Out of the 9 participants, 7 responded by posting a cherished memory of theirs. Below are the memories shared.
Below is the wall, before and after the generation of images to depict these memories.
Following this process, I have sent out a questionnaire (feedback form) to the participants. The participants will be sent the before and after and have to answer a few questions on the process. The questions I have posed are:
1. How did you feel having to share an old cherished memory?
2. Does seeing the generated images, alter or affect how you remember the event?
3. How does it feel to see your image amongst many who have shared fond memories?
4. Do you feel any difference when seeing the before and after of the wall?
5. Do the images make you curious to read other people’s shared memories?
6. How do you feel about AI being used as a tool to create moments from your past?
7. Is your opinion on generative AI changed in anyway through this process?
For this intervention, I was able to engage 9 individuals that practice visual arts in some capacity.
These individuals range in age from 22 years to 39 years.
2 participants identify as Female,
3 as Non-Binary and
4 participants identify as some degree of Gender non-conforming.
2 participants are engaged in full time employment in visual arts ,
3 make supplementary income through visual arts, and
4 participants engage in it as a hobby.
Below is a break down of the forms of art identified in their practice.
I further enquired if they had ever used or engaged with generative AI. Out of the 9 respondents, 5 had engaged in the use of generative AI in some capacity.
Further, I wanted to understand their views on the technology before I moved to the next stage of the intervention. As such, I think they were unaware that the intervention had already started.
Below are the responses to the question: Please tell us a bit about your current views on generative AI.
I posted a shout out for visual artists to participate in the “Wall of Memories: Lost and found” intervention. I had initially planned to do a physical wall, but as I have been travelling and interest came from various parts of the world, I decided to replicate it as a digital wall instead.
The sign up sheet was a google form. [screen shots below] Sent out over the weekend of 12th July to 15th July, I wanted to give adequate time for participants to sign up.
Following the sign up, I sent out communication in the form of an email and followed up via the social media links provided. This included the explanation and instructions for participating in the intervention. [screenshot below]
Are there memories for which people don’t have photographs?
Have there been moments in our lives that we wish we had captured but didn’t?
Or did evidence of those moments get lost to time?
Can we take the stories from our memories and recreate them?
Will this feel good or bad? Is this scary or pleasing?
Can we change the way we look at our past?
These are some of the questions I was asking when planning an intervention. How can emerging technologies in generative AI help us recreate and curate memories to help shape our outlook on the self?
To answer these questions, I have envisioned a Wall of Memories: Lost and Found.
The participants will be asked to write down a memory that they cherish but have no photographs of. Something from their past that is important to them. They will then place this memory randomly on a wall. The wall will then become a wall of lost memories. I will then replace these texts with AI generated images of their description and allow people to come back and see it.
Did they notice what was written around them before? Or will they notice it better in images. Will their image help them better connect with their memory? How will this affect their view on the past and on the future of technology?
My journey to the Tate Modern in London was dedicated to see Yoko Ono’s exhibition: Music of the Mind. I often find museums and exhibition centres to be places of inspiration. My mum had had a chance to visit this exhibition and was moved by it. Aspects of the showcased works intrigued me to check it out for myself. What I realised was that Yoko Ono had a fairly interventionist approach to her art. But then again, one can argue that all art is interventionist in nature.
One of the works that inspired me was ADD COLOUR (REFUGEE BOAT). In an all white room lies and all white boat. Visitors are asked to take the blue, white or purple markers provided and write messages of hope on the white space. Visitors have slowly filled up the space turning it into shades of blue. It is meant for the participant to reflect on the plights of refugees braving the ocean to arrive into Europe, the urgent crisis of stateless people and the impact of collective action. I feel there is something poetic albeit sad about this. I couldn’t help but feel it was a metaphor for the many who are claimed by the sea when attempting this perilous journey, similar to the blue that claims the white space. Our writing and drawings, a prayer of hope to those that have failed to cross the vast waters.
On observing the piece, I could see that the most dense area of colours were those at hand and eye level, slowly tapering up and down. There was almost no marks above a certain height where no one could reach. The floor and boat also covered in ink. There was ink on top of ink as large spaces wore away. There were also spaces that no one could reach on the underside of the boat. Upon exiting, I could also observe the ink that has managed to escape the room through the shoes of some participants, in someways it is a metaphor for the art spilling out of its designated space and into the outside world.
The second large piece of work was – The personal is political: My mom is beautiful. Participants were asked to write messages and notes about the memory of their mothers, while a video played of Ono doing a hauntingly beautiful musical performance. This room too was filled to the brim with varied text in unique handwritings. Notes placed one on top of the others, high and low. I wonder what it would’ve looked like at the starting moments and how the very first notes have long been covered up.
I find the approach of these works to be extremely inspiring on how to approach the idea of imagination and engage audiences. My aim to utilise Yoko Ono’s work to inspire my approach towards intervention techniques as well, or at least give it a start point to diverge from.
I’ve been tinkering with Tensor.art, an image generating platform. My first impression of this platform was that it was a new type of website that I was visiting. Harking back to the early 2000’s when the internet was a less centralised space. Over the last decade, the majority of time I have spent online has been on either social media platforms, search engines or games. This was very different from those. The success of chatGPT may lie in the fact that it is a new kind of use of the digital spaces we visit, one that is more active rather than passive.
Tensor has many things to offer its visitors. Here is the landing page. The many options availabe for explorations include the ability to create your own images by using the large library of tools and models available. One can also train their own LoRA (low rank adaption) a form of base trained models to provide context or style that you may be looking to create. It also allows the use multiple LLMs (large language models) such as stable diffusion, flux as well as those independently created by enthusiasts. One can choose from a wide variety of tools and models due to the open source nature of the platform
Here, I am giving an example of the image generator. I wanted to create an image of a boy riding a bicycle through a forest. I kept the prompt simple to demonstrate how using different LoRAs changed the image created through the same prompt.
I started with a base of Indian woman and combined it with different LoRAs. The images varied based on the second input. Some models worked better with each other while others can interfere with each other to create an output.
Different models can be assigned prompt weights that decide how much of each model is considered in the final outcome. In case of prompt weight being too high, the website will suggest changes for use.
There are lots of modest to choose from and it can be a good tool to create a vary array of images. Here are some examples where the models worked against the prompt to create some hilarious results.
I spent the last week playing with Tensor AI, a free image generating AI website. I was made aware of this through an AI artist whom I interviewed. They spoke on the subject of not having digital art skills but having the desire to create works of their favourite characters through the use of Gen AI tools. My earlier assumptions were that a generative model of AI required text input that were descriptive and would generate a close enough image to what is desired in a “generic” AI style. My experience this week has taught me that AI generated art is harder than it first appears, especially if you are trying to achieve a specific output. Tensor AI had a large number of base models that have been developed to cater to different styles and different characteristics models. It is a large part of model training that has been done by individuals or groups and can be used to build up from. To generate images, one has to build upon these models and spend time experimenting on how different text prompts translate into images and how different prompts interact with one another. I see this field of art evolving into a specialised field, similar to the use of digital design software’s such as Adobe or Corel. While it makes the creation of images faster, the training that is required for individual creators does take time, interest and engagement. It also requires research to create different styles of work. The same prompts may translate very differently on different models. If you spend a lot of time getting comfortable with the use of one, it may be difficult to shift to a new base model. I therefore, see artists specialising in a unique style that they have developed through the combination of the generative models that they have chosen and expertise with the use of prompts learnt through experience.
Playing with AI models (part 2)
This week has made me experience something new. I personally may not shift entirely to using generative AI tools for my creative practice, but I can see it’s appeal. I was able to create a vast amount of image option, even though they were not meant for any end use. The anticipation of each new image being generated; what was going to pop up? An entirely unique and new visual piece was exciting, almost titillating. There was a sense that this was not an image I found on the internet but created using a software and will not be seen by anyone else. A private work of art (using that term loosely) that was spat out by the technology god, only for my eyes. I can imagine that people who create AI images must be experiencing a similar sense of purpose as they sit for hours testing prompts and perfecting a range of images. Though works of art created by AI cannot be copyrighted, they must feel a sense of ownership over their work. Many of these creators may have felt that they missed the ship on the digital art movement, but now have their own little boat to ride upon behind it.
Going into the incubator, I was unpacking a lot of information. I had to find an easy way to present it and engage the audience. Keeping it to comparing two popular platforms definitely helped with this process. My concern now coming out of it, is that presenting large chunks of legal data is not productive in changing minds or engaging the audience to introspection. A lot of these systems (social networks, media and ownership rights) have existed for some time and there are clearly more experienced minds working on both sides of the discourse. My engagement felt in that sense, a bit boring. As I proceed with this project I need to pull my subject of research out of the realm of data and security and into the realm of culture and application. I feel I need to make my interventions in the future more engaging and fun. This is something I will look into as I progress further. I don’t think it will be an excuse to say, this subject is new for everyone including myself and that it has little prior examples on how to be approached. Because of the contemporary nature of my subject, I need to search for directions and perspectives that are niche or yet unknown to create a more interesting way of generating interest.
For the incubator, I asked the question- Who owns your work online? It was meant to highlight the current information gap amongst those that use social media and the privacy policy they have agreed to. For simplicity, I used the example of two well known platforms- YouTube (owned by Alphabet/Google) and Instagram (owned by Meta/Facebook). Comparing the privacy and licensing rights users agree to when signing up and sharing their work on these platforms. Meta/Facebook has been in the press over allegations of unfair practices and non-ethical privacy practices*. Google has largely kept a relatively cleaner image*. However, a comparison of their terms and conditions documents show a different story. Most respondents that I interacted with were surprised by the findings and were not aware on the details of the contract they sign when using these platforms. There was one respondent who was aware due to their research work in the field of data collection. This may suggest that unless a person is specifically looking into the field of data collection and usage, platforms discourage Awareness on the subject. This is designed into the way these contracts are presented*.
Data from both websites was accessed on 9th may 2024.
Process:
Over the course of 1 hour, I used an original illustration to intrigue interested participants to come forward. I started by introducing the subject of digital ownership and licensing. This was followed by a short quiz. The questions were-
Question 1: When you upload a photo or video of your work on Instagram, who owns it?
Out of 9 respondents, 8 replied with Mark Zuckerberg or Instagram.
Answer: Infact, you own the rights of your image or video, however you grant them non exclusive rights to use it.
Question 2: Do you know what licences you provide to online platforms when you use them?
Out of 9 respondent, 9 replied that they have some idea but aren’t a 100% sure.
Answer: Between these two platforms you are granting them rights to host, use, distribute, modify, run, copy, preform/display and create derivatives of your work. These rights are transferable, sub licensable and royalty free.
Question 3: Out of the two platforms (YouTube and Instagram) which do you think has a longer licence period to use your data?
Out of 9 respondent, 9 replied that it was probably Facebook/Meta/Instagram.
Answer: the truth is that based on their current agreements, meta owns your these rights till you delete your post from their platform. Youtube however continue to retain rights after you delete them, till what they claim is a “commercially reasonable period”. They also maintain server copies of your videos.
Question 4: Did you get a chance to read the terms and conditions for the different platforms you use online?
Out of 9 respondents, 9 replied that they hadn’t read the Terms and conditions as it was too much to read or they didn’t care enough.
Question 5: Will you be reading them now?
Out of 9 respondants, 6 replied that they probably won’t. 3 responded that they are intrigued and will give it a try.
Feedback:
Participants felt engaged and noted that they had learnt new information with this interaction.
Some of the participants felt the intervention simplified a subject that was often information heavy.
The general sentiment was that this was a topic they had come across but not engaged with previously due to its complex nature.
Most participants felt that while the information was interesting, it would probably not alter their actions in the future.
