By Aryan Nainy-NejadHave you ever looked at something and wondered how it was made, what thought was put into the design of it, and why the final result is the way that it is? Everything manmade around us probably passed through the scrutinizing stares of a designer at some point, which is the reason that most things around us work well. There are many principles in the field of design that can be used to help designers perform better, and I discussed some of these principles with Kosa Goucher-Lambert, Assistant Professor of Mechanical Engineering at the University of California, Berkeley. Goucher-Lambert started his undergraduate studies as a Physics major, but eventually found himself doing engineering-adjacent research, such as testing, and was captivated by the technical engineering questions asked in design. Following this, he shifted towards design in mechanical engineering but kept the focus on research. Now, he researches meta-design methodologies that can be used to make tools for designers to make the design process easier and more fruitful. As the field of design is very driven by success/failure, a lot of thought has been put into understanding why some designs succeed while others fail. For Goucher-Lambert, the variable that is responsible for these outcomes is empathy. As a designer, one is essentially creating something that they believe will be useful and desirable for somebody else, so the better that the designer can understand their user and target audience, the more suitable their solution will be. Similarly, designers that have a hard time empathizing with their users often find themselves falling short. One example of this that Goucher-Lambert experienced comes from a prior work experience of his when he worked in an audio device company. He was working on a digital microphone that would record sound and can play it back for the user, which was tested with musicians. Goucher-Lambert recalled that he was surprised at how little time the engineers spent looking at the recordings from the musicians perspective: the engineers looked at technical data such as frequency wavelength and decibels, but the musicians were more drawn to the subjective feel of the recordings, evaluating them in ways such as saying one recording feels “warmer” or “softer” than another. If the engineers were able to see the recordings from the perspective of the musicians a little better, the product would likely be more successful. Although empathy stands head and shoulders above the rest as a prominent factor in the viability of a design, three others that Goucher-Lambert noted as being necessary for designers to embody were creativity, the ability to work hard, and the technical background and skillset. One fascinating point is how several of these traits (but not all) can make up for each other if one is underdeveloped; for example, someone can lack the domain expertise, but can then develop their abilities in that competency through hard work. The other interesting thing to note is that all of these skills can be practiced to make a better designer; work experience naturally comes to mind when evaluating how technically sound someone is, but personal qualities like empathy and creativity can be exercised as well, if not for the difficulty in practicing them. This leads into a point of discussion for the future of the design world: the role of AI and machine learning in augmenting design processes. Goucher-Lambert’s lab works on building tools and methods for designers to use in their own practice; an example of this work manifested would be an algorithm that can take in data on design methodology, then be given a problem, and can crank out potential solutions. The role of computational methods in the realm of human-centered design is one of Goucher-Lambert’s greatest interests. This begs the question as to why humans are even needed to design things if the process can be automated. For one thing, some of the personal psychological qualities mentioned earlier, such as empathy, are difficult to replicate in automation. The middle ground that Goucher-Lambert sees as the eventual future is one where a human can approach a problem and crank out 50 solutions, then use their algorithm as support to get 50 more; we will never be fully without these machines, but can use them to bolster the effectivity of design processes. However, the fascinating opposite end of the spectrum on the topic of automation in design is the stance that designers don’t need methodologies and structured practices to achieve great designs, similar to how artists and painters don’t follow a formula to create beautiful paintings. Some people (not Goucher-Lambert) consider design processes and methodology to not be truly creative, since they are following set patterns in how they approach problems. These variables, such as the role of psychology and empathy, as well as machine learning and computational tools, force us to consider the fine line between humans and technology in the role of design, because of how integral technologies have become into our daily lives. Only the future of the design world holds the answer to this controversial fork in the road, although as a designer and engineer, I would probably forge my own third path that I think best tackles the problem at hand. Connect with Aryan.
Life in Tech: Human-Centered Design and Empathy was originally published in Berkeley Master of Engineering on Medium, where people are continuing the conversation by highlighting and responding to this story.