Social media platforms, from Facebook to Instagram to LinkedIn and Twitter, make intensive use of AI to process all the data their human user feeds them – and with close to 3 billion people using at least one social media app around the globe every day, the amount of data to process is daunting.
Artificial Intelligence (AI) is a branch of computer science whose goal is to decipher data, often using algorithms in computer programs to achieve certain tasks instead of humans. Yet, it doesn’t function entirely on its own but requires human orders. AI is powered by machine learning, which enables systems to process large quantities of data, and make predictions that improve in accuracy over time. These tools can be used to personalize interests and experiences to an unimaginable degree.
Projected growth for the AI market jumped from $633 million in 2018 to more than $2.1 billion by 2023, according to estimates from Markets and Markets.
We use AI every day without even realizing it: all smartphones are powered by AI, from voice assistants to geolocalization to predicting email content to giving product recommendations from Amazon or Netflix. When it comes to social media specifically, AI helps manage platforms efficiently: it helps engage users, analyze the data they provide, identify behavioral patterns and hashtags, monitor comments, translate automatically, process the content of text and images, help detect spam, and much more. Here are 8 ways social media leverages the power of AI to manage and improve user experience – even if sometimes at the expense of privacy.
With more than 2 billion users, Facebook employs AI for a variety of purposes. The platform uses everything from neural networks who learn to tag, to image recognition, to machine learning that seeks to optimize search results and filter users’ news streams. But the company is also using AI to flag suicidal posts, with the help of a tool called DeepText, which analyzes the meaning of posts on the platform and can look for self-harm-related content. With one death by suicide every second on the planet, Facebook has the potential to help save lives.
LinkedIn uses Machine learning and AI to help match job candidates with employers, using an algorithm that can predict who could be the best fit for the role. More than that, LinkedIn employs AI to suggest people to connect with, feed certain posts to your wall and give you job recommendations relevant to your profile.
Facebook and Instagram have long used AI to analyze visuals. Facebook notably uses machine learning to recognize faces in pictures in order to help you find Catfish (fake accounts that use your picture). Twitter, for its part, notably uses AI to crop images using face detection or to create a thumbnail from a bigger image, recognizing the important parts of the image and putting them in the preview. And, whenever you use a social media app to take a selfie and apply filters to it, it is AI that is working to track your facial features. Snapchat too became renowned for its filters that move with your face in real time.
Depending on your behavior on social media platforms, AI and machine learning can decide which ads to place on your feed. Instagram for instance tracks which posts garner more engagement or more searches, and uses AI to help companies target their advertisements.
AI provide tools to automatically generate social media content, including hashtags, and auto-schedule posting. Then, several other AI tools can provide insights into the reach of your posts, and details about your audience, thus helping you track your brand’s online reach and strategize your next moves – switch audiences, run optimized paid ads and more, for a reduced cost and time.
It is thanks to AI that platforms such as Facebook, Instagram, and YouTube can recognize and flag so-called bad content – including nudity or sexually suggestive items, hate speech, excessively violent words, spam and fake profiles.
Video-centered platforms such as TikTok and YouTube use AI to train algorithms to produce more engagement: the more you interact with a certain type of video, the more this specific type of video will be recommended to you. The more you watch, the more the algorithm can refine your preferences and suggest content that you might like, which can appear in YouTube’s ‘up next’ feature for instance. Instead of relying on the number of views a video gets, YouTube’s algorithm is based on the time people spend watching videos.
Tinder and other matchmaking apps heavily rely on AI to bring people together according to their profile and preferences. Moreover, Tinder’s AI tools work to remove harmful content that could bother you and block offensive users by finding potentially harmful messages and flagging the