The Role of AI in Improving Content Moderation in Social Media
UPDATED June 21, 2024
Written By Alyssa Maano
How Artificial Intelligence Enhance Content Moderation in Social Media
Social media has been woven into the fabric of society for an integral purpose—to connect people from all corners of the world. Thus, it’s rare to know someone without a social media account. However, the rise of social media also birthed pressing content moderation challenges.
As of April 2024, 62.2% of the world’s population use social media platforms such as YouTube and Facebook, among others. With this statistic, can you imagine how many social media posts are generated each day?
It’s actually mind-boggling to know that we produce 2.5 quintillion bytes of data each day! On Facebook alone, over 300 million photos are uploaded daily, and 510,000 comments are posted every minute.
With the staggering volume of online content, turning to artificial intelligence (AI) for content moderation in social media has emerged as the new ideal.
Understanding Content Moderation
Before anything else, what is content moderation in social media?
Content moderation refers to monitoring, screening, and regulating user-generated content (UGC) on social media platforms. Social media moderators act as security guards, ensuring that all posts comply with the platform’s rules and guidelines by preventing the spread of harmful content.
During the earlier days of social media, human moderators manually filter and remove inappropriate content on a platform. While this method ensures that each post undergoes a thorough review process, it can be arduous and time-consuming.
With the continuous surge of UGC, traditional methods may not meet the demand for more efficient social media moderation. More so, companies must strive to keep up with the increasing volume of posts that may contain potentially damaging content for their online image. Due to this dilemma, many companies have resorted to AI-driven social media moderation services.
The Rise of AI in Content Moderation
AI has undeniably revolutionized the way we approach work. Due to its automation capabilities, business processes can be optimized to be more efficient and accurate. This is why content moderation companies have begun embracing this technology to surpass the limitations of manual moderation.
An AI-powered system can streamline the social media moderation process by automatically identifying, classifying, and removing unwanted content based on predetermined criteria. However, an AI system is not a single technology. It encompasses several components, including:
Machine Learning
Machine learning technology allows content moderation systems to detect non-compliant activities and harmful behavior among social media users. They are trained using extensive datasets which “teach” them what content counts as inappropriate, offensive, and harmful.
The machine will then turn this information into detection and prediction tools. As a result, it can quickly detect and filter unwanted content and remove them before it reaches other users. As more data is fed into the system, it can learn better and work quicker and more accurately than before.
Natural Language Processing (NLP)
As a tool for communication, social media generates an ocean of text posts, whether through comments, status updates, or threads of conversations. With the help of NLP technology, the AI system can analyze language patterns to detect offensive language, hate speech, and even spam.
NLP can also determine the sentiment and intent behind textual content, further strengthening the capacity of the system to accurately moderate harmful texts.
Computer Vision
Aside from communication, social media also serves as a platform for sharing experiences through images and videos. Today, users freely express themselves through TikTok videos or Instagram reels. With the rise of short-form content, the demand for better image and video moderation also increases.
Computer vision combines several detection techniques to accurately identify visual elements that may be disturbing or unsuitable for social media users. It can detect objects, logos, and even text within an image that fall under the different categories of the system.
Advantages of AI for Improving Social Media Moderation
Without a doubt, effective content moderation in social media can be achieved through AI. It offers several key advantages for companies that require large-scale content processing, such as:
Scalability And Speed
The main benefit of AI for social media moderation is its ability to handle massive amounts of data in real-time. Since content is posted almost every second, human moderators struggle to keep up, resulting in poor moderation practices.
Meanwhile, by implementing AI-powered moderation, UGC across multiple social media channels can be screened in the quickest possible time with little to no error.
Automatic Content Filtering
By utilizing the aforementioned technologies, AI makes it possible to automatically filter unwanted content, including hate speech. It can classify them based on their context and mark them as safe or unsafe, supporting human moderators in the review process.
In more complex cases, however, humans still need to investigate thoroughly before flagging or removing a post.
Customization and Adaptability
AI moderation offers a higher degree of customization by training the algorithms based on the specified community guidelines and policies set by the client.
AI algorithms can be calibrated to adapt to various cultural subtleties, global sensitivities, and social media trends. With this nuanced approach, false positives and false negatives can be avoided, ensuring alignment with the platform’s values and standards.
Enhanced Consistency and Accuracy
AI algorithms learn through an iterative training process, allowing them to adjust their parameters and make more accurate decisions. Over time, the AI system can recognize cues and patterns in the datasets they are fed on and consequently adapt to evolving trends and user behavior on social media.
