The evolution of artificial intelligence defined 21st-century technologies. It transformed the way businesses and users interact with each other.
From facial recognition to product recommendations and interactive screens to smart assistants, AI technologies offer endless possibilities.
In this digital world, the massive amount of user-generated content flooding multiple communication channels is overwhelming. Therefore, leveraging AI content moderation is vital to business strategy and ensuring a safe user environment.
This article explains the importance and power of AI in scaling content moderation.
What Exactly Is Content Moderation?
Content moderation is the process of regulating and monitoring user-generated online content against specified rules and guidelines. It then makes a judgment on whether the content is appropriate for the digital space or should be removed.
The digital era calls for billions of photos, posts, tweets, and other content to be shared regularly. Therefore, all online platforms require continuous screening to filter unwanted content and uphold fundamental rights. However, it’s challenging to determine if the content is malicious, inappropriate, or harmful to the users.
Why Is AI Content Moderation Necessary?
As the name suggests, AI content moderation employs artificial intelligence to impact digital content moderation. It scrutinizes online content to an unparalleled level of accuracy, far exceeding the efficacy of manual monitoring. AI content moderation means leveraging the power of ML algorithms to learn from existing data and review user-generated content online.
Compared to manual content moderation, AI technology speeds up the moderation process and eliminates errors. Most businesses are now adopting AI to combat spamming and other irrelevant information in their content moderation.
The content moderation strategy for each company varies based on their review systems. But all AI content moderation includes one or both of the points below:
- Pre-moderation: AI moderates content before publishing it online. Content assessed to be harmful is removed while the safe contents are visible to the users.
- Post-moderation: AI reviews the content after publishing it online. If any user reports the content as harmful or inappropriate, AI reviews it and takes appropriate actions.
How Does AI Content Moderation Work?
Similar to other machine learning tools and technologies, AI moderation systems are also trained on large datasets previously classified by humans. The AI systems learn from the data to recognize different types of content.
AI content moderation can ease the review process for humans and allow companies to scale faster. Depending on the type of media content, numerous AI techniques are used for content predictions.
Computers use natural language processing (NLP) to identify human language and emotions. This algorithm is used to comprehend the intended meaning of a text and filter or remove offensive language. The text is then assigned a category based on its sentiment.
Sentiment analysis is used to help computers identify the tone and sentiment of the content. The text is then grouped into categories like anger, sarcasm, bullying, sadness, and such, giving a positive, neutral, or negative label to the content.
Computers use knowledge Bases to gauge through familiar information from the database to identify content likely to be fake or spam.
Entity Recognition is another approach to AI content moderation to identify company names and locations. This AI technique informs of the frequency of your brand name mentions on specific websites or by people from different locations.
Images & Videos
AI content moderation for images combines text classification with visual search techniques. This method identifies harmful images and pinpoints the exact location of the harmful content in the image. Image moderation also uses image processing algorithms to identify distinct regions and then categorize them based on predetermined criteria.
If the image contains text, object character recognition (OCR) is used to moderate the entire content and identify the most prominent objects. This AI technique uses an object detection algorithm to analyze images and detect abusive or offensive words and body parts within the data. This is to identify target objects that violate platform standards.
For video content, AI moderation also has the power of scene understanding. Computers are adept at comprehending a scene’s context for better decision-making.
For voice content moderation, AI technology uses voice analysis. It makes use of several AI-powered tools to study speech sounds. It performs tasks like voice-to-text transcription, voice tone interpretation, NLP, and sentiment analysis for speaker identification.
Other Types of Data
Irrespective of the type of content, companies often rely on reputation systems to determine which content they must trust. This technology enables customers to rate peers or businesses based on their levels of satisfaction with the product or service.
Besides, reputation technology detects fake news sources and labels them as untrustworthy. The good thing is AI content moderation continues to produce new training data for better results.
When computers forward content to a human for review, they label it as safe or harmful. The tagged information is then fed back to the algorithm to increase its accuracy for future use.
Moreover, AI content moderation systems classify users or sources with a history of posting spammy or obscene content. They label these sources as non-trusted and examine their future content more closely.
User-generated content (UGC) is present in various industries besides social media. These contents are integral to the digital world, from online reviews to opinions.
In the present situation, UGC includes anything from text, image, video, audio, and other relevant content found online. However, newer forms of content may appear in the future.
Therefore, efficiently managing user-generated content must be a central element of any company’s strategy. AI content moderation is the most effective way to ensure a positive customer experience and reputation consistent with branding.
It is crucial to pay attention to how you distribute your resources and labor as your company continues to expand. One of the most effective ways to regulate and monitor high-quality content is using AI-powered tools combined with human supervision.
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