Using AI and Machine Learning for Content Moderation
Artificial Intelligence (AI) is the next technological revolution in the modern world. It is a technological innovation that will change how organizations operate and how people engage with data in the twenty-first century. The main goal of artificial intelligence is to build intelligent devices and algorithms that can carry out complicated tasks that call for the human intellect.
Many user-focused services have been impacted by AI-powered technology. Google uses machine learning to anticipate users' search intentions and provide them with highly accurate results, and Amazon uses the same technology for logistics and product suggestions. Even Tesla's self-driving cars use a variety of AI algorithms to prevent accidents and traffic jams.
It is impossible to debate the significance of artificial intelligence given how many sectors and facets of our everyday life the technology has already altered and disrupted. "Content moderation" is one of them.
This article will explain what content moderation is and the role of AI and machine learning in content moderation.
What is AI Content Moderation?
Content moderation is the process of screening and monitoring user-generated online content. The goal of content moderation is to provide a secure environment for both the brand and its customers. Online platforms have to watch over this material to ensure it is suitable and that pre-established rules are followed.
Additionally, it is crucial to ensure that the online conduct is suitable for the platform and target audience. The burden of removing objectionable content (such as nudity)is enormous. At this point, machine learning is essential for maintaining the cleanliness of websites. Online content can be categorized, photos can be processed, and undesirable content can be filtered out using the power of AI and machine learning.
Types of user-generated Content and Content Moderation Applications
Text, images, and videos are the three primary types of user-generated content. Everything else fits into one of these categories. Any of the following are examples of user-generated content:
● Content shared on social media
● Reviews and feedback from users
● Blog articles or any type of blogpost
● Video material (including live streaming and augmented reality lenses/filters), among other things.
● Infographics
● Podcasts
● Q&A Forums (including comments)
● Product reviews
● Case studies
● Testimonials
Text Content
Simply put, too much text material is released online to be evaluated manually, and text data can not be reviewed without content moderation AI. So, how does content moderation work while it is scanning the texts?
Natural language processing algorithms are utilized to interpret the emotions in text and grasp the intended meaning. Text categorization enables the text or emotion to be classified according to the content.
For instance, sentiment analysis can determine the tone of communication and classify it as bullying, rage, harassment, sarcasm, etc., before categorizing it as positive, neutral, or negative.
Another AI content filtering method that removes names, places, and businesses is entity recognition. This kind of content moderation AI technique may inform you of the frequency with which your business has been discussed on a particular website, even the proportion of reviewers who are local to a specific area.
Image content
It would be unreasonable to expect personnel to manually moderate every single picture, given the vast number of photographs shared online.
Although asking users to report content breaches might seem beneficial at first, this method is unreliable in the long term. What one moderator may deem objectionable might be seen as neutral by another. Hours of manual content moderation may also tax the eyes and lead to exhaustion, which is bad for employee health.
This is where content moderation comes into play. AI-based Image Content moderation uses image processing techniques to locate certain regions inside the image and classify them according to a specified criterion. Object character recognition (OCR) can control the complete content piece if the text is present in the picture.
These AI methods for image content filtering enable the recognition of any objects or body parts in unstructured data as well as inappropriate or abusive language. The content can be published after it has been authorized. However, content that has been flagged is forwarded to the next round of human review.
AI Content Moderation Challenges
Human moderators are becoming more challenging to manage large amounts of information as the number of material users provide increases. Because of social media, users' expectations are shifting, and they may become more demanding and less tolerant of the rules and guidelines governing online content sharing.
This makes it an even more significant challenge for moderators to manually check for inappropriate internet content. In addition, the inherent discomfort of manually moderating content comes from the potential for human moderators to be subjected to upsetting material on an ongoing basis.
Moderating content software driven by AI like Cameralyze becomes relevant here.
The partnership Between AI and Human Content Moderation
It is widely known that there is just too much user-generated content (UGC) for human moderators to work on, not to mention the mental fortitude required of workers to seethrough content that may be upsetting to specific users.
The development of AI-based content moderation is a direct response to the everyday problems businesses must overcome to discover effective methods to help their customers.
The other side of the coin is that no matter how quickly artificial intelligence becomes, it will never be able to filter extremely complex stuff that requires a piece of profound human knowledge, creativity, and subtlety. This is the case regardless of how fast artificial intelligence gets, and this is something that can be done most effectively by human content moderation alone.
If businesses combine these two strategies, they will be able to achieve the best outcomes possible for regulating material in order to create online communities that are better, safer, and more varied.
Both human content moderation and AI content moderation approaches have the potential to set up a functional framework that will enable companies to achieve the best possible moderating outcomes in the digital sphere.
To Sum Up
It becomes challenging for businesses to keep up with the need to check the information before it goes live as user-generated content keeps growing. One efficient answer to this expanding problem is AI-based content moderation.
AI can safeguard moderators from objectionable content, enhance user and brand safety, and simplify operations by relieving human moderators of tedious and unpleasant jobs at various levels of content moderation via different automated technologies. Companies should find that combining AI and human experience is the best strategy to control dangerous online content and ensure a secure environment for visitors.
Content Moderation with Cameralyze
As your company grows, paying attention to how you distribute your resources and labor will be crucial. The most effective approach to regulate content and continue to grow can be the key, thanks to AI-powered automation under human supervision. Developing a content moderation approach is crucial for achieving this.
At this point, AI automation can change lots of things. Using a solution like Cameralyze allows you to train AI models on images, documents, and text data because Cameralyze is a ready-to-use solution with API integration. So you can link anything to your current systems and simplify your manual process without creating a single line of code.
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