How AI Transforms Design Practices

While people who work in design and design-related roles such as user research and human-computer interaction (HCI) may be aware of Artificial Intelligence(AI), the speed that this technology is being adopted calls for some consideration. About 20% of organizations are considered AI pioneers. Having achieved successes in initial AI experiments, these firms are now rapidly infusing all areas in their enterprise with AI. What does this mean for design practice?

You may have heard that AI automates repetitive, mundane and often time-consuming tasks but it may be harder to see what that means in the context of creative design roles. For people who know a bit more about AI and Machine Learning (a specific form of AI) they may believe that AI could commoditize the practice of design and lead to products that lack creative processes and outcomes. To understand the impacts of AI on design practice, first consider what AI is.  

What exactly is AI?

When I give talks about AI and User Experience(UX) I explain that most of AI boils down to one word, prediction. Prediction means using machines to process data and create new information. With this one concept, it’s possible to frame all other applications of AI. Various forms of a prediction can be; 

  • Classification – predict how to associate data with categories defined by a human
  • Clustering – predict how to group data into categories defined by the machine
  • Recommendations – predict a choice for a user based on assumed or actual preferences 
  • Generative design – using existing content to predict or generate variations of content 

You may have already interacted with a design system such as Wix, an example of artificial design intelligence (ADI) that automates generation of variant webpages. There are numerous examples of AI assistant tools applied to ideation and creation in design. 

What are the benefits of AI? 

AI equips design teams with tools to take the concept of user-centered design, to the most granular level, design for individuals versus designs for usually poorly-segmented groups of users. One example is how Netflix combines user behavior modeling with recommendations to offer each viewer a personalized viewing experience. 

What does this mean for Designers?

Designers need to learn about AI/ML, what it can do and how to strategically apply it to improve user experiences or to improve their design practice. While designers may not need to become data scientists (in the same ways that they don’t need to be coders), they can work to understand the applications, risks and nuances of AI as the first step to benefiting from its power. 

Process Automation: AI enables automation of problem solving tasks such as collecting and analyzing large amounts of data to discover invisible patterns without limitations of volume and speed. With this knowledge, designers can then pivot to focus on higher value tasks.  

Problem Identification: With AI taking on some repetitive tasks, this enables designers to focus more on “sensemaking” — understanding what problems need to be solved. 

Problem Framing: With AI, designers can shift to focus more on problem framing, clarifying the underlying questions and assumptions that the solution needs to respond to. They can also learn to architect frameworks to explore design alternatives and leverage machines to run through alternatives, freeing their time from some of the more mundane aspects of design. 

Human Element: AI is weak in areas that require knowledge of culture, emotion, context and identity, and ethics, to name a few. This is where designers’ impact would be well spent. Designers can have some time freed up from repetitive tasks that pave that way for more time to explore how the problem definition and solution variants could be optimized against these needs. 

Risk Mitigation: AI is a tool that opens the door for designers to create new experiences and to achieve process efficiencies. However, it also raises new risks around security, privacy, fairness and equity. A designer would lean heavily into the work of subject-matter experts in these areas to optimize solutions that consider the full impact of AI on a user’s experience. 

Is there anything to fear with the emergence of AI in design practice and allied roles? According to a report by Oxford University and Deloitte, 800,000 jobs were lost in the UK due to automation between 2001–2015. But according to the same report, 3.5 million new jobs were created. AI is already having an impact on the practice of design, and will likely lead to transformational shifts in how design work is done. 

More information: 

Basu, Ritupriya. (2019, Dec. 6) Algorithms Are a Designer’s New BFF – Here’s Proof. Adobe XD Ideas.

Irfan, Mirza. Artificial Intelligence and the Future of Web Design. Usability Geek.

Basu, Ritupriya. (2019, Dec. 6) Algorithms Are a Designer’s New BFF – Here’s Proof. Adobe XD Ideas.

Lant, Karla. (2018) Art by computers: how artificial intelligence will shape the future of design. 99 Designs.

Deep, Akash. (2019, May 15) Real-World Applications of AI in Design. Hackernoon.

Insall, J.. Borrtharkur, A. From Brawn to Brains: The Impact of Technology on Jobs in the UK. Deloitte Insight.

Verganti, R., Vendraminelli, L., Iansiti, M. Working Paper: Design in the Age of AI. 

Białek, Bartek. (2019, March 26) Artificial Intelligence Disrupts UX and Product Design Like No Other Industry.

Guszcza, Jim. (2018, January 22) AI Needs Human-Centered Design. Wired Magazine.

Koponen, Jarno M. (2019, February 9) UI + AI: Combine user experience design with machine learning to build smarter products. Venture Beat.

Clark, Josh. (2019, Nov 5) AI is Your New Design Material. Presentation from Amuse UX Conference.

Published by Jennifer Otitigbe