The increasing population of online users resulted in a surge of user-generated content (UGC) online. The demand for effective content moderation services increases as the volume of UGC continues to skyrocket. This necessity gave way to the latest integration of artificial intelligence (AI) and machine learning (ML) into content moderation systems.
According to a report by the International Telecommunication Union, around 5.4 billion people, or 67% of the global population, are online users in 2023. This growth represents a 4.7% increase since 2022.
Gaps in Traditional Content Moderation
Imagine the sheer volume of UGC produced when billions of people engage in online communities and join digital discussions. The World Economic Forum estimated that 463 exabytes of data will be created each day by 2025.
Manually checking online content can be taxing even for a seasoned content moderation company. The chances of making a mistake increase as the workload of human moderators amasses. The constant flood of UGC may also lead to delayed responses and inconsistent moderation.
Furthermore, constant exposure to distressing content can hurt a person’s health. A study by the U.S. Marshals Service shows that a quarter of investigators under the Justice Department’s Internet Crimes Against Children suffered from symptoms of secondary traumatic stress disorder due to exposure to content showing child exploitation and violence.
Another gap in manual moderation lies in human subjective judgment. It may be difficult for humans to perfectly interpret the context, intent, and cultural nuances behind every content. Even a skilled moderator may miss subtle forms of hate speech or misinterpret the context of a meme.
Filling the Gaps with Artificial Intelligence
Integrating artificial intelligence into content moderation can optimize the process. It can fill the gaps in manual moderation, increasing efficiency and effectiveness. Here are a few ways how AI can help improve content moderation.
Enhanced Accuracy through Context Understanding
AI can recognize keywords and understand the context behind their usage, enhancing the accuracy of content curation. Discerning the subtleties behind the language, tone, and intent behind UGC makes moderation more effective and contextually aware.
Continuous Learning and Adaptation
Content moderation AI learns from the vast amount of UGC it processes and analyzes, making it progressively smarter. This adaptivity powered by ML allows the AI to cope with the ever-changing trends and patterns behind UGC.
Multimodal Content Analysis
AI content moderation grew beyond simple text analysis with the help of ML. Modern AI can moderate other forms of UGC, including images, videos, and audio. This multimodal approach ensures that content moderation covers diverse forms of content, enhancing the overall safety of online spaces.
Automation and Content Filtering
AI-based content moderation increases the efficiency of the process by integrating automation and content filtering. The AI moderator automatically analyzes UGC and filters content that goes against predetermined criteria. This automated content filtering helps human moderators reduce their exposure to distressing and potentially traumatic UGC.
Types of Inappropriate Content Suitable for AI Moderation
Is AI content moderation better than humans? AI-powered content moderation is better than humans regarding moderation speed and scale. However, it is still far from being perfect. While some content still requires human moderation, AI-powered moderation systems can detect most types of inappropriate content.
Here are the most common types of inappropriate UGC that can be detected by AI.
Abusive Content
Abusive content comes in many forms, including hate speech, cyberbullying, and abusive behavior. A combination of natural language processing (NLP) and image processing helps AI moderators detect abusive content.
Adult Content
Adult content refers to UGC depicting sexual acts. It usually appears in forums, comment sections, dating platforms, and e-commerce websites. AI-powered adult content moderation relies on image processing to detect sexually inappropriate photos and videos.
Offensive Content
There are many types of offensive content. However, the most commonly used are profanities and naughty jokes. AI uses NLP to identify bad words. Additionally, AI moderation can recognize a string of random characters and symbols representing swear words.
The Effectiveness of AI in Content Moderation
Facebook’s Content Moderation Efforts
Facebook uses AI and human moderators in its fight against inappropriate, disrespectful, or offensive content. The tech giant lets AI technology detect and remove content that goes against its community standards. In some cases, AI sends the content to human moderators for a more in-depth review.
Youtube’s Content ID System
YouTube protects copyrighted materials using its Content ID System. The automated content identification system scans uploaded videos against its audio and visual content database. It automatically flags videos with a match and applies a Content ID claim to the matching video. This AI-driven approach allows the platform to address copyright issues even with minimal human intervention.
The Future of AI Content Moderation
AI content moderation will continue to improve as AI technology advances. Developments in explainable AI models will allow AI to explain its actions.
Meanwhile, ML makes AI progressively smarter by analyzing large amounts of data. This continuous training will improve AI’s detection method. In the future, AI may even detect images created by deepfake technology.
Collaboration between AI and human moderators will grow stronger. AI will continue to handle the bulk of content processing while human moderators address complex or ambiguous cases.
AI’s continuous evolution makes content moderation more efficient and effective. This progress will create a safer online space conducive to a positive user experience.
Lynn Martelli is an editor at Readability. She received her MFA in Creative Writing from Antioch University and has worked as an editor for over 10 years. Lynn has edited a wide variety of books, including fiction, non-fiction, memoirs, and more. In her free time, Lynn enjoys reading, writing, and spending time with her family and friends.
