Meet the community: Kwan Suppaiboonsuk

Member Highlight — Introducing the Newsletter Lead @AIxDesign

Boshra Javaheri
Published in
17 min readMar 2, 2021


Kwan and I met for a coffee and sat down in her living room to chat about her path towards the AIxDesign community. She talks about data and design from a technical point of view and how these two can collaborate more effectively. Stay tuned and learn more about Kwan.

Hey Kwan! Can you please introduce yourself and tell us what are you doing at the moment?

I’m currently working as a software developer at the Digital Society School in Amsterdam, where I get to not only build digital tools but also create and give workshops and courses related to design, tech, and data. I really enjoy helping people learn more about AI and data — how to properly design that in such a way that it’s good, not only for business but also for society at large. I’m also helping out with the AIxDesign community, where I lead the newsletter. We’re currently redesigning it to make it “smart.” This means streamlining the process of putting it together as much as possible through automation while still keeping the human aspect in the curation.

What’s your background, and how did it lead you to AIxDesign and this intersection?

My background is a bit of a mixed bag. I studied Technology, Liberal Arts, and Sciences, with a focus on Biomedical Engineering. And I did a minor in Bio-Robotics and ended up working in software for a bit. So, my background was pretty much two-thirds engineering, and the rest was social sciences, humanities, etc. I went into this path because I was always interested in technology, but I didn’t want to go full-on tech because I knew tech always has implications. And I was really glad with my study because it taught me to question many things when we design technology — the impact of our work and vice versa, like how people and their behaviors affect our designs.

And how I got here, I came across one of Nadia’s work, and I was really impressed with it, so I sent her a message along the lines of: “I love your work, would love to chat and hear about your process and how you got started with it.” Then I saw her post saying she wants to start the AIxDesign community and if there are people interested in helping out. At the time, I was working in the AI domain. I was developing an object recognition system for automating the process in a factory environment, where a lot of the process was being done by hand; in other words, improve the process so we can have a machine come in and help people. I was doing research and prototyping with computer vision to test how viable it is to have a system integrated with collaborative robots. Along the process of working with AI and designing it, I started learning more about the design thinking process. So when I saw Nadia’s post, I was like, oh, this is pretty cool, it’s a collaboration, and there’s so much to explore in this field. We had a call sometime in February [2020], and now I’m here.

Why are you drawn to AIxDesign? Why do you care about it?

Community-wise, I think it’s a super great environment; it’s really blended. Everyone’s always doing something different. It’s in AI and design, which is, of course, already pretty cool. It’s really new and refreshing stuff. I enjoy how there are so many people from different backgrounds with different skillsets working on cool projects. I think it’s a cool place to see ideas happen. Also, you really start seeing what happens when you’re collaborating from different disciplines.

On why I care about it, I would say, because it’s such a new topic (or rather, a new intersection) where there’s still so much to be explored and so many questions to ask. Also, there’s a huge hype in AI; however, not everyone is applying it in a responsible way, so I feel like here we have the opportunity to come up with principles and new frameworks that could be really good standards for the industry.

For me personally, I’m coming from a mix of engineering slash business background. I want to help people better understand AI so that they can communicate better. I’ve been in situations where there’s like a divide between the engineering team, the business, and the designers, and I believe that could work a lot better if there is a common ground or common terms that people could use.

Why do you feel AIxDesign is important?

I think we need more multidisciplinary approaches to solving problems in the future, or even today. And it requires a hand-in-hand collaboration between all these different fields. Among all the problems we have and talk about, most of them can be solved by people communicating and working together. When you’re working with people from different perspectives, you will start to notice vital questions popping up. So that’s why I think it’s important to have a space like the AIxDesign community, where people find common ground round and common terms for communication.

AI/machines are just are stupid and the intelligence pretty much comes from the designer. So it’s just a set of instructions that we, as humans, put in.

What’s the one thing designers should understand/know about AI?

I can say two things. First of all, you see some designers who are slightly afraid because they’re unsure of what AI is and how to use it. Although I feel like that’s gone a lot better, I would say what they should know is that there’s nothing to be afraid of because machines are stupid. And it’s pretty much just thinking about input and output. Mainly, what you want as output and then looking at what you put into the input as like a quality. You want a quality input to get a quality output. So, there’s nothing complex about it. AI/machines are just stupid, and the intelligence pretty much comes from the designer. So it’s just a set of instructions that we, as humans, put in.

