Yesterday at its I/O conference, Google announced new features to Google Lens, its image-recognition app for Android, and they’re all about improving the restaurant experience for customers.
Google Lens uses machine learning, computer vision, and a whole lot of data to interact with the world around you and answer your questions. For example, when Lens launched in 2017, it was touted as a way to instantly translate another language.
According to a blog post from Google published yesterday, the new features for Google Lens “provide more visual answers to visual questions.”
Like what’s popular on your restaurant menu right now. Within the Google Lens app, when a user snaps a photo of the menu and taps on an item, Lens automatically pulls up relevant information, like a photo item description, and reviews — data Google already has thanks to its Google Maps-Yelp integration.
Lens is basically automating something most of us have done at least once while out at a restaurant, which is see another table’s food arrive and, intrigued, ask them what it is. But asking Drew at the next table what she ordered only offers so much information. After all, Drew hasn’t tasted the food yet, and her preferences could be completely opposite of yours.
What Lens appears to be doing with this new feature is taking most of that guesswork out of the ordering process by not only matching a photo with its name and description, but also aggregating reviews, so a user can get a clearer sense of how the dish tastes. If nine people say the dish was super bland, those who prefer a little more kick to their meals might order something else.
It all sounds wonderfully convenient for us consumers. For example, it could be a valuable tool when you’re trying out a new type of cuisine and have no idea where to start.
What I wonder, though, is how this will affect menu planning for restaurants. On the one hand, it could provide valuable information for restaurants when it comes to figuring out what is and isn’t selling on the menu, so chefs and operators could better adjust their planning and inventory (potentially helping them avoid food waste and keep costs down).
But what this will do to the adventure of going out to eat? Part of the fun of the restaurant experience is the guesswork, which would be gone were we to rely too heavily on data-driven recommendations. This seems unlikely at higher-end restaurants and places designed for adventurous foodies, with robust appetites for the unknown. For all the places in between, though, too much knowledge might make the restaurant experience just a little too predictable.