I see my domain expertise as expertise in designing with emerging technologies and thinking through the unintended consequences of them.
My first encounter with generative artificial intelligence (AI) and recommender systems was during the project, Recommending Sports. It laid the groundwork for me to understand how AI systems work and how they can be applied. Due to this project, I was able to formulate the case for me to go to Technische Universität Wien (TU Wien) to learn more about recommender systems to understand Surveillance Capitalism.
In the last few semesters of my master’s education, I ventured out to try to understand the cultural, societal, and economic influences of Surveillance Capitalism. In the project, How the system crumbles, I tried to make sense of the influences by creating a design research program. In this program, I performed interviews, interventions, and crafting methods to research the topic. Through interventions, I tried to give them ways to talk about these systems.
I used my time at TUW to develop domain expertise in how algorithms are created and about recommender systems work. During the BIP project and the project Humanizing AI systems, my understanding of user needs in a complex society got developed, which helped me to understand the entanglements of Surveillance Capitalism and humans in my FMP.
Design and research expertise
During my Master programme, I learned new ways of approaching design and new methods.
Speculative futuring techniques were applied during the project, On the Move. The skills I learned in creating a future and immersing participants in it to understand their fears and desires in it, helped me form the adjacent future during my Final Master project. More methods, like the autoethnographic approach that was utilized during the project, Humanizing AI schedulers.
The user experience and user interaction design skills were developed during my work as a user experience researcher and during the project On the Move, where I took over the designs for the digital prototype. During the Final Master project, I implemented this knowledge by designing booklets, diaries, and design cards.
During my master education, I was able to work with diverse groups of people. During the project Thom and M1.1 project, I was able to work with people who did not know the ways of working at TU/e. I often took on the role of explaining theory and showing them design methods. These learnings helped me during my research project, M2.1. in which I collaborated with experts on a recommender system platform, and had to be able to talk about my study and the way students make it on a more abstract level. In my M2.2, I built further experience by explaining my project to experts from different fields, such as Audrey Desjardins, Daniel Buzzo, David Chatting and Niya Stoimenova. Companies like Bureau Moeilijke Dingen contributed as experts in workshops and interviews. As I attended the workshop, Data as a Material for Design: Alternative Narratives, Divergent Pathways, and Future Directions, during the CHI conference 2023, I was able to talk about my Final Master project topic with more experts and collaborate on an exploration of how we see data in our everyday lives as professionals.
Throughout the last two years, I gained knowledge, skills, and attitudes in different expertise areas through courses and projects. My chosen ones are: Creativity and Aesthetics & Technology and Realisation.
In this section, I will explain what each expertise area means to me, and then I will move on to link them to my identity and vision, development, and my Final Master project.
Creativity and Aesthetics
I see Creativity as a way of looking at the world and being able to see problems from different perspectives as key points for me as a designer. Doing this by applying design methods can guide a designer in their journey. To understand complex subjects, creativity can be used as a compass, employing strategies such as lo-fi prototyping, brainstorming, and workshops. These technologies allow me to go into things that would otherwise appear incomprehensible through basic discussion. Aesthetics can be many things; for me, it is the way an artefact communicates with a person. An artefact for me is aesthetically pleasing when the user can have a conversation about it, or even with it. This derives from my professional identity as a design researcher, in which I create artefacts to perform research.
Technology and Realization
Technology and Realisation represents a bridge between design and technology, transforming abstract ideas into tangible realities. It involves navigating complex issues, using technology to inspire meaningful dialogue. The essence of Technology and Realisation is making theoretical data practical. It uses technologies to shape data into meaningful forms for individuals, necessitating an understanding of technical architectures, system design, and continuous experimentation.
I view the realm of Technology and Realisation as an opportunity to use technology as a means of translating design ideas into reality. This enables designers to delve into complex systems such as Surveillance Capitalism, using materials and technology to inspire thoughtful dialogues around this phenomenon.
User and Society
User and Society prioritizes understanding and addressing individual needs and values within their broader societal contexts. This focus area involves the application of qualitative research methods to identify and understand user concerns, placing them within their respective social, political, and cultural spheres.
A central tenet is the active engagement of users through empathetic, respectful methodologies such as direct interviews.
It necessitates a conscious understanding of the delicate balance between humans and technology, with an emphasis on acknowledging and considering the societal, political, and cultural implications of design technologies. Therefore, “User and Society” encapsulates an approach to design that is respectful, sensitive, and actively involves users as key stakeholders, aiming to challenge societal and cultural trends within larger historical contexts.
Math, Data and Computing
Math, Data, and Computing as an area of expertise involves delving into data analytics to decode and comprehend research data. It necessitates an understanding of complex computing systems, such as recommender systems, as well as the ability to read, comprehend, and implement related code.
This area of expertise also includes studying machine learning literature. It is not just about coding, but also about comprehending the complex architecture that underpins technologies such as machine learning and recommender systems.
In addition, “Math, Data, and Computing” necessitates effective communication about AI methods, potential ethical implications, and the opportunities and challenges they bring.
Business and Entrepreneurship
Business and Entrepreneurship as an area of expertise within design involves creating significant product-service systems that add value to individuals and the broader economy. Furthermore, “Business and Entrepreneurship” necessitates a thorough understanding of organisational structures as well as the ability to manage processes involving multiple stakeholders. I see this area of expertise as a means of leading and taking the risk of creating something new. For me, the most important aspect is one’s attitude.
Design and Research process
For me, a Design and Research process means standing in front of a problem and creating designs to research it or applying methodologies to find new ways of looking at the issue. These tasks would generate knowledge for designers or researchers. This means constantly creating and testing and iterating on the project at hand.
Expertise areas integrated
As I started with these two expertise areas, I have to say that the other expertise areas merged into the project as well. As a designer, I acknowledge that I am not just an expert of two expertise areas but I will always have to have attitude, knowledge and skills from other expertise areas as well.
A lack of knowledge
Determining the hidden intentions of corporations, particularly those operating under the model of Surveillance Capitalism, is as difficult as finding a needle in a haystack. It’s a daunting task, as we are required to comprehend and anticipate the unknown (i.e. design and research process, technology and realization).
This challenge is similar to the one we face in the field of design. Consider the impact of the Bauhaus movement. Its guidelines were widely adopted, and many of the era’s designs now seem short-sighted. They used materials and design principles that, in hindsight, should have been different.
But how can we create designs that are future proof without having to first learn the consequences that might appear (i.e. creativity and aesthetics)? When it comes to data and AI, we do not have the luxury to create devices and see what will happen (i.e. technology and realization, math, data and computing). We have to know what we do not know yet to design future proof designs. This can be done by applying speculative futuring methods and through the involvement of domain experts, like I did in my FMP.
A user experience nowadays is flawless and does not give away too much of the inner workings of systems. Creating disruption in the way this user experience is built up, could help future designers to create transparency in the data gathering of systems and create more awareness for data privacy (i.e. user and society).
Furthermore, a central tenet is the active engagement of users through empathetic, respectful methodologies such as direct interviews (i.e. user). This approach is exemplified in projects like studies of Surveillance Capitalism, where interactions with interactive prototypes are observed within users’ personal spaces, revealing insights about technology integration into daily life (i.e. design and research process).
As technologies become more ubiquitous in our environment, we have to find ways to unearth them. There is a trend towards hiding those technologies, but I believe that we have to make the work they are performing and the data that they are gathering obvious (i.e. business). To go against a trend, designers might need new ways of working to create these technologies. (e.g. design process) Thinking about the environmental implications of these technologies, the server rooms and geographical implications of these systems, could be legislated to create an incentive for companies to change (i.e. computing).