Diagram of input, output for designers

The second thing I’ve noticed in designers is that they can be really abstract. They’re working on a more abstract level, and they’re working with this idea they have, as this vision. But then, on an engineering level, things are much more practical, like how we want the details of what data is coming from and what type of data it is. One thing that I think designers should know is that designs come from a source of data. Any idea or functionality they want to implement, there’s gotta be a source of data and a form of data for it. So I think going back to that basics is necessary. For example, when I’m helping friends who are designers learn how to program, I noticed they think in a complex/round manner, an entanglement of things, but once you go to programming, you’re just going step by step. So what could really help designers — maybe this is in terms of communications (with engineers) — is to look at their idea, present their idea, but also break it down.

Here’s an analogy I have in my head. I don’t know if it makes sense, but I’m just gonna say it. As designers, you connect the dots. And the thing is, if you’re connecting the dots, the dots have to come from somewhere, right? I think, to help with communications, one thing is to look at the meta-level of what are the dots that have been connected, where they come from. Then when you communicate that, I think it helps us as engineers, better help you figure out what is the proper path to connect those dots.

What’s the one thing AI/ML engineers should understand/know about design?

I think understanding the design process helps a lot — the design process of a designer. Of course, there’s a standard design thinking process, but most designers have their own, where they put their own flavor to it. So engineers better understand that for the designers they’re working with.

And I think really great designers are able to pick out the true needs of the clients. Just beyond what they think they need or what they think they want. And when you have this, it is also just trusting that the design has been done in a well-researched way. And, yeah, it’s not always functionalities that you think would be nice. Sometimes design research surprises you.

Different ideas of what customers want and how different careers see it.

What’s something you’ve learned recently that you think would be valuable for anyone working at the intersection of AI x Design?

Here’s something I’ve been thinking about recently, which is more like a challenge for people exploring AI x Design in general: to question things and push the creative boundaries of what can be done. We’re thinking a lot about how to design AI. But then a question that I’ve been thinking a lot about lately is, how can we also use AI as a byproduct. So not designing the AI itself, not the system itself, but taking an algorithm from a system and then putting it into another system and then just seeing what are the different ways we can play around with that. So my challenge is to push the creativity cause I feel like there can be much more creativity to be injected into this intersection. Together we should be able to come up with new novel ways in which we use AI as a tool, right? Beyond guidelines and design practices…

Back to what I’ve learned recently, not in terms of topic, really, but more of a realization. I’ve learned recently that it’s difficult to find research and materials in this intersection, especially when you have a particular question. I had this idea, and I was googling it, and I can’t find anything on it. That’s the nice thing about working in this field, right? Seeing like, ‘Oh, there’s nothing here.’ There’s space to explore and room for new content. So, definitely, one thing I’ve learned recently is that there’s still a lot of gaps in this field. Lots of opportunities for people to explore and share thoughts, ideas, and learnings.

How can you incorporate ethics into the design process?

I think it already starts at the beginning, critically question. When you have an idea, critically question it. After brainstorming ideas, critically examine, explore, and question them. Walkthrough if you apply this idea, who does it affect and how. I’m a bit of a systems thinker here. And also, I think it’s nice to talk to different people. Everyone comes from different backgrounds, and if you ask people, you will get a better understanding of what they think of it, how it will affect them, not only people around you but also go and talk to people you don’t usually see as well.

And I think what we can do better is to incorporate checkpoints throughout the design process where we ask: “Hey, is what we’re designing still heading in a way that will be good for society as a whole?” You’re always heading in some direction when you’re designing something, and it’s so easy to be like, “Oh, wait, let’s add this functionality because it would be nice for a certain group of people.” But then, slowly, after some time, you start adding something, and it starts deviating, so I believe adding more checkpoints will definitely help us through the process.

Going on another line of thought, sometimes there’s a discrepancy between the design process and the whole thing with data — collecting data and data quality. I feel like that is currently not involved as much in the design process. The ethics question already starts there with all the data. The whole data and data engineering process is often left to engineers. The specifics of data, data collection, data storage, and data usage are often brushed off in the non-technical design process, left to be thought of by engineers and maybe researchers. This is why we need more multidisciplinary teams that work well together and are not just three different islands. Many questions relating to ethics often lie between these roles, and because the roles are so separate, not one person feels the responsibility to take the lead on asking those questions.

