Reviews are an important part of modern life. People often consult reviews before buying things, visiting a restaurant or booking a hotel. There are even reviews on the best seats to choose on planes. When reviews are honestly given, they can be very useful to potential buyers, but what if they aren’t honestly give? What if they are glowing reviews written by friends of the restaurant owners, or scathing reviews written by friends of the competition? What if the service received was fine, but the reviewer simply didn’t like the race or gender of the person delivering it? Many reviews fall into these categories, but of course we can’t be sure how many, because when someone writes a review, we don’t know whether they were being honest or not, or whether they are biased or not. Adding a category of automated reviews would add credibility provided the technology is independent of the establishment concerned.
Face recognition software is now so good that it can read lips better than human lip reading experts. It can be used to detect emotions too, distinguishing smiles or frowns, and whether someone is nervous, stressed or relaxed. Voice recognition can discern not only words but changes in pitch and volume that might indicate their emotional context. Wearable devices can also detect emotions such as stress.
Given this wealth of technology capability, cameras and microphones in a restaurant could help verify human reviews and provide machine reviews. Using the checking in process it can identify members of a group that might later submit a review, and thus compare their review with video and audio records of the visit to determine whether it seems reasonably true. This could be done by machine using analysis of gestures, chat and facial expressions. If the person giving a poor review looked unhappy with the taste of the food while they were eating it, then it is credible. If their facial expression were of sheer pleasure and the review said it tasted awful, then that review could be marked as not credible, and furthermore, other reviews by that person could be called into question too. In fact, guests would in effect be given automated reviews of their credibility. Over time, a trust rating would accrue, that could be used to group other reviews by credibility rating.
Totally automated reviews could also be produced, by analyzing facial expressions, conversations and gestures across a whole restaurant full of people. These machine reviews would be processed in the cloud by trusted review companies and could give star ratings for restaurants. They could even take into account what dishes people were eating to give ratings for each dish, as well as more general ratings for entire chains.
Service could also be automatically assessed to some degree too. How long were the people there before they were greeted/served/asked for orders/food delivered. The conversation could even be automatically transcribed in many cases, so comments about rudeness or mistakes could be verified.
Obviously there are many circumstances where this would not work, but there are many where it could, so AI might well become an important player in the reviews business. At a time when restaurants are closing due to malicious bad reviews, or ripping people off in spite of poor quality thanks to dishonest positive reviews, then this might help a lot. A future where people are forced to be more honest in their reviews because they know that AI review checking could damage their reputation if they are found to have been dishonest might cause some people to avoid reviewing altogether, but it could improve the reliability of the reviews that still do happen.
Still not perfect, but it could be a lot better than today, where you rarely know how much a review can be trusted.