Every week, the Castille Product team meet to discuss the ongoing development of a new Digital platform. The platform follows a user’s career journey from their first employment to their retirement. Naturally, a lot of focus on user experience (UX) led to a recurring question within the team: How can we use AI to support UX? We knew that a digital revolution was underway wherein constructing an online platform necessitates the use of AI technology.
Any Product or Design team will know that constructing a feasible UX is important to ensure smooth user journeys, engagement, and the return of these users to the product. Dialogue around AI typically begins a worrying narrative where robots will replace human involvement, but the relationship between AI and UX is more complex. Empathy—the ability to share and understand the feelings of another individual, or ‘knowing what it’s like to walk in someone else’s shoes’—is a unique human trait that computers have not yet grasped.
AI technology works on the premise that it simulates human intelligence, including emotional attributes. Empathy can be difficult to mimic for AI systems, as human emotions are often nuance. For example, humans are able to smile and appear happy even when feeling the complete opposite. Artificial Empathy is a popular area of research for this reason, in that researchers must consider the complexities of human emotions, including physical and behavioural manifestations of emotion, so that AI can learn to mimic it effectively.
With this in mind, it makes sense that AI and UX collaborate with one another, rather than have one replace the other. It is a more worthy perspective to interpret AI alongside other emerging technologies to allow design and product teams to create products in an expressive and intuitive way. In other words, the general concern where AI will replace jobs in Malta and beyond is not the reality—wherein truth, AI creates more jobs than it does replace, and one of these is to be able to work alongside designers.
How AI Collaborates with UX
AI can help construct robust design systems. Keeping products consistent with users by using AI to provide metrics on user behaviour, allows designers to interpret data on user interaction with products. In this way, components and functions of a product can be optimised to deliver better results to the user. A design system hosts a number of modules and elements that supports a company’s brand and keeping this consistent throughout the design process is imperative to releasing a good product.
Additionally, AI allows for generation of large quantities of data that can be analysed to drive better UX. Every time a user interacts with a design system, such as an application or website, data is captured. Whilst AI collects data, specialists are able to focus on analysing data in depth.
Perhaps one of the more popular reasons AI integrates in products is to provide a personalised user experience. AI processes user data and amends current models for future use. The selling point here is pretty conclusive, the more personalisation in user experience leads to more relevance for users, which leads to better conversion rates.
AI Improves UX with Testing
For designers, testing is an integral phase in developing a product. A number of metrics are available to understand user behaviour, such as user flow and the session time of users. If your website generates a lot of traffic, it would be easier to apply AI to gather that data for you. AI technology is able to collect data at a high-volume and rapid speed, and having this data is important for experimentation of new ideas and to run applicable, supportive tests.
Another popular testing method is A/B testing. An experimental research methodology, A/B tests work by showcasing two variants of a product. For example, designers might wonder whether the positioning of a call-to-action button is more functional at the top or end of a page. The A/B test would be created with two designs: One where the button is at the top, the other where the button is at the end of the page. A/B tests apply similar statistical approaches in that hypotheses drive the quality of a test.
AI works with A/B testing effectively because it eliminates bias. The use of data generated by AI will answer whether one design works better through statistical validation and reliability. Eventually, AI will develop to collect A/B test and heatmap data and analyse it quicker than humans can. With AI, UX teams can follow data-driven approaches more effectively.
As AI encompasses many technologies such as cloud software and big data, there are a number of ways to integrate AI to support UX. As a versatile technology, businesses can align their IT jobs, goals, and objectives to meet AI intuition.
AI and UX Work Well Together
No matter the means you choose to apply AI technology to your product, a common end goal between AI and UX is to create sustainable and deeper human connections. Technology offers possibilities that improve social listening, data analysis, among others, that tailors an effective and personal user journey with a product.
All in all, AI is great for testing and collecting behavioural data, but human intervention is still valuable in terms of UX. AI cannot handle complex design tasks as yet. UX is a priority, AI works as an additional insights tool.
The goal is to work with AI and technology to remove the need to conduct repetitive tasks, allowing designers and teams to focus their minds on strategy implementation. It is time to consider AI with an opportunist lens and not think against it.
Stay tuned to Castille Resources and learn how we incorporate AI to improve UX. Our new Digital platform launches end of this summer, and we look forward to meeting you.
This article is from the Castille Quarterly Newsletter | July 2021
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