A colossal quantity of user-generated content goes online continuously. Henceforth, it is challenging to stay on top of content moderation. Furthermore, there are risks associated with the exposure of human moderators along with making manual moderation less desirable. This is where contextual ai applications are required. Content moderation is vital in the present functioning of digital platforms. It renders the required safety and protection against hazardous and illegal content.
What is Automated Content Moderation?
Automated content moderation encourages the use of technology to accelerate the process of eliminating harmful and inappropriate content. Furthermore, it also automates the tedious task of reviewing every single post. It incorporates the amalgamation of several algorithms and human reviews in certain cases.
It is the technology that executes the maximum task. Human intervention is required or necessary only after the automated screening process is complete, in certain situations. The process of automation in content moderation is executed with the support of AI-backed algorithms. It can filter out content that is recognized as sexually explicit, illegal, and harmful for visual videos, texts, and live streams. In cases where AI fails to recognize the threshold for moderation, human input becomes necessary.
The working Mechanism of Automated Content Moderation
Depending on the demands and needs of the platform, automated content moderation can be used in multiple ways.
The methods in which content moderation can be used are mentioned below:
- Pre-moderation algorithms evaluate every single content before it goes live.
- Post-moderation is the most popular method where content is checked right after it has gone live.
- Reactive moderation allows users to report posts for inappropriate and illegal content after they have been published.
Irrespective of the methods chosen, the primary step is to set the moderation policy. The user needs to define and set clear rules and types of content that need to be eliminated, based on the strategy of the content platform. The thresholds also need to be defined so that the contextual ai applications and moderation tool can differentiate the contents that violate the standards and moderation policies.
In common cases of post-moderation, the user-generated content gets processed by the moderation platform. Based on the moderation policies, and defined thresholds, and rules, inappropriate content gets removed immediately. Thanks to automated content moderation, this can take place instantly after the publication. Often certain contents are complex and tricky for the AI algorithm to understand, thereby demanding human review.
Content moderators evaluate and examine the questionable content via the moderation interface. The final decision of removing or retaining a specific content depends on the moderator. When content gets directed for manual or human moderation, the actions of the human moderator’s training data feed into the automated content moderation platform. This is how the AI gets to learn about the minute details in human decisions to keep or remove certain content. With the advancement in technology, algorithms are getting enriched making the automated process more precise.
Key benefits of Automated Content Moderation
Speed
The digital landscape demands quick moderation. Nobody likes to wait days before their content or social media post goes live as it needs to be reviewed by a human moderator. One of the biggest advantages of automated contextual ai applications is the speed. Moderating a wide array of content that goes live every second seems an impossible task without an automated technology. With AI-backed algorithms, the process of moderation gets faster and more efficient. Content that is illegal and harmful is removed instantly. Doubtful content gets filtered out and often demands human review. The whole cycle is quicker, providing better outcomes to the end-users.
Safeguarding of Human Moderators
Another benefit is associated with the work of human moderators. The automated content moderation prevents the moderators from going through disturbing and harmful content as the automated moderation screens them out. The negative impact on the emotional and mental health of human moderators is not unknown. Furthermore, the risks and the challenges can be curbed significantly with the use of AI moderators.
Conclusion
Artificial Intelligence (AI) is making a significant impact on digital content moderation. The presence of contextual ai applications renders an optimal level of precision. With the help of AI-supported algorithms, and machine learning of existing data, content moderators can easily review the decisions for user-generated content.
