Growing Need of AI moderation
The era of digital media as given users new levels of connectivity, but also unique challenges such as cyber bullying. I expect the importance of tools for effective moderation to be higher than ever. It sounds hopeful so far especially given the kind of problem that AI solves for in identifying and preventing harassment on digital platforms. Examples of this include mainstream social media platforms that state that up to 90% of policy-violating content is found using AI before users report it.
How AI Identifies Harassment In the Online World
Built with NLP (natural language processing) and machine learning technology, AI technologies analyze textual and multimedia content. Image captionAutomated moderation systems are designed to use these examples of abuse to learn what it looks like elsewhere Facebook and Twitter employ A.I. to analyze tens of millions of posts each day, identifying suspect hate speech for further review. For instance, the use of artificial intelligence (AI) systems to cut hate speech exposure by half on these platforms over the last year is a good example.
Enhancing Accuracy and Speed
The true advantage of AI in the realm of online harassment is its efficient, swift and accurate way of handling abuse. The volume of content generated online far exceeds the capabilities of human moderation in its traditional sense. Since platforms like YouTube are creating hundreds of hours of video per minute, it is essential for AI systems to be able to analyze thousands of posts per second. And not only is their time performance incredible at first but their learned accuracy is always going up. AI is getting better at processing context and nuance, which is critical for identifying harassment correctly.
AI Barriers in Detecting Harassment
AI in the Detection of Harassment: Despite the benefits of AI for the detection of harassment, there are challenges involved. This means that false positives and negatives can occur due to the subtleties of language, such as sarcasm or missing cultural references. In addition to this, the user explained how these harassers are constantly evolving how their approach to try to bypass the AI detection to require consistent updates to the AI. There are also fears of AI bias which can come from biased training data. These challenges cannot be resolved with AI alone, but rather need to be tackled in a balanced manner that harnesses AI with human review.
Read Part 2: AI: AI for Proactive Prevention
Artificial intelligence just isn't for identifying harassment; it might also stop it AI can recognize possible harassment before it even starts by looking for odd communication behaviors. This more proactive method involves getting mods involved, or stepping in yourself for interactions that are likely to result in harassment. At the moment, they are testing out these systems in-game and on social platforms, and the early signs show a reduction of up to 40% in toxic interactions.
Impact of Ethical issues
With the rise of AI in our digital interactions, it is important to take the ethical implications of its use into account. AI systems must also respect user privacy and guarantee fairness in their deployment. Given that AI now helps determine who can say what on platforms, it is necessary for both those systems and the people who oversee them to be transparent, and held accountable.
Learn more about the difficulties and ethical dilemmas involved in the use of AI for content moderation in The nsfw ai - a story about how algorithms learn to moderate content to get a case study of working with AI deployment in sensitive areas.