When I organised this workshop, I simply wanted to understand how the students would look at common objects and what they would be able to imagine starting from familiar shapes.
The objects were the same for everyone, but many different stories were created!
Some students started from the shape of the object, others from an idea or an image they already had in their mind. A detail could become something completely different depending on who was looking at it.
This activity confirmed something that I am exploring in my research: the meaning of an object is never completely fixed. It does not depend only on what the object is, but also on the person looking at it and the experiences they bring with them.
I would definitely do this workshop again! I was surprised to see how quickly the students were able to move beyond the function of the object and imagine new possibilities. It also created a new curiosity for me: what would happen if I did the same exercise with adults?
One thing I would improve is leaving more space for randomness in the choice of objects: instead of giving everyone the same objects, I would let each participant pick different ones, creating new and unexpected combinations.
The most interesting part of the activity was exactly this: there was no right answer, every object could become something different!
Below are some observations that emerged during the workshop…
I noticed two different approaches:
some students started working immediately, with very clear ideas
others needed more time to observe the objects and let themselves be inspired
Some objects led different people towards similar interpretations, probably influenced by their shape:
screw → drill
pine cone → tree crown
shoehorn → slide
glove → bird
When an idea appeared, it often created a feeling of satisfaction: the object started to become something new.
The activity was experienced as a moment of:
relaxation
involvement
concentration
The first transformation seemed to be the easiest one to find. Often, after completing an idea, imagining new interpretations required more time and creativity.
In the attached PDF, I collect some of the works created by the students during the workshop!
In everyday life, we are surrounded by objects that we know so well that we almost stop really looking at them. An object becomes familiar, loses its ability to surprise us and remains simply what we think it is.
But what would happen if we tried to look at it with different eyes?
From this question, the workshop I created with some middle school classes in Egna, a town in South Tyrol,, was born. During the period when I worked at the school as an Italian substitute teacher, whenever we had some free time, I enjoyed proposing small creative activities to the students. Luckily, my colleagues were also enthusiastic about the materials I prepared and welcomed this activity with pleasure, giving me the opportunity to experiment!
The goal was to explore how objects are perceived and reinterpreted, leaving space for creativity and imagination.
I presented the students with a series of common and random objects, printed on a worksheet, and asked them to cut them out and transform them through drawing. The task was not to represent the object as it is, but to try to see what it could become.
A glove did not have to remain just a glove. It could transform into a character, a fantastic creature, a part of a new body, or something completely different.
Through this simple activity, objects stopped being only functional objects and became starting points for new stories. Their shapes, details and visual characteristics opened up different possibilities, depending on the perspective of the person looking at them.
This workshop connects to my research: if the meaning of objects comes from the encounter between what we see and our experiences, what happens when we leave space for imagination?
In the next blogs, I will collect some of the results that emerged from this experiment and the different interpretations that the students gave to the same objects.
During International Design Week, I participated in the workshop PLAYS! with Emilio Leonardo.
One of the sentences that accompanied the workshop was: “Playing is a serious way to imagine other possible futures.”
The activity explored play as a tool for knowledge and imagination, not only between humans, but also in relation to animals and non-human systems. Through scenarios, roles and collaborative processes, we worked on the possibility of seeing the world from different perspectives.
One of the exercises proposed was “A day in the life of…”: choosing an object and imagining a day in its life.
A day in the life of a bench, Max Degtyarev
The inspiration came from the work of Max Degtyarev, who tells the everyday life of a bench through an illustration showing what happens around it during different hours of the day.
Looking out of the window, I chose an object that we often see without really observing: a street lamp.
And this is how the story of Giorgione was born.
A day in the life of… Giorgione, the street lamp
Giorgione starts his day when most people are about to finish theirs.
As the sun goes down, he slowly opens his eyes and turns on. From that moment, he stays awake until sunrise, while the city around him changes rhythm. During the day he stays silent, almost invisible, but at night he becomes one of the few fixed points for those passing by.
His life does not follow real schedules. He always stays in the same place, while everything around him changes: people running, bicycles passing, seasons changing.
Giorgione observes.
He sees people coming home late, someone stopping for a phone call, someone leaning against him for a moment.
Sometimes someone gives him a little tap, almost as if he was an old friend.
Dogs are also part of his everyday life. He sees many of them passing by and, regularly, someone decides to leave their mark at his feet.
To stay on during the night, Giorgione needs electricity. He does not drink, he does not eat, he does not move, but he completely depends on the energy that keeps him awake and ready to illuminate those who pass by.
