4.1. Where does our writing go? - The invisible journey of content

Today, the Internet is truly in the age of “content overload.” Anyone can easily express and share their thoughts and information. This platform for free communication is one of the greatest attractions of the digital world, but it also casts a dark shadow. It is the spread of harmful content.

Limitations of rule-based systems: Filtering that does not understand context

In the past, rule-based systems were mainly used to block such harmful content. This method involves setting specific keywords and automatically filtering or blocking content that contains those keywords.

Rule-based systems are efficient at applying simple and clear rules, and can still be applied intuitively and quickly in cases where specific words or expressions must be clearly prohibited, such as “prohibited words.” However, there was a fatal limitation in that it did not understand context, which led to problems such as false positives and false negatives.

Ultimately, rule-based systems alone had clear limitations in creating a pleasant online environment in the face of the complexity of language and the diversity of user expressions, and these issues soon became the main motivation for introducing AI technology.

The Reality and Challenges of 24-Hour Monitoring: The struggles of human operators

So, before AI existed, who kept an eye on this vast amount of content? This was the responsibility of the monitoring operators. Operators are the frontline guardians who review content pouring in 24 hours a day, determine whether it is harmful, and immediately delete problematic content or impose appropriate sanctions on users.

However, despite their hard work, the practical limitations were clear.

Physical limitations of mass content processing: Large-scale services used by tens of millions of people generate countless pieces of content every day. It is physically impossible for humans to review all of this in real time.
Difficulty in maintaining consistency in judgment criteria: Determining what constitutes harmful content requires complex criteria and an understanding of social context. However, since this is done by humans, subtle differences in judgment may arise even with clear guidelines. It is also difficult to maintain consistent criteria for evaluating large-scale content, as fatigue and subjective interpretations may come into play. In addition, continuous exposure to unpleasant or violent content can also be a factor that increases the psychological fatigue of operators.

AI adoption: not a choice, but a necessity: Human-AI collaboration model

AI performs well in quickly categorizing repetitive and large amounts of content, detecting complex patterns, and finding areas that humans tend to overlook. AI can also play a supporting role in the labeling process for training data, reducing the amount of work required by humans. With this assistance from AI, human operators can move away from simple review tasks and focus on ambiguous cases that are difficult for AI to judge and on deeper issues that require ethical judgment.

Through this collaborative model between humans and AI, we were able to expect the following synergies.

Maximizing efficiency: With AI handling initial filtering and classification, operators are left with far fewer suspicious pieces of content to review, dramatically improving operational efficiency.
Quick response: Before harmful content spreads, AI detects and blocks it in real time to minimize its impact.
Strengthening consistency in judgment: AI makes decisions based on predefined algorithms and learned data, so there is little room for human bias, enabling more consistent moderation standards to be applied.
Operator protection: By preventing initial exposure to harmful content, AI helps reduce the frequency with which operators are directly exposed to unpleasant or dangerous content, thereby alleviating psychological stress.

In the next chapter, based on the necessity of AI adoption, we will examine specific AI technology examples that effectively detect and block the harmful nature of text, images, and AI services themselves.