Companies both big and small are benefitting from big data collection. As billions of people share texts, tweets, photos, and videos, tech companies are building a vast database of information. This information is worth money.
The advent of artificial intelligence is providing a method to sort through this data and harvest it. One of the most promising frontiers is facial recognition. AI has reached the level of sophistication where it can recognize faces as well or better than humans. For entrepreneurs, this means opportunities to use facial recognition for sales and marketing, as well as selling collected data as an additional revenue stream.
True to its name, Facebook has the largest collection of facial data in the world. Facebook has been collecting this data since its inception. We are literally talking about billions of user photos. If you use Facebook, they have your face. Even if you do not, someone may have posted your picture. As the collection of facial data becomes more ubiquitous, it may become impossible for your face to remain unrecorded.
The marketing possibilities are endless. When consumers, whether online or in a brick-and-mortar store, can be tracked by their faces, it becomes possible to slant marketing campaigns toward them on an individual basis. Right now, companies like Facebook and Google use online search history to target ads to certain users. Facial recognition allows the recording of people’s online activity to go far beyond their searches. It also provides a way to bring the kind of targeting seen on the Internet into the brick-and-mortar world.
Facebook is keen on facial recognition software and so created Deepface. Deepface uses AI deep learning to recognize faces based on photos. The program utilizes a nine-layer neural network to record faces and is able to recognize them again, even pick them out from a crowd. At the present time, it has a 97.2 percent rate of accuracy, 0.2 percent better than the human average. Facebook is still improving Deepface, which may hit 100 percent accuracy soon.
Facial recognition does not stop with identifying people. AI deep learning also identifies emotions. As humans, we are accustomed to reading faces. Unless someone has a good poker face, we can at least make an educated guess about their mood and interest level. AI can be trained on what to look for in a face to gauge, for instance, interest level with the same accuracy as humans.
But humans cannot log faces in a database or simultaneously read many people at once, as AI promises. This efficiency separates AI from human beings and allows facial recognition to be employed on a mass scale. This not only opens marketing and sales opportunities, it also holds the promise of big profits from data mining. When businesses collect data on customers, its worth money in the AI powered world.