It is not an easy life. He is always there, in the same place, while everyone else moves. Even when he is turned off during the day, someone continues to interact with him and this sometimes makes his resting time more difficult.
Maybe the hardest part is being far from others. The other street lamps are his family, but they are often only distant points of light across the city.
And yet, every night, when he turns on, Giorgione goes back to doing what he does best: staying still and accompanying the movement of others.
This exercise felt particularly interesting because it allowed me to change perspective: instead of observing an object from the outside, I tried to imagine what the object itself would see.
A street lamp is no longer just a functional element of the street, but becomes a silent observer of everyday life.
When I started my pilot study, I mainly wanted to find out whether my survey worked well. I expected to make a few small changes before starting the main study, but I didn’t expect the pilot study to change the way I think about my research. But if I am honest, I feel that it did much more than test my questionnaire. It gave me new ideas, new questions and a much clearer direction for the next step of my project.
One thing I learned very quickly is that research rarely gives you simple answers. Instead, every answer seems to lead to another question. At the beginning, I only wanted to find out whether people can recognise authentic, AI-edited and fully AI-generated images. Now I find myself asking something different: Why do people trust some images but not others? I think this has become one of the most interesting questions in my research.
The pilot study also helped me develop a few assumptions that I would like to investigate in the main study.
I expect that highly photorealistic AI-generated images will continue to be much harder to recognise than authentic photographs.
I believe that people’s confidence does not always match their actual performance.
I think that our judgement is influenced less by whether an image is objectively real or fake and more by specific visual details that make an image appear trustworthy.
I now suspect that AI-generated images may have a second effect that I had not considered before: they might slowly reduce our trust in authentic photographs as well.
This last assumption is probably the most interesting outcome of the pilot study for me. When I started this project I wanted to understand whether people can recognise AI-generated images. But after analysing the pilot study, I began wondering if the real issue is something bigger. Could AI-generated images slowly make us trust authentic photographs less? If people start doubting real images because they look “too perfect”, then AI is not only changing how images are created. It may also be changing how we decide what we believe.
The pilot study also made me rethink the design of my main study. For the pilot survey, I intentionally selected mostly very realistic AI-generated images because I wanted to create a situation that reflects how AI could actually be used in the real world. Several participants told me afterwards that the images were “too good” and that people would normally not see such difficult examples online. I understand this opinion, but I personally see it differently. If someone wanted to spread misinformation using AI-generated images, they would most likely choose the most convincing image available, not one with obvious mistakes. For this reason, I still believe that the image selection represents a realistic scenario.
However, the feedback also gave me an idea for improving the main study. Instead of using only highly realistic AI-generated images, I now want to include images with different levels of difficulty. Some images will contain obvious AI artefacts, while others will be almost impossible to distinguish from real photographs. I hope this will make it easier to compare different age groups. My current assumption is that younger participants, especially those between 25 and 34 years old, may recognise the more obvious AI-generated images more easily than older participants because they are generally more familiar with AI tools and digital media.
Looking back, I feel that the pilot study has given me much more than I expected. It helped me improve my survey, but it also changed how I think about my research question. I now have a clearer idea of what I want to investigate and which questions I find most interesting. At the same time, I know that there is still a lot to discover. I am excited to continue this project and see whether these first ideas are confirmed when I conduct the main study with a larger and more diverse group of participants.
“There are more chairs than asses,” said Bruno Munari. An ironic, almost provocative sentence that accompanied me throughout my whole research…
One chair, many stories.
The chair I am sitting on right now is a simple IKEA office chair, bought second-hand on Willhaben. At first glance, it is just a functional object, but looking closer, it tells much more. Its shape suggests concentration, the colour and materials speak of a simple and minimalist aesthetic, while the marks left by time tell something about the people who used it before me.
Even a small detail can become a story: the lever to raise and lower the seat, for example, has been chewed by a pet. Probably a curious cat that did not see this object only as a chair, but as something to explore. A place to rest, play or attract the attention of the person who spent hours sitting there.
During the first semester, I explored the communication of objects through perception, semiotics and design. I discovered that objects are never neutral: even before using them, we interpret them through what we see. Shape, materials, colours, proportions and signs of use suggest meanings and ways of relating to them.
A handle suggests how it should be grabbed, a chair suggests a posture, a worn object tells a story. But meaning never completely belongs to the object itself: it is created through the encounter between what has been designed and the person who observes, uses and experiences it.
From here comes a new question: if objects communicate, what happens when they meet people?
I want to understand how people interpret objects and how, through their experiences, they create new meanings.
