I enjoyed the class because I was genuinely interested in the GroceryHop app that we worked on. Conducting surveys and figuring out what the market needs has been a non-linear & a very educational process which I think gave me great insight in terms of creating products/apps with user in mind. As an ID student, it was also pretty remarkable to see the app come to life through coding. I also learned storytelling through videos which will be beneficial in my studies as a designer.

That being said, I wish we were introduced to coding and CS software in class. Although there was great collaboration and communication with our CS classmates, I initially thought that we would get some sort of exposure to what CS students learn. I am definitely interested in coding and will be trying to learn the basics in my free time in the future.

Overall, I think we came a long way since the beginning of the class, delving truly into what the user wants and how to provide it to them. Our team was overall passionate and interested in the topic we chose, so the positive group atmosphere was definitely a plus.

On Readings – Pt. 2

Artificial Intelligence as a New Design Material & UX Design Innovation: Challenges for Working with Machine Learning as a Design Material

Both articles point out the challenges that AI have and why they fall short in satisfying humans in ways they expect to be satisfied. These points raised a whole new question in my mind, maybe slightly off-topic but somewhat still relevant. The AI receives stimulus and responds to it, just like the neurological system of humans. However, human behavior is not limited to the data we have gathered (i.e. experiences), we rely on the data of other human beings, the restrictions set by society, emotional responses and most importantly empathy. Without such inputs, these AI challenges arise. Out of all these, empathy is in my opinion the hardest one to replicate because there is no hormonal or physiological explanation for why we have this skill other than our evolutionary coding (I read this article because I actually got super curious as to why we empathize so if you are curious, there you go ( your-wise-brain/201003/how-did-humans-become-empathic) Even though we can transfer data from one computer to another, set the restrictions of society, teach emotional responses, I believe the step that sets humans apart from AI and makes them inefficient at human-to-human interaction and cause dissatisfaction (or sometimes even danger) in adaptive technologies is because they can learn from behavior but can’t predict expectations. “They may inadvertently display an inability to understand the intent behind users’ behavior, which results in “intelligent” features being perceived as useless and unintuitive” ” is one of the points made in Dove & Zimmerman’s article emphasizes exactly this point. Until then, they will most likely be used as a tool for data exchange and complex problem solving and continue to have the challenges discussed within the article. And I think, allowing the share of control is the most dangerous of all because if the controller programs the AI with malintent, the AI is not in a position to predict the ramifications of its behavior.  And as to why it is hard to prototype with ML is again relevant to the points I made above. Machines currently lack common sense and are unable to make sense of data in a more complex and all-inclusive fashion like humans do, making them great at assisting us by providing us information but less than satisfactory as a dependable source of feedback.

Machines Learning Culture

When it comes to art, I have always wondered how conscious is the artist when he/she creates his/her paintings? I have always been curious if Artist B arranged his work according to the inspiration gathered from Artist A’s work or was it merely a coincidence that for example, they both painted the interior of a room with blue windows? Or are the critics reading too much into it? Here in a visual, Bazille and Rockwell’s paintings are being observed. It is true that the machine has figured out similarities in composition and subjects but it is still us that interpret what any of these findings actually mean. This is similar to Turing’s “Normalizing Machine”. Does the machine know that it is looking for normality or do humans interpret its algorithmic pattern as a proof for what we hope/consider to be normal? Is the machine really learning anything or is it a mere illusion on our part or wishful thinking towards the machine as it begins to respond in consensus to our expectations? In my opinion, the ones who reject machine assisted analysis and the ones who work with it are just changing the way they get to the result but are not changing the result itself because the result is just an interpretation of the data presented analogically or digitally. So at the end, the machine is not “learning” anything, it just begins collecting data in accordance to our expectations.



Wallet Designs

My CS partner dropped out so I had some issues with data collection but I had casual conversations about wallet designs with my friends and figured out that majority of my classmates don’t carry a traditional wallet. There is a major interest in wallet designs that are more mobile – in the sense that they are easily carried and also that they usually have mobile phones attached to them. Therefore, I looked at ways to minimize the amount of space taken and maximize the space and ease of use offered by such phone cases.



Out of the three designs, I prototyped the last one because I liked the idea of a hook to attach your wallet onto your pants. Of course, I had to consider ways to make sure that the phone or the wallet would just slide down or drop so I incorporated magnets onto my sketches to hold the wallet.

This design has a hook that attaches to your clothes with a magnet and allows you to easily chose between cards by offering multiple accordion-like slots for cash and cards. Ideally, the phone slot would have a protective screen for extra protection, allowing the wallet to also used as a phone case. The screen of the phone is not concealed so that you can still see your notifications or respond to incoming calls.

Overall, my focus was to have a design that protects your phone, has multiple slots for cards and cash, that is compact, mobile and secure. There can even be a pin attached to the back to completely ensure the position of the phone and protect it from pickpocketing. It also solves the issue of woman pants not having pockets because the design would ideally work for any clothing by placing the pin on different places such as the collar of a dress or a chest pocket on a shirt.

Reading Week 1

The most intriguing part of the first article was the discussion about how our pleasures have been majorly separated from our task in means of maximizing efficiency. It made me question why we seek comfort in our extracurricular activities and whether or not efficiency would be affected in a positive way if people associated tasks with pleasure. Also, the discussion about complexity of humans and AI’s place in experiences was interesting in terms of understanding the challenges of converting data input of computers into emotional outcome of humans. It made me realize how a value of an experience depends on meaning and think of ways to enhance the meaning in order to make an experience valuable.
The second article pointed out the components that made an experience valuable which I think was an excellent, more detailed continuation of the article previously discussed. Both articles made me question the ways of engineering an experience, using the threads listed, in order to create something valuable and pleasurable.