AI in UX
Master Thesis
“How might UX designers apply artificial intelligence into their practice in order to remain relevant in the future?”
The profession of user experience design has widely integrated the model of Design Thinking as a foundation to build design processes upon. The model is promoting a human-centered, low-tech approach to innovation and is involving many manual practices. This thesis investigates whether advances in artificial intelligence combined with increased digitalisation of society may pose a challenge to the paradigm of Design Thinking. The concept of computational design is explored as an alternative paradigm for future UX design. Computational design is fundamentally built around applying the power of intelligent computer algorithms, such as AI, to assist or automate design processes.
Death of the post-its?
Design Thinking often positions itself in opposition to technological innovation by being presented as the human-centered, practical and low-tech approach to innovation and complex problem- solving.
The framework is built around simple and manual methods and the design materiale is often physical in the form of pen and paper. The prototypes which are generated through such practises often start out as low-fidelity doodles made by hand. Approaching innovation in this manner puts a lot of pressure on the ability of the designer. They will need to initially master the ability to comprehend and work with complexities of contemporary digital services based on their intuition and artistic ability to express themselves visually by hand. Relying on such methods can be limiting.
Methodology
The subject was explored by interviewing UX professionals in relation to their view on the state of UX and how the profession might be changing in the future. The thesis placed extra emphasis on how UX designers could implement AI as a design material and what the potential benefits and challenges of doing so would be. Based on the findings of the interviews a synthesized list of key insights is presented in the form of guidelines for AI in UX.
“Artificial intelligence is the capability of a machine to imitate intelligent human behavior”
Artificial intelligence was estimated to be the technology that had the biggest impact on UX design during 2020. It won over big data, VR, and IOT.
(World Usability Congress, 2020)
Being a part of an industry that is constantly evolving, UX designers need to stay on top of breakthrough technologies to meet the design challenges of tomorrow. My research attempts to add perspectives to this field of inquiry.
Smart algoritms
Computational design describes an approach of enhancing design by applying the power of intelligent computer algorithms, such as AI, to assist or automate design processes and decisions.
New technological breakthroughs are enabling tools that are making computational design more intuitive. This is supported by visual programming instead of textual programming, where it is possible to develop programs by working with components graphically. This means that applying a computational design approach no longer requires high levels of programming skills
Adding computational design to a design process can radically change the way a designer constructs interfaces, products and services.
Generative Design
The use of generative design can help find solutions to complex problems where the designer needs to explore many different alternatives. Adopting generative design into the design framework can bring advantages like:
efficiency, cost reduction, optimization, accuracy and consistency
1. An AI algorithm will generate different versions of the design based on prioritization of multiple parameters and variables.
2. The designer can critically and iteratively explore and adjust these possible alternatives for inspiration or further development.
3. The model is built on a human-in-the-loop design approach where the designer guides the computer system and uses it to assist his or her work.
The guidelines:
Involve UX Designers in the AI design process
AI should be implemented as an assisting technology
Develop tech skills
Focus on efficiency
Ensure trust and transparency