My thesis builds on the hyperawareness of our body. New technology – especially in the field of quantified-self movement – gives us the possibility of self-monitoring close to everything about the physical state of our body as well as our mental state.

We know how many steps we walk, on what fitness level we are. We know how much we eat & how many calories we are still allowed to eat. We know how productive we are during work time and what situations increase our blood values. We can even measure how we clean our teeth.

Even if we could measure our body and brain accurately and get more efficient in our daily life with this gained knowledge and data, 1/3 of our life we are still sleeping. That’s more than we do anything else. And of course, we do need sleep, to be capable of doing what we want to do. But when we sleep, we also dream. However, 95% of all dreams fade away even before we left the bed.

‚Dreams serve the function of sorting through the experience of a day & integrating them with past experiences stored in our memory.‘

I assume that the quantified-dream is the next step of the quantified-self. We could even call it the meaningful-self. So, what if we could enhance the efficiency of dreaming? Make the dream phases longer and more often but also be more aware of what we are dreaming and even control the dreams into the direction we want them to go. Maybe even doing things we didn‘t find time during the day, so we catch up while dreaming? Those questions offer a lot of possibilities but also open up a critical dialogue. I want to focus on both the possible & the impossible and conclude this in a critical examination of the efficient dream.

With the help of a future cone (or rather a future landscape), I outlined a first draft of how a more efficient dream world could look like. It plays with progressive technology and stories that sci-fi films like Inception are based on, but also studies in science that tries to figure out why and how we dream. The map is divided into three main phases. The quantified-dream, the dreamer community & the dream market.

Quantified-Dream (the probable future)

The quantified dream covers the enhancement and efficiency of dreaming. It‘s a probable future or even the future some people are living in right now. In the quantified-dream we have tools to record & collect our dreams, can enhance our state of dreaming with (lucid) dreaming devices & have the knowledge to make sense of dreams & can reflect them into our conscious life.

Dreamer Community (the plausible futures)

Building upon the quantified dream, communities similar to the quantified-self movement, start to shape and organize. There could be massive datasets that collect our dreams, sort them by topic, emotion or other parameters. This could help understand how people with different cultural backgrounds dream. What people dream about when specific events like earthquakes happen. To find out how genders differentiate while dreaming and also how people with dementia and other illnesses dream.

Besides those dream studies, dream communities could also exchange their dreams and try to make sense of their dreams or build collective dream stories.

Dream Market (the possible futures)

The dream market opens up the most questions about what impact (good or bad) a more efficient dream world could have. There might be a marketplace where dreamers could buy and sell their dreams. Companies like Disney might be interested in dream stories. There might be a Netflix for dreams, where dreamers could buy dream stories they want to dream about. Companies or state institution might manipulate our dreams, transplant ideas or products in our head. There might be a substantial new advertisement market based on dream analysis.

But we might also use the dream market to learn things while we are dreaming. The dreams might be used to learn new languages, specific sports movements or math solutions. This would mean that our dream phases would be used more productively. We might do tasks, we don‘t find time during the day. Meet family members (dead or alive) we would not meet else. And we might also dream together, similar to the plot of the film Inception.

The influence of sleep and dreams for the creative process is a technique that some of the greatest minds used as an influence on their work. Salvador Dali, the master of surrealism, for example, used a method where he did hold a key in his right hand and beneath his hand was a plate. Once he fell into a deep sleep, his hand releases the key which clings onto the plate, so he awoke with a refreshed mind ready to get weird again. But also other geniuses like Einstein, Ludwig van Beethoven or Aristotle used the power of dreaming for their work and other problem-solving tasks.

[...] ‚this fugitive moment when you had barely lost consciousness and during which you cannot be assured of having really slept is totally sufficient, inasmuch as not a second more is needed for your physical and psychic being to be revivified by just the necessary amount of repose.‘

Based on my research of how creative people in the past used their dreams for their creative work. I started to outline three personas that use their dreams actively to be more creative, foster new ideas & test them in a protected environment.

There is Thomaé – a surreal VR artist who embodies his dreams while asleep, Frederik – a copywriter and best selling author who uses his dreams like a puppet master and Samara – an Interventionist who conducts social design problems from a dream-like perspective.

All of those three personas enhance their dreams with nearly invisible technological devices. These devices let them dream more vividly, focus on specific problems & helps them reflect on their dreams.

I imagine this device to act like a box which you can feed with specific inputs, like sketches, or an initial idea. A disruption mode while asleep that helps control the dreaming states and our body. And last but not least an output system that connects our creative dreaming experience in a loop with our creative process.

A big part of my project is based on experiments that I conducted on myself. I started to induce my sleep and dream phases with different methods and prototypes. My initial goal was to finally dream lucid and also to see what outer influences can have on my sleep and dreams, but as my project evolved, I‘ve changed direction a little bit. Some of those experiments are