Beauty, it is said, resides in the eye of the beholder. What if that beholder is a machine learning model being trained to describe and classify fine works of art? That's what AI researchers at Zhejiang University of Technology in China are attempting to find out by comparing the ability of different models trained on a growing list of image data sets to classify artwork by genre and style. Whether these models can be trained to respond emotionally remains to be seen. Preliminary results from one study published earlier this month in the journal of the Public Library of Science highlighted the utility of using convolutional neural networks (CNNs) for demanding tasks like art classification.

In the past, it was fairly easy to gain visibility and engagement on social media. But as the number of users and platforms increased quickly, competition stiffened. Moreover, social media has evolved from a place to connect with friends into a full-fledged publishing and advertising channel. It can get overwhelming to track countless metrics, like reach, engagement rates, and more. Since everybody is competing for limited audience attention, you need to keep a tab on your competitors' metrics as well.

If you search for "man" on Google, most of the image results you'll get are of white males looking confidently at the camera. "Woman," meanwhile, brings up pictures of women that appear to have been taken from a male gaze -- and yes, you guessed it, they're also predominately white. That lack of inclusion in machine learning is what "Untrained Eyes," an interactive art installation, aims to shed light on. The project, created by conceptual artist Glenn Kaino and actor/activist Jesse Williams, comes in the form of a sculpture that uses five mirrors and a Kinect to get its point across. Stand in front of it, wave and, within seconds, you'll be presented with an image that will "match" your appearance.

What if you stood in front of a mirror and saw someone who barely looked like you? That's exactly what happens in Untrained Eyes, an interactive sculpture debuting today at the Engadget Experience, a one-day event that showcases exhibitions which mix art with technology. Untrained Eyes, created by conceptual artist Glenn Kaino and actor Jesse Williams (Grey's Anatomy), doesn't require a headset to be experienced. Instead, the project uses your face, a mirror, a Kinect and machine learning to show you pictures of people who you may look like -- or not. Sometimes you won't get a person who resembles you in any way, but that's the entire point of Untrained Eyes. When Kaino and Williams set out to make this project, it was always with the intention to shed light on the inherent flaws of artificial intelligence algorithms, particularly those utilized in image search databases.

In July 2015, Google's public-relations machine was in full-on crisis mode. Earlier that year, the search giant announced Photos, an AI-driven app that used machine-learning to automatically tag and organize your pictures based on the people, places and things depicted in them. It was an exciting step forward, but Photos wasn't perfect. While the app was capable of recognizing some faces, it mistook others. It would have been easy to pass this off as a routine software bug if it weren't for the nature of the failure.