Because maybe it is not only the object that tells something. We also create a story around it through the way we look at it and use it. The same chair can become a workplace, a place for a break or simply the spot where we leave something at the end of the day. The object stays the same, but the story changes.
In this second semester, I want to observe these encounters: through stories, observations and experiments, I will try to understand how objects are perceived, interpreted and reinvented in everyday life.
Because maybe objects do not communicate fixed meanings. They communicate possibilities.
Once I had analysed the overall results, I became curious about the individual images. The average recognition rate already showed that identifying AI-generated images is difficult, but I wanted to understand what was behind those numbers. Which images confused people the most? Which ones were recognised more easily? Looking at each image one by one turned out to be one of the most interesting parts of the whole project.
As I mentioned in my previous blog post, authentic photographs were generally easier to recognise than AI-generated images. But once I started looking at the individual images, I realised that the averages only told part of the story.
Some authentic photographs were recognised by more than 70% of the participants, and one image was even recognised by almost 80%. At the same time, several fully AI-generated images were correctly identified by only around 20% of participants.
One result immediately caught my attention. Image 13 was an authentic photograph, but only 14.3% of participants identified it correctly. Image 20, which was fully AI-generated, reached exactly the same recognition rate. I found it fascinating that two completely different image types produced almost identical results. So, looking at each image individually revealed details that would otherwise have been easy to miss.
Another interesting part of the analysis was the confidence ratings (1 = not confident at all, 5 = very confident). Before analysing the data, I expected participants to feel much more confident when they answered correctly. Instead, the difference was surprisingly small.
On average, participants rated their confidence as 3.13 when they answered correctly and 2.99 when they answered incorrectly. Both values are very close to the middle of the scale, meaning that participants generally felt only moderately confident about their decisions. What surprised me most was how similar these two values were. Whether participants were right or wrong, their confidence hardly changed.
I also noticed a change in how participants viewed their own ability to recognise AI-generated images. Since participants rated their own ability before and after the survey, I was able to compare both answers. At the beginning of the survey, many participants rated themselves as being quite good at identifying AI-generated content. After completing the survey, several participants rated themselves as less confident than before. Although this pilot study is too small to draw firm conclusions, it seems that taking part in the survey made some people realise that distinguishing between authentic and AI-generated images is more challenging than they had expected.
The second part of my pilot study was a little different. This time, participants did not have to classify a single image. Instead, they saw two similar images and had to decide which one they thought was authentic. I was curious to find out if comparing two images directly would make the task easier.
The average recognition rate was 55.4%, which is slightly higher than in the first part of the survey. Even so, I was surprised that the results were still so close to chance. Some image pairs were much easier than others. Pair 3 was recognised correctly by 71.4% of the participants, while Pair 4 was the most difficult, with only 42.9% choosing the authentic image. Most of the other image pairs were recognised correctly by about half of the participants.
For me, this part of the study added another interesting perspective. It showed that even when participants could compare two images directly, deciding which one was authentic was often still difficult.
Analysing the results in this level of detail helped me understand much more than the overall recognition rate alone. It showed me which images were particularly successful for the study and which ones challenged participants the most. These observations will surely help me improve the image selection for my main study.
!!Attention!!
!!Please only look at the documents if you have already completed the study or if you do not intend to participate in it!!
For this semester, I wanted to show a different side of design activism, namely, design activism through analogue experiments. I did that by first researching what kinds of experiments I was going to focus on and deciding on a certain topic that I wanted to focus on, since the whole area of design activism would’ve just been too vast. I thought about doing something on sustainability, but this would’ve asked different questions and it would’ve been tough to show sustainability in different ways than it is already shown. I also thought about doing something on fashion, since that is one of the main fields that I have knowledge in, but this was actually a field that I have already researched so many times and I wanted to get out of doing the same thing in all aspects of my life over and over again.
Therefore, I decided on the topic of food. Specifically the phrase: “Food is political” and the aspects of showing certain cultures or talking about problems certain cultures are facing today through fruits or vegetables as symbols. This turned out to be the right topic for these experiments, since I love working with food or showing different kinds of foods. However, it also turned out to be quite difficult to work with this, because it is such a political topic on many different layers. Food politics have been with us throughout the history of mankind. There was always some sort of dependence of people that put their livelihood on producing and cultivating different kinds of foods for other people that had more power than them. Wars were fought over food and some of the biggest panics that arised were, when food was scarce and there was not enough there for everyone. That is all still the case nowadays, even if we privileged people like to forget these aspects usually.
