How Facebook Uses Artificial Intelligence and What It Means for Marketers
If you remember the early days of photo tagging on Facebook, you’ve seen firsthand how far the company’s artificial intelligence capabilities have come. In the bad old days, the social network was liable to recommend the wrong tags for people in photos—or worse, mistake a chair or futon for your best friend (OK, maybe we’re exaggerating a bit, but the tech was still learning).
Facebook’s image recognition capabilities, powered by artificial intelligence and machine learning, have improved immensely in recent years. Now, the platform auto-classifies what’s happening in images without human captions or tags, allowing users to search photos using keywords even if images are unannotated.
And images are just the beginning. Like other major tech players, Facebook is all-in on AI. The company has, as of early 2017, more than 150 people working on AI and, reports Fast Company, has “tripled its investments in processing power for AI and machine learning research” in recent years.
The result? Facebook now uses AI to deliver the right content to users across text, photos and videos, as well as to influence how its ad product works. This has significant implications for marketers trying to reach Facebook’s nearly two billion users.
Teaching Facebook to Read Your Posts Automatically
Facebook’s AI capabilities start with text. The company’s DeepText system is a deep learning engine that understands text on the platform with near-human accuracy. Composed of several neural networks, DeepText uses these networks to process the written word as it’s used on Facebook. The resulting data can be used in many ways: the company can now understand more than 20 languages to serve a global audience and better understand queries in its Messenger app.
Thanks to these developments, Facebook is testing recommended responses in Messenger, which offer a logical next response to a friend or family member’s message. As Google and Amazon create their own voice and chatbot assistants, AI will likely play a large role in how Facebook develops its own messaging and artificial assistant capabilities.
Know What Every User Looks Like
Facebook also deploys AI and machine learning across its platform to identify people in photos and suggest that users tag people they know. Facebook’s DeepFace AI system is responsible for image identification, and at launch in 2014 it was 97 percent accurate (beating out an 85 percent accurate system used by the FBI).
Recent developments also allow the company’s machine learning algorithms to automatically annotate photos with text, so that they’re more accessible to blind users and more easily searchable by all. In 2016, Facebook open-sourced a number of its image recognition tools in the hopes this would accelerate facial recognition progress even faster.
Facebook already uses algorithms to determine which content appears on your News Feed. This has been a defining feature of the product since the beginning, though the algorithms have changed over time. But today, says the company, AI is responsible for more than just guessing what content you’ll like.
“Machine learning models are part of ranking and personalizing News Feed stories, filtering out offensive content, highlighting trending topics, ranking search results, and much more.” (Facebook)
Part of that “much more” is Facebook using artificial intelligence to combat a problem hyped during the U.S. presidential election: fake news. In 2015, TechCrunch reports, Facebook released an update to fight hoax stories, which worked by penalizing stories flagged fake by a large number of users. In 2016, Facebook experimented with using a machine learning algorithm to identify fake news.
Today, AI affects what you see when you browse Facebook, based on your interests and what your network finds interesting. But as the company teaches AI more about the context behind content, CEO Mark Zuckerberg has discussed the possibility of serving you content based on what AI—not your friends—thinks you’ll like.
If AI gets good enough at understanding text, images and videos, this could have a major impact on advertising. AI may be able to determine with a high degree of accuracy which content will appeal most to which users, leading to better targeted and higher engagement ads.
What This Means for Marketers
AI already has a major impact on how Facebook works. Its News Feed is governed by AI, and could become more dependent on the tech in the near future. The company’s machine learning systems are getting better at understanding text and images. And the ads you see could lean heavily on the preferences and insights AI reveals to the company’s data scientists.
The use of AI across every aspect of the platform is likely to accelerate. In 2016, Facebook introduced FBLearner Flow, an internal platform that shares machine learning knowledge and code across the company. At a high level, FBLearner Flow makes it possible to apply algorithms and models from one aspect of the company’s operations to others, speeding up machine learning developments.
This—and the company’s rapid AI developments—have some significant implications for marketers.
1. Keep a close eye on Facebook News Feed changes in the next couple years.
From ads to organic content, marketers rely on the News Feed to get their messages in front of consumers. If AI begins to exclusively determine what users want to see, marketers may have less insight into how those decisions are made.
The hope would be that super-effective AI would make reaching the right audiences with paid ads even easier. However, this may not apply to organic content if what your brand shares doesn’t beat out the content selected by algorithms. On Facebook, marketers may need to rely far more heavily on paid targeting than engagement from organic sharing.
2. Take a hard look at your Facebook content’s value.
Consumers and Facebook have more control over platform content than ever. AI developments at Facebook accelerate changes at scale that potentially give users more ability to filter out unwanted messages. Mediocre posts and updates are not going to cut it. Brands need to take a brutally honest look at how much value they’re creating with their content. Assume right now it’s not enough, and plan how to change that.
3. Dig into AI tools that help you better understand return on investment.
Depending on the AI-fueled changes made by Facebook and other tech giants, you might need to fight fire with fire. Keep tabs on AI tools that analyze campaigns and recommend profitable actions. These may provide critical guidance on how to generate an adequate return on Facebook and other platforms. It pays to start demoing tools that catch your attention.
About Mike Kaput
Mike Kaput is a senior consultant at PR 20/20 who is passionate about AI's potential to transform marketing. At PR 20/20, he creates measurable marketing results for companies using data-driven strategies, market-leading content, and scalable marketing technologies. Full bio.