengths. In most cases AI will be able to make a review decision on par (or with even higher accuracy) than a human, and at the same time much cheaper and faster. But this is not achievable for every single review. If this occurs, humans will step in and do a better job. This combination of the two approaches, and knowing which reviewer needs to step in and when, leads to better outcomes.

3. Continuous Feedback Loop: Human reviewers refine and improve AI models as training data input over time, while AI provides detailed analytics and insights into content trends and moderation performance.

How Co-Pilot Moderation Transforms Content Safety

This symbiotic relationship between humans and AI in content moderation offers numerous advantages:

✔️ Improved Accuracy: Accuracy improves because humans and classifiers split the task of reviewing, depending on which system leads to better results.

✔️ Enhanced Moderator Wellness: By automatically handling much of the most egregious

 content before it reaches human moderators, AI can help protect their mental health and reduce burnout.

✔️ Increased Efficiency: The combined approach reduces overall costs by reducing the number of people needed and the time it takes to review content while allowing moderators to focus on decisions that truly require human judgment.

✔️ Scalability and Adaptability: Co-pilot moderation allows platforms to handle rapidly increasing content volumes and adapt quickly to changes in volume and type of content. AI can process massive amounts of data, while humans can quickly identify and respond to emerging trends or novel forms of abuse.

✔️Continuous Improvement: The feedback loop between human moderators and AI systems leads to ongoing refinement of moderation algorithms. As humans provide input on AI decisions, the system becomes more accurate over time, creating a constantly evolving and improving moderation ecosystem.

The Road Ahead for Online Safety

Many worry about AI taking jobs away from humans, but in Online Safety, it's not about replacement, it’s about collaboration and enhancement.  As many of the emerging threats can be created with AI (i.e. synthetic content, deepfakes, misinformation) it’s important that we also use this technology to understand and fight these trends. 

Too many companies have yet to fully embrace the potential of AI in content moderation, either due to implementation challenges or a lack of trust in the technology. And even those who have adopted AI often find current tools and available algorithms lacking.

But the reality is: the technology is here, and Trust & Safety teams can redirect their efforts currently spent on overwhelming, demoralizing, and harmful content moderation tasks to more worthwhile, human-centric efforts.

We've explored the challenges of content moderation and envisioned a future where human expertise and AI capabilities work in harmony. But how do we turn this vision into reality?

Enter ModerateAI. 

ModerateAI embodies the co-pilot approach, empowering online platforms to create safer spaces, protect user wellbeing, and scale effortlessly—all while preserving the nuanced understanding that only humans can provide.

The future of content moderation isn't about choosing between humans and AI - it's about creating a powerful partnership between the two. By embracing this new paradigm, we can create safer online spaces, protect the well-being of our moderation teams, and stay ahead of the ever-evolving challenges of the digital world.

The content moderation revolution is here. The question is: are you ready to join it?