Traditionally, UX is a design process where products are designed in such a way that they are easy to use and engaging to interact with. The experiences that people have while interacting with these products holds almost as much value as the product itself. With this in mind, UX designed experiences had been aimed primarily at presentation and precise navigation of information.

Up until now, a website or piece of software was considered “dynamic” if there were text and images on the screen which pulled from a database rather than being hard-coded. With technology rapidly expanding the horizons of what can be accomplished and users expecting more from their product experiences, designers are going to be asked to do more than just present compelling information. They will instead need to create dynamic experiences to go along with that information.

What does this mean, exactly? Currently, experiences are designed in highly-conditional states and optimized to be useful and flow well. Algorithms are employed to measure continually the context of what a specific user is doing and store that information for future reference. The goal of this type of design is to use data predictively and make an experience progressively better each time someone uses it. In no uncertain terms, the system should learn a little from each experience it generates and then continuously improve.

With new technologies pushing the envelope of design, some of the approaches being taken now and systems being created are becoming incredibly sophisticated and powerful. Take for example systems that model the most important of personal tools for interaction: Speech. Years ago, we struggled to make products such as mobile phones understand the commands we would give them to place a simple call. Today, we can touch a button in our automobile and speak to a system that not only understands our speech and that of anyone driving, but it can follow commands. By understanding and following these commands, the system can change features on the vehicle, launch apps, or call and text people by speaking their name without ever having to touch more than a single button at any given time.

Because of the far-reaching implications of such technologies, UX stands at the crossroads of several disciplines. These disciplines include technology, business, and human behavior. Each of these disciplines, along with dozens of others, must be understood to create the types of designs that will be required in the years to come. Part of understanding how these needs will be fulfilled will rely on algorithms as design tools. These algorithms will be used to measure inputs and translate that data to make user experiences more engaging, fun, beneficial and useful, no matter which application or use they are designed for, from the simplest task or goal to the most complex one.

Most importantly, the data must be interpreted entirely to discover what it means and how it can be applied to each users experience. This is the core of data-driven design. The traditional model of data-driven design is determined by the number of clicks, interactions or conversions. This model is elementary at best and doesn’t go nearly deep enough to mine the type of feedback data that is required to optimize the design. This is a generalized approach that looks at an entire experience from 50,000 feet. It judges decisions based on the whole experience.

On the other side of the coin are systems that measure based on a large number of small experiences that are then collectively added together. This approach is not optimal either, and can lead to misinformed data or conclusions. What is needed is a “data informed” design approach.

“Data-informed” design is far better informed and calculated. This method of design uses data in the most useful way, by combining design that is intuitive and educated with machine learning. The proper combination of the two creates a symbiotic relationship that works well when created and nurtured with the right balance.

Today, this type of machine learning and AI can be evidenced in products like Siri, Cortana, Google Now and Echo. This is just the beginning of a line of future products that all employ the AI experience to create incredibly valuable products with dynamic learning experiences. Even more exciting products and applications are on their way in the years to come.

One of several UX design disciplines in the digital screen-based consumer product space is interaction design. Interaction design is focused on users and their interaction with a product — users take an action, and the system does something in response to that action. This interaction may be with a “bot,” a virtual entity that listens via text or speech, which in turn responds to that input. The more the user interacts with the bot, the more refined the future interactions become.

These bots live in screen-based interfaces that are all composed of the same parts. They must include a start-up process, initiate an interaction with the AI, recognize that interaction, allow for back and forth discussion to define a user’s goal, and then provide a way to acknowledge the final output which in turn may lead to other activities.

In some cases, the AI may search for ways to automatically insert itself into the user interface when needed, and in the best case scenario, do so in a seamless fashion. For example, when you wake up in the morning and look at your iPhone to check your texts and messages from the previous evening, your home screen may tell you how long the drive to work will be that day, whether there is any traffic, and how the weather might affect your drive. All of this is done without your even having to ask, and is useful information that is relevant.

The tenets of interaction design will undoubtedly influence the future of UX design. This leaves UX designers with the challenge of creating interfaces where these interactions are largely unscripted. Another consideration for future and current UX designers will be the utilization of bot-logic and functionality. Typical interaction design has included actions such as a limited algorithmic response that helps the user to refine information to reach the content desired. Bot-logic and functionality take this to a new, more complex level, allowing for designers to anticipate and handle even more sophisticated kinds of responses.

Like the engineers, inventors and software programmers who came before them, the greatest source of innovation will come from UX designers who dedicate themselves to continuously experimenting and adapting their approaches. This discipline has traditionally appealed to those who enjoy challenges and new experiences, which lends itself well to advancing the technologies and products they design for. The best advice for those who are currently employed in the UX world, or for those who want to enter this career path, is to constantly continue to learn, adapt, and think of new ways to combine and create the rapidly changing technologies emerging today to create the amazing products and user experiences of tomorrow.

originally posted here: