AI generates content, summarizes articles, recommends videos, and filters inappropriate material. News outlets use AI to produce drafts or summaries quickly, while social media platforms rely on recommendation algorithms to keep users engaged. AI also creates realistic synthetic media, including images, video, and audio.
Why: To process large volumes of content, personalize user experience, and increase engagement.
Ethical considerations: AI-generated misinformation can spread rapidly, deepfakes can manipulate public perception, and recommendation systems may amplify bias or echo chambers. Transparency and accountability are crucial.
AI-Driven Deepfake Content & Abuse
When anyone can fake reality, trust becomes the first casualty.
In 2026, the European Union opened a formal investigation into Elon Musk’s social platform X over its AI chatbot Grok, after it generated and disseminated sexualised deepfake images, including content involving minors, which regulators say may violate protections under the EU’s Digital Services Act. This probe reflects growing concerns that mainstream AI tools can be misused for non-consensual, harmful media, eroding safety on major platforms and prompting legal scrutiny.
These deepfakes not only harm individuals’ privacy and dignity, they also highlight how AI systems with weak guardrails can enable exploitation and illegal content at scale, especially when platforms lack robust moderation and accountability.
Non-Consensual Deepfake Distribution Online
Millions of synthetic abuses and barely a handle on them.
Investigations have uncovered massive volumes of AI-generated explicit content being shared on messaging platforms like Telegram. Tens of thousands of channels have hosted non-consensual deepfake images targeting individuals globally, driven by easy-to-use AI tools.
The scale and ease of generating abusive content reveal the dark side of democratised AI content creation. Without strong platform safeguards or legal penalties, victims may suffer damage to reputation, mental health, and personal relationships, all before content is taken down or traced.
AI Saturation in Video Platforms
AI slop: cheap content churned out faster than truth checks can catch it
A study found that over 20% of videos shown to new YouTube users in late 2025 were low-quality, AI-generated contents, sometimes called “AI slop.” These videos often prioritize engagement and ad revenue over accuracy or value, highlighting how generative tools flood platforms with shallow or misleading media.
Saturation of AI-generated content can drown out credible creators, spread misinformation, and dilute viewer trust. It also rewards quantity over quality, which can distort what audiences perceive as important or true.
AI Tools in Journalism Workflows
AI speeds headlines today, but may rewrite standards tomorrow.
Media production increasingly uses AI for drafting, summarising, and editing content, from automated highlights in sports reporting to production workflows that generate visuals or cut footage. These tools promise efficiency, but experts caution they can also introduce errors or bias if oversight is weak.
While AI boosts productivity, it can inadvertently embed bias or fabricate details. Without human judgment and fact-checking, automated content may mislead or spread inaccuracies, undermining the very credibility journalists seek to uphold.
AI’s Role in Misinformation Spread
Algorithms that amplify clicks can also amplify lies.
AI-powered recommendation systems and content amplification algorithms play a significant role in how users encounter news and viral media. These systems tend to favour engagement and sensational content, increasing the visibility of misinformation spikes. Studies and research highlight how AI distribution plays into the speed and reach of fake news.
Even when AI models are not malicious, social platforms’ business incentives can prioritise sensationalism over accuracy, leading to echo chambers and reinforcing biases, making it harder for audiences to discern truth.