Case Studies and Examples
Throughout the years, social media companies have realized the benefits that AI content moderation offers. Despite their advocacy to promote free speech, it’s still necessary to remove racist, discriminatory, and violent content on the platform.
Moreover, as misinformation continues to plague social media sites, the need for faster and more reliable solutions becomes an urgency.
Here are some of examples showcasing how AI has successfully kept our social media environments safe:
Facebook is one of the biggest social media platforms, with over 2.9 billion active users worldwide. However, despite its popularity, Facebook has been under scrutiny due to several moderation issues in the past. Two of the most controversial ones are the Christchurch Attacks and the Cambridge Analytica lawsuit, which affected hundreds and thousands of users.
Due to the terrible consequences of these incidents, Mark Zuckerberg adopted a robust and proactive AI system that could instantly detect and flag problematic content, claiming that it can discover 90% of user-flagged content while the remaining 10% is handled by a team of human moderators.
Youtube
In 2022, YouTube took down 5.6 million videos that violated the platform’s community guidelines. By using an AI-driven approach, 98% of the videos showcasing extremist ideals and propaganda were also removed.
One of YouTube’s content moderation algorithms, called Content ID, is used to flag videos due to copyright infringement. Additionally, by training their machine-learning classifiers, they can easily regulate toxic speech within an uploaded video and also predict profanity, harassment, and inappropriate language.
X
Another social media platform that suffered backlash due to poor content moderation methods is X (formerly Twitter). To respond to this, the platform developed an AI-powered tool called Quality Filter to detect spam and low-quality content. However, instead of removing unwanted content, this tool only makes them less visible to users following the First Amendment.
AI is also integral to Instagram’s content moderation efforts. It can analyze all forms of online content and remove those that go against their community standards. In other cases, the content will be forwarded to a human moderation team for further review and making the final decision.
Challenges and Ethical Considerations
The integration of AI in the content moderation process carries several challenges and ethical implications, including the following:
Technical Challenges
AI is not a fool-proof content moderation solution. It has its own limitations in terms of context comprehension and multilingual capabilities. It might take some time for the system to recognize nuances in language due to the subjectivity of human speech.
For example, some words and behaviors that are not deemed offensive to a certain demographic may be interpreted differently in another region.
Additionally, AI systems may be limited to understanding a single language based on the datasets the algorithms were trained on. The key to dealing with these technical challenges is to feed the system with diverse datasets to enable accurate contextual understanding and effective moderation across various languages.
Ethical Concerns
A significant ethical concern with AI content moderation is the possibility of perpetuating bias. If trained using unrepresentative datasets, it can shape NLP models to associate specific words and or phrases with existing prejudice and harmful stereotypes, leading to unfair moderation decisions.
To mitigate potential biases, it’s crucial to meticulously analyze the datasets during the development stage. Developers should take a proactive role in continuously monitoring and testing the performance of the system to ensure that it fosters inclusivity.
It’s also important to practice transparency and accountability to let users understand how they carry out the moderation process and get collaborative feedback to eliminate AI bias.
Human-AI Collaboration
Despite its promising features and capabilities, AI is still far from being a standalone solution for content moderation in social media. Although it can enhance the review process, human oversight is still needed to ensure the quality and precision of its performance.
Human moderators are still needed to analyze complex cases and respond to user appeals. They offer a human touch to the moderation process, ensuring thorough and fair judgments.
The Future of AI in Content Moderation
The role of AI in improving content moderation in social media is pivotal and ever-evolving. As social media platforms continue to grow, the sheer volume of UGC necessitates advanced solutions. AI's integration into content moderation addresses this need by offering scalability, speed, and enhanced accuracy, ensuring a safer online environment.
Emerging AI technologies such as deep learning, advanced natural language processing (NLP), and more sophisticated computer vision systems promise to further enhance content moderation capabilities. These technologies will refine the process of detecting harmful content, accommodating cultural nuances, and evolving social media trends.
Looking ahead, the future of AI in social media content moderation is promising. We can expect AI systems to become more adept at understanding context and subtleties in human communication. The continuous improvement in AI training data will also help mitigate biases, leading to fairer moderation practices.
Moreover, as AI continues to advance, it will likely play a critical role in educating users on how to use social media in moderation, promoting healthier online interactions.
Ultimately, content moderation companies that use a combination of AI and human oversight can create a robust framework for social media moderation services, ensuring that platforms remain safe and inclusive spaces.
Partnering with a content moderation service provider like Chekkee is essential as we navigate the complexities of digital communication and strive to foster respectful and constructive online communities.Stay ahead of your moderation game. Contact us today!
