This article has been written by Swati Mujumdar pursuing a Remote freelancing and profile building program from Skill Arbitrage.

This article has been edited and published by Shashwat Kaushik.

Introduction 

The internet has become an inseparable component of human life. It is bringing the world closer. Social media is a very active and fast-moving area. A large amount of content is being generated every day in the form of text, social media posts, blogs, images, videos, etc.

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Artificial intelligence (AI) is a field of computer science that helps study intelligent machines. It is an emerging field of technology. The term “Artificial Intelligence” is used for the intelligence of machines or software. AI relates to the development of computer systems that can perform tasks which are normally practised by humans, such as learning, problem solving, understanding languages, etc. AI helps implement novel concepts and unique solutions to resolve complex challenges. Some of the common applications used in day-to-day life are Google search, Google Assistant, Self-driven Cars, Chat GPT, etc.

Content moderation : lesser-known aspect of AI

People are embracing AI generated content available on various forums for efficiency, accuracy, and domain enhancement in various fields. With the amount of user generated content (USG) uploaded on on-line platforms, it has become impossible to identify and remove the inappropriate content with the help of human moderators. Human moderators are struggling with manual content moderation. Content moderation by AI can reduce this burden with efficient, repeatable, and reliable solutions.

AI is mainly used where automation is necessary to avoid repetitive work. This is achieved through a variety of techniques, such as machine learning (ML), deep learning, and natural language processing (NLP).

  • Machine learning (ML): Machine learning is a key component of data science. Algorithms are trained to make projections from available data. The projections are further used to improve the performance of machine learning algorithms. From the content moderation perspective, machine learning algorithms identify and isolate potentially harmful content and eventually remove it in accordance with the set standards and guidelines of the platform.
  • Deep learning: Deep machine learning is also known as supervised learning. It can use unstructured data like text or images in their raw form. It can auto-determine the set of features to differentiate various categories of data from one another.
  • Natural language processing (NLP):  NLP is a part of AI that helps machines identify and interpret natural language. It can perform repetitive tasks automatically. Speech recognition, chatbots, and analysis of sentiment from natural language inputs are some of the real-life applications of NLP.

The internet is a double-edged sword. It has become a battleground for harmful and inappropriate content. Social media is a very active and fast-moving area. AI based content moderation is an effective way to keep platforms free from inappropriate content. AI content moderation tools can review, filter and flag content that violates the guidelines of the forum. A vast amount of on-line content, like hate speech and sexual abuse material, poses a big threat to maintaining healthy and safe on-line environments. AI content moderation can delete such objectionable material and maintain harmony on the platform.

Process of content moderation

Following is the process that is usually followed for content moderation.

  • Uploading content: The process starts when users upload content on websites or various social media platforms. The content may be in the form of text messages, images, videos, etc.
  • Analysing content: AI algorithms analyse uploaded content using “machine learning” techniques and natural language processing.
  • Inappropriate content identification: If the uploaded content is harmful, it is flagged out and forwarded to human moderators for further action.
  • Role of human moderators: Once the content is flagged out and forwarded to human moderators, they analyse it carefully from the legal aspect and check whether it violates guidelines of the forum. The content is further approved or rejected as per standard guidelines.
  • Improvement in AI algorithms: Machine algorithms learn feedback provided by human moderators for further accuracy in identifying malicious content in future. Thus, by using learning techniques, human moderators can improve algorithm performance in future.

Types of content moderation

Various ways of content moderation are as follows:

  • Pre-moderation: The content is reviewed and approved prior to publishing. This ensures that quality content is posted on the website. However, it might not be cost effective.
  • Post-moderation:  In post-moderation, revisions are made to the content after posting it on the platform. This method is not so effective as there are chances that users can use inappropriate content prior to its removal from the website.
  • Reactive moderation: Reactive moderation is carried out in response to a complaint by a user regarding inappropriate content.
  • Proactive moderation: It uses machine algorithms and detects harmful and offensive content before publishing it on the platform. This establishes a positive user experience as it deletes problematic content prior to posting on platforms.
  • Hybrid moderation: Hybrid moderation ensures inclusive coverage of proactive and reactive methods, which helps in saving time.

Uses of AI in content moderation

AI content moderation is performed using modern artificial intelligence technology. It can be used for multiple purposes, such as:

  • Creating a safe and positive on-line environment: AI can efficiently identify and remove a variety of harmful content, which helps to create a safe and positive online environment for users.
  • Quick analysis of data: AI can accelerate the moderation process by quickly analysing large amounts of content. It helps human moderators focus on the on-line material, which requires immediate attention.
  • Tailoring moderation process: AI can help in adjusting content moderation as per the guidelines set by the respective forums / platforms.
  • Ensuring consistency in content moderation: AI algorithms learn and improve accuracy by identifying harmful as well as biassed content. This brings consistency in content moderation across the respective platforms.
  • Confirming diversity and inclusion: The detection of biassed content helps AI create an environment where all voices are heard and respected.