I may not have made the most of my experiments, but what I can say is that even though my life is currently really difficult and I didn’t have the time to do all of this, which is why all of my posts are now coming at once. I really did some experiments and I also did everything myself and put all of my own thoughts into these blog posts without using AI for any of it. I hope that it is still appreciated, because I just want to keep the skills that I have of writing texts. In times of AI writing is something that happens so fast and so easily, so it is easy to forget that it is a process that takes time, but it is also a process that gets the brain going and enriches us. So, in times of complicated AI texts writing in ways that people would never write themselves and everything becoming much more similar and much more artificial by the second, I hope there’s still people out there that appreciate people for trying and for being authentic with their own experiences. Thank you for the opportunity of doing these experiments, even though it was much more stressful for me than it should’ve been. Thank you for coming on this journey with me. Looking forward for the directions that I really will go in the future with this thesis.
I have already done quite many experiments for my research, this time I decided to activate another childhood memory and do something with play-doh. I had many ideas on how to approach this topic, since it makes certain playing aspects possible, so I’m sure that it would’ve been nice to also use some other tools than just plain play-doh. In the future, I would definitely try to also include using some stencils to make the whole object more patterned in the end. To add to that, it would’ve worked well to combine some of the colours and really mix them so that the different colours mix at some points and some others show up in streaks in the patterns, of course this method can only be done once, since the colours will then be mixed together and cannot fully be taken apart anymore. However, I think that in this case it would work out well to just form some abstract shapes with it and then use this type of structure for future projects.
The play-doh I used was of lesser quality, therefore it tended to stick to the hands more than it did other things. It was really hard to form and I think it would’ve also been harder to mix. When I started the process I already wanted to get it off my hands, because it was really uncomfortable to work with. Since this was still my experiment and I had to make at least something out of it, I decided to work on two simpler shapes that I had done before in some of my other experiments. The watermelon and the pomegranate. I only had little play-doh, so I had to make them quite small, which was fine, since this experiment was just supposed to get me started and help me try out different materials. To start, I chose the colours that matched best with the result I was going for, started to make the play-doh smoother by rolling it in my hands for a bit and then decided on doing simple shapes to just show the fruits for what they are. The pomegranate was just made out of red play-doh in two pieces, a ‘crown-like’ piece for the top and the round body of the fruit. The watermelon was done by using, emerald, black and pink play-doh and creating a watermelon slice, by making its distinct shape in a pink moon-like shape, the outer part in a similar shape but much thinner in emerald and the seeds in black. First I wanted to add just three seeds, but I decided it would look better with five seeds.
In the following pictures you can see my final outcome. Again I chose to stay with the same topic as all of my other blogposts, so the pomegranate stands for Iranian culture, while the watermelon stands for Palestinian culture.
One of my earlier experiments was making a collage out of paper scraps, so this time I decided to try it out with fabrics. Since I have been working a lot with fabrics in fashion school and I have so many leftover fabric scraps, I decided that I could at least give this a try. My plan was to be much more detailed than I was in the end, also because I found out that I didn’t have too much of the colours that I wanted to have and I didn’t want to use new fabrics, because this was supposed to be a project that uses up some of my fabric scraps. It started out with chaos. The chaos of rummaging through all of the fabric scraps that I still have at home. Then I chose some that fit the colour and topic scheme that I was focusing on for this part of the experiment.
The next step was to try to choose which of the coloured fabrics to use for which motive and cut it out, while trying to focus on which kind of fabric to use for what part of the project and what structures to combine for the right outcome. For the first part I worked solely with red fabrics and decided to just use the fancier ones, since the others just didn’t seem to work for this pattern-wise. I ended up choosing an old fabric of a ballgown and some lace to cut out a pomegranate, again standing for Iran, as well as some lace detail, to make it more interesting structure-wise. We are still on the same topic of using food as a political symbol for a certain culture.
The second idea was to use more yellow and light green colours, as well as, other Ghanaian fabrics that were leftover of some t-shirts to create a plantain and some colourful background representing Ghanaian culture a little bit. Luckily I still had a few fabrics left that made this composition work, otherwise it would’ve been harder to achieve.
In general I tried to find some more fabrics for other compositions, but since I didn’t find the right colours, for instance for another watermelon or for some other fruits or vegetables that algined to my chosen topics, I decided to just stick with the ones that I could make more easily. In the following pictures you can see my end-results for these types of experiments. I recommend you to give this technique a go as well, since it is a more crafty approach and includes some materials that some people tend to not work with that often. The goal of this process would be to then also really put it on a different kind of fabric and make a full collage out of it by sewing everything onto the base fabric. But I just wanted to try out the main idea for this experiment.
