Will machine learning and AI change responsive web design?

Web developers have streamlined and added features in web design to customize websites for users, but AI and machine learning will further the user experience in web design.

artificial intelligence / machine learning

We see it every day – robots taking on tasks that we didn’t think possible just a few short years ago. This particular topic or task is employing AI to create responsive webpages that change and update automatically with new content. How do we keep up with the user demand for personalization at each level, and their insatiable quest for instant gratification? Sure, web developers have streamlined their content management systems and added features to automatically capture user input and habits, then apply it for a customized but limited user experience. This where AI and machine learning come into play.

One such example is a startup that leverages AI to build websites to make form dynamically adapt to content. Imagine machines making pertinent design decisions based on artificial intelligence, where it intelligently analyzes user content to find optimal fonts, graphics, and layouts that best compliment their website and design tastes. This is where machines are truly making intelligent decisions.

Delegate everything to AI?

Let’s talk about the progression of web design and the many things that have been slowly automated with the advent of machine learning and AI. Remember the time-intensive task of rendering graphics or photos? Over the years, software developers and companies like Adobe have improved features and added batch processing for large numbers of pictures, as an example. Now, designers are turning over these tasks like processing or rendering responsive images, or dynamically creating content and URLs based on data collected from the end user. Other advanced tasks that leverage AI is where the machine can categorize and tag photos using image recognition.

Simply put, using AI accomplishes two basic things: it allows mundane and repeatable tasks to be handled quickly and accurately by the machine, and it frees up valuable developer time to focus on more strategic tasks or projects – thereby making the development process leaner and more effective. Yet another example, but on the customer side of the coin, several companies have launched DIY websites in the last few years. These sites apply machine learning to help eliminate technical barriers for non-technical folks who need to communicate amongst a myriad of platforms or devices without the troubles of knowing how to do manage all the technical nuances associated with them.

AI is quickly becoming a vital aspect for the products and services that our customers come across on a regular basis. Eventually, everything including mobile devices, applications, and search engines will be completely powered by AI. Over time, machines will begin to develop dynamic responses or applications to adapt to customer requests in the blink of an eye.

To fully utilize the capability of machine learning, one must understand the task as a computer might analyze or see it. This is the foundational concept of true machine learning. When we need the machine to finish a task, we need to ensure it has the complete directions to learn the specific task we are asking it to perform. As an example, if we wanted the machine to paint a house, you would have to provide specific information about paint preparation, types of materials needed for the various steps, including color of paint, types of brushes, etc. If the data or instructions are complete, the machine will learn to perform other related painting tasks on its own over time.

Are we there yet?

Not quite, but machine learning is very promising. It’s important that we embrace machine learning technology so that we continually improve the customer experience. What can we do as designers to contribute to the progression of machine learning and web design? Most importantly, listen to our customers. Then, continue to train our machines to learn web usage patterns, and new, but moderately harder tasks. We truly possess the power to put the machines to work so we can produce a better product more efficiently and smarter for our customers. As designers, we have a responsibility to provide the best user experience. Keep in mind, over time the consumer demand will only become greater. Customers will continually expect a seamless experience, regardless of what they are trying to do, or what platform they are on. So, embrace the machines and enable the environment such that they must learn the task by themselves. Let them design with deep learning to produce automated and responsive output better and faster than we could have ever done.

This article is published as part of the IDG Contributor Network. Want to Join?

NEW! Download the Winter 2018 digital edition of CIO magazine