Who do you follow for inspiring content around AI x Design?

I follow a lot of people, mostly creative AI artists. That’s also one reason why I’m drawn to this area because I think there’s all this cool new media art happening. People are pushing the boundaries of creativity and using AI as a tool.

There’s Ouchhh Studio. I really like Sofia Crespo and her work with bio-inspired AI art. Aside from art, Autodesk has a lot of cool, practical generative design use cases. For the technical stuff, I love Andrew Ng’s newsletter. I can always find amazing stuff and the latest trends of AI there.

What about your favorite day-to-day AI feature, what is it?

Google Maps. I don’t know how I would navigate without that. Also, living abroad, Google Translate is super handy, and I don’t know how I would have survived without it.

What’s your biggest/main fear about AI?

AI being used as a surveillance technology. Being designed and used in a way that represses our humanity. AI being used as a repression tool and repressing individuals from growing as a person. Repressing freedom of thought and freedom of speech. That’s my biggest fear; AI being used as a tool for controlling and limiting people.

What do you wish you knew about AI when you got started in this field?

Funny story, I had an AI class in my study, and I didn’t like it so much. It was on the different learning algorithms, which is cool, but in practice, I found the fine-tuning process (in order to get the best model) to be a bit overwhelming. I didn’t find it interesting because I thought it was a fussy process to make small adjustments. So I had a different mindset at the time because of that experience.

When I first started learning what AI is, I wish I understood that it represents how we see the world. If I had that mindset, I would have found it much more interesting and also much more connected to it. You’re practically modeling things; you’re modeling the state of the world so that you can predict it.

I wish I’d realized that AI, as a field, is not a super-specific and hard drawn line. There’s a lot of ways that you can connect to it. The field is evolving, and I think maybe that’s also why I enjoy reading and learning about AI now.

What’s your dream company to work for?

I used to have a couple of dream companies, but now I don’t know if I want to say “to work for” I would like to work with. My mindset has changed a lot from working as an employee to finding a place where I feel autonomous and don’t feel set into one thing.

I’d love to work with Google, especially their Creative Lab.

When I was younger, I played many sports and competed at a pretty high level, so I’ve always admired companies like Nike, Adidas, and Under Armour. Also, with a background in biomedical engineering, I’m super interested in health and movement data. Doing something with that would be fun, not necessarily with these companies.

New York Times, I love all their data visualization journalism. As well as The Pudding.

And actually, I would love to work with Pixar. In animation, there’s a lot of deep learning happening nowadays. Also, I would love to get back into working with motion capture technology, which I worked with during my bachelor thesis.

Also, Team Labs! They’re a Japanese studio doing interaction design, and they do exhibitions with a lot of interactive installations.

Lots of companies mentioned here. I don’t know what kind of work this would be. That’s something for the future. I just know they’re doing cool stuff, and any projects with them will probably be amazing. I have a lot of things I’m interested in, that’s why my background is also a bit all over the place.

That is a lot of different companies working in different industries. It surely demonstrates how much your mindset is multidisciplinary. Let’s go to the next question, What do we not talk about enough around AI x Design?

Enough is a difficult word to put a pin on. We’re starting to see people talk more about AI explainability and AI ethics. There’s more, but I think we could use more of that in the industry. Often in industrial settings, there’s the timeframe pressure because of the financial aspect of things. So quickly defining something and then quickly launching a product that sometimes these questions [on AI explainability and ethics] are overlooked. Or companies think they can’t afford to spend time on it. But I think great companies will spend time on that, and it’ll show in their products.

How is designing for AI different than other formats?

There is another layer of complexity that comes into it because it’s AI. If you’re developing a mobile product, you’re probably thinking, “How will this product affect my customers?” But because AI is not static, it gives a more dynamic product, so there’s a higher chance of it affecting people and having more impact. As you’re also working with data as a basis, you have to take things like data bias into account as well.

What are you looking to learn more about?

Actually, right now, I’m interested in virtual reality (VR), augmented reality (AR), and cross-reality platforms. On a parallel side, I am still interested in AI, so I will probably try to think and see how these two disciplines cross over. I’d like to learn more about how AI is or can be implemented in there. Also, learning how to use data to do fun stuff, playing around at the mathematics, art, and technology intersection. Mostly, just exploring where creative AI goes.

