As companies talk seriously about the workplace role of adaptive intelligence, machine learning, artificial intelligence, and natural language understanding, it’s time to talk about the fundamental shift in user experience (UX) these emerging technologies could also bring about.
Our research on emerging technologies reveals three main benefits to developing such a smart UX:
- Automate tasks to increase efficiency.
- Advise users on the best course of action to meet their objectives.
- Discover relevant, actionable information while also inviting exploration.
The goal is to deliver more personalized and contextual user experiences based on where users are and what they’re doing.
Two concepts are particularly important in building a smart UX:
- How we leverage technology and design to anticipate what a user needs.
- The “thinness” of an experience—how much users have to go through before they get value out of their experience.
One or Two Steps Ahead
Any form of intelligence, whether machine learning or AI, is there to anticipate your needs. This extends beyond computers—a butler, for example, is there to do what you ask and anticipate your needs.
From a UX perspective, we can look at any transaction. An online form may have 40 items—that’s 40 things for the user to understand or learn about and actually do.
With the addition of machine learning, information is gathered amid the structure of several business processes, and that data is stored in the system. So now when the user opens that form, what if 35 of those 40 fields are already filled in or contain suggestions? The user has to learn only five things now.
Machine learning, AI, and other emerging technologies will help us take UX design to the next level. The smart UX we’re creating is all about anticipating the intent or goal that a person has, then guiding him/her to that goal with minimal learning required.
Another core concept of UX is the thinness of experience—how much someone has to go through to get value out of a product. When you want to buy something, how much effort are you willing to expend? Do you want to drive to the store, park, go in, shop, stand in line to check out, and then drive home? Is this something you can do by logging onto a shopping site and pushing a button?
Chatbots, a way of interacting with enterprise systems via text-based messages, are one way to make simple transactions even easier and more accessible. Chatbots don’t force you to open your laptop and log on to complete a task, and they’re already on your mobile device. On the back end, there’s a machine learning system that interprets and responds to your text-based messages.
For example, a system-generated notification might appear in my text stream, say from the city of San Francisco, alerting me that I need to renew my driver’s license. It asks whether I want to make an appointment, and I respond yes. The system can assume that a previous appointment is my preference and look for a similar day and time to suggest. Again, I just respond yes, or change the time and date.
In this scenario, my interaction with an enterprise system is as easy as texting. But I can see clearly where the system is getting its information from, and the design of the smart UX turns it into a narrative, asking me questions in a leading way to automate the task for me.
Chatbots Oracle has built are “forgiving,” in that they let you adjust the business process so that the questions become more like advice. There’s a convenient gateway to discovery if the task becomes more complicated.
A smart UX with a forgiving nature is a very human trait. It’s also exactly how we use search, which gets us to a page with a series of links. Then we further refine our task.
At its most basic level, we are using different tools or emerging technologies to sort information and determine what to do with it. The intelligence piece, the part that makes it a smart UX, exists within the context of the task.
In the end, the goal is the same as for any user experience: to help you be more efficient.