Benefits of AI in content moderation

AI powered content moderation is a powerful tool that helps platforms manage biassed and harmful content effectively. AI algorithms are programmed in such a way that they strictly follow pre-defined guidelines. This maintains consistency in the content moderation.

  • Platform reputation: Using AI moderation tools, platforms can be more vigilant about content published. This will help them retain their users.
  • Joyful experience: AI algorithms can single out images, video clips, and articles with inappropriate content and give safe and enjoyable experiences to the audience.
  • Scalability: AI content moderation is a fast, accurate and cost-effective technology. It can analyse data much faster than human moderators. It is a preferred choice for large database platforms. In this way, community guidelines are adhered to.
  • Round the clock monitoring: AI can constantly monitor the content. This helps reduce the workload of human moderators.
  • Social media analysis: AI can identify, isolate, and delete inappropriate content and user interactions on social media.

AI can help limit the use of the following:

  • Hate speech: AI can find and delete text for keywords and phrases to identify potential hateful language, racial discrimination, and child abuse.
  • Terrorism: Human moderation is based on individual experiences and ideologies, which could possibly lead to personal biases. AI can auto filter and flag out content that promotes terrorism in an unbiased manner.
  • Misleading information: Promoting misinformation related to violence, or unlawful activities can be controlled by AI content moderation.
  • Malware and phishing links: AI can identify suspicious websites and links associated with harmful content.

Types of AI-powered content moderation tools

Different types of AI-powered content moderation tools are:

  • Text analysis tools: These tools can be used to identify harmful content in text, such as hate speech, spam, and sexually explicit content.
  • Image analysis tools: These tools can be used to identify harmful content in images, such as nudity, violence, and child sexual abuse imagery.
  • Video analysis tools: These tools can be used to identify harmful content in videos, such as hate speech, violence, and child sexual abuse imagery.

Potential challenges in AI content moderation

AI content moderation is helpful in controlling the appearance of inappropriate material on social media platforms.

  • Bias: AI algorithms could possibly be trained to remove content or suppress certain views. This would lead to unfair suppression or removal of specific content. Thus, limiting free speech.
  • Over-censorship: AI may project legitimate content as harmful by setting certain algorithms; this would lead to unnecessary censorship and suppression of creative content.
  • Threat to online security: Malicious actors can manipulate and misuse AI systems to spread misinformation. This would pose a threat to online security.
  • Deep fakes: Online content may be in various formats, like images, videos, audio, and memes. Deep fakes pose a great challenge as fake but convincing images, audio, and videos are created using machine learning.
  • AI hallucinations: AI hallucinations occur when an AI model generates false information but presents it as if it were correct. AI hallucinations spread biases and can misguide people with factually incorrect information.
  • Less transparency: The internal workings of AI moderation systems are complex. AI moderation systems make it difficult for users to understand and challenge biassed decisions. This can lead to frustration and distrust in the moderation process.
  • Job displacement: AI may replace human moderators. This would lead to job losses in the content moderation field. 

What everyone should know about AI content moderation

Content moderation is challenging. It is not always possible to moderate content in such a way that all the stakeholders are happy. AI is not a perfect solution to content moderation, although it is a powerful tool. The role of human moderators is crucial to ensuring fairness and perfection. Platforms should be more vigilant about checking how their AI moderation systems work. They should take ownership of their decisions. Users should have the right to appeal and challenge AI-based decisions. Content moderation technology is evolving every day. Developing an effective content moderation system needs time, financial allocation, and talented/skilled developers. Due to constant improvements in the field, it is necessary that organisations keep a cordial and collaborative approach to managing malicious content. Proactive measures and periodical audits of posted content are necessary to reduce the risk of bias in AI algorithms. The balance between efficiency and fairness in content moderation can be maintained with the strengths of AI and human supervision. To ensure that technology is used for content moderation ethically and responsibly, it is necessary to use calibrated data sets and set guidelines and government . regulations for avoiding abuse of technology. AI technologies can be used to encourage positive engagement and discourage users from posting potentially harmful content.

Conclusion

The Internet is connecting humans with informative material, entertainment, and communities across the world. Harmful content posted on various platforms is posing a threat to our safety, security, and stability. The rising wave of artificial intelligence is giving us hope to fight against these vulnerabilities. It’s the duty of all humans to make positive use of this modern technology and make this world a better place to live.

References

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