Topic-wise, I’m exploring how we can use algorithms in a more creative way. Two other things I’ve been exploring for some time: social networks and knowledge management systems. I guess my interest in social networks is because it has to do with algorithms and human connection. For the longest time, people have not been satisfied with the social networks that are available. What would a new social network look like? How can we build a social network that’s less driven by materialism and capitalism but more driven by the pursuit of truth and knowledge and sharing creativity?

With knowledge management systems, you go through life, and you make a lot of notes, right? In a way, that’s like your brain. But then we just write it, and then it goes away. So what would be an ideal system to help people manage all this knowledge that they accumulate over time in their life? That’s something my thought goes to every now and then. There are all these note-taking tools, and there are people creating ‘digital gardens.’ Each person has different systems, but there’s not really one single application that is able to keep track of it all or adapt and personalize to individuals.

The thing is, the stuff that I’m hoping to learn more about at the moment isn’t really directly about designing AI, designing ML. It’s stuff on the side, but there’s the possibility that AI could help or come into, or maybe even not come into.

Interesting, tell us about your favorite use cases so we can look into them?

Spotify is amazing. I love how they are a blend of creative and personal use cases of AI. I also enjoy watching self-driving cars and how the machine (the computer system installed in the car) sees different things. Not only how the cameras view different objects and classify them, but also how they segment the objects.


For my favorite use case, I’d say activity recognition. That’s super fun to look into, especially coming from my background. How it works is it’s pretty much signals from sensors in your phone. If you look at the data, you’ll see continuous lines, and the algorithm classifies what action is happening. So, that’s one of my favorite use cases from a technical perspective because it’s some signal processing, which I enjoy.


What are you most anxious/concerned about? What are you most excited/hopeful about?

I am going to answer these two questions at the same time. Right now, we’re still mostly at narrow AI, so I’m really excited and curious to see what it would be like when we get to general AI and AI is able to reason. That also falls a bit under anxiety; how our relationships with AI will evolve over time because people fear what they don’t understand. So I’m a bit anxious about the pushback. This cohabitation between AI and humans. What will human relationships with AI be like? But what I’m hopeful about, in terms of the development of AI, is all the doors that it’s going to open and all the new questions that we will have in terms of applications, as well as design.

It reflects our nature as a society and it represents the world as is. Because there is already bias in the world as it is, it shows up in the data as well.

AI helps us to process huge amounts of data, more than we’ve ever done before. Especially now, with quantum computing and better hardware, we’re gonna see amazing analysis and be able to find connections in data in a way that I don’t think we’ve really seen yet. I mean, in the past 50 years or so, we’ve already seen the ways that AI has allowed for accessibility in health care. Everyone kind of has their own personalized doctor in a way, or personalized nutritionist, among others. With all the things like Fitbits, people are able to know more about their lives. So yeah, just imagine that, but like multiplied. I’m hopeful about all the insights we’ll be able to extract. But then I’m also anxious about how people will be affected by our society's biases brought up by AI. There’s already ingrained bias in the society that we’re just realizing now (or being more convinced of its existence) because it shows up as an AI design problem. And I think we’re gonna find out more about that. It reflects our nature as a society, and it represents the world as is. Because there is already a bias in the world as it is, it shows up in the data as well. It reflects our society more, and it’s like we’re looking into the mirror at ourselves. That’s a really anxious thing because we will see the problems, but that’s also very hopeful because if the problems don’t arise and we are not conscious of the problems, no change is going to happen.

If you could bring one book to a deserted island, which would it be?

I love books, but If I can pick one, maybe “Tuesdays with Morrie,” which is about a professor who’s dying. The main character is a former student who reconnects with him, and every Tuesday, they meet, and Morrie gives him life lessons. It’s one of my favorite books.

“Tuesdays with Morrie” with Mitch Albom

Favorite podcast?

I’m really terrible at listening to podcasts. I don’t have a podcast that I listen to regularly. I do like this one podcast from Lex Friedman from MIT. I think that’s one I listen to most regularly. Or the episodes that are recommended to me. One of my favorite episodes is the one with Rosalind Picard on affective computing.

And the last question is where can we find you?

You can always reach out to me on LinkedIn. I’m trying to do more write-ups of my projects and workshops, and when I post them, they will be available on Medium.

This interview was conducted by Boshra Javaheri.

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Boshra Javaheri

Designer and researcher passionate about people, their experiences, emotions, and interactions with AI. Get to know me better