When you think of artificial intelligence, the first thing you think of is not just renting out a room or an apartment. With the development of AI and a data-driven b2b data culture, Airbnb has transformed not only the hotel industry, but the industry’s relationship to AI. When you go on vacation, it doesn't matter where you live or what type of accommodation - you are most likely paying the price according to a supply and demand model.
Airbnb's "Price Guide" is an AI tool that "let Airbnb hosts know that they should price their home on a daily basis to make it more likely to be rented out" - Airbnb. With this technology, landlords can see a calendar showing the price they set for their home each day. Dates appear green if the landlord's price setting for the home is reasonable, and red if the price is too high. Using this information, hosts can use sliders to adjust prices and find the "sweet spot" - too low a price and a high chance of being rented, too high a low chance of letting, and possibly less overall profit.
The price guide AI algorithm is based on the vast amount of data that Airbnb collects and processes using open AI tools. There are many factors in the price guide model, including listing type, location, price, availability, and how far each date is from the current time. With this data, price guides can be automatically calculated and thought through for Airbnb users, making the experience more intuitive and transparent.
chatbot
Chatbots and other modern interfaces are getting more and more human every day (or at least that's how they feel) - due to the "Hollywood formula". The Hollywood formula was developed by Martin Stellinga to create meaningful stories. Think about how Disney characters build relationships with their users. They managed to form these large-scale relationships with diverse groups of people.
Each of Disney's characters has a unique personality that is presented in different mediums (apps, books, movies, etc.). Imagine if we could become experts at creating these personas on the interface and make similar connections with our users. If AI is the new UI, personalization may be the new UX.
Many websites/products offer customers the opportunity to chat with chatbots while browsing. *plot twist* While they look like real people, not every company has a real person on the other end. Usually you are talking to primitive AI. Interestingly, these chatbots need to be proficient in interpreting natural language—a difficult assumption to test.
Netflix
In a multi-device world, designers from all walks of life have to come up with tons of content/graphics to meet the demands of many media. This process takes time...a lot of time - oh, not so with Netlfix. Netflix and many other companies have handed this creative phase to artificial intelligence.
Examples of image focus using facial and full body features - Image: Netflix
Netflix discovered early on how visual effects influence user groups and their decisions to watch specific content. To capitalize on this finding, Netflix developed an artificial intelligence algorithm that grabs elements from pictures and applies stylized movie titles to create a Posters that correspond to user interests, language and location - cool, right? At the same time, the algorithm AB tests each design effect to optimize the content. When AI handles tasks like this, design teams can focus more on understanding the user's path and refining those rules.
AI isn’t just limited to big players, smaller companies like RealEyes are taking advantage of advances in technology.
It is not rationality that drives human decision-making, but emotion. We know that humans are motivated by their emotions, and emotions stimulate the brain 3,000 times faster than cognitive thinking. To help organizations measure human emotion objectively and accurately, RealEyes provides technology that reads human expressions through facial recognition algorithms.
RealEyes software records people's emotions through webcams and uses underlying artificial intelligence algorithms to understand them. This technique is very useful for things like usability testing - when testing a product, you may find that users are able to use and understand it (nice), but then get angry after seeing a certain information (not so good) ). If users' emotional responses were not measured, the product could have been released and upset customers. Other benefits of this technology include the automation of workflows by efficiently analyzing and encoding video/image data.
You've already read some case studies on how artificial intelligence can be used to improve user experience, but at the end I like to add a slightly different example. This example is about AI that may and will change the way we build products, but also has the potential to improve our relationship with products.
Pix2code
AI could be your new front-end developer — yes front-end developer, great, right? Pix2code is a smart form of generating code from screenshots of your interface. Tools like this can help bridge the gap between UI/UX designers and front-end developers, but they're not a replacement either.
Although the code thus generated is not perfect right now, it is important to understand the concept. As AI gets more training, it will only get smarter and more efficient. From this moment on, it will only get better.
Let's talk about data. Data = intelligence, no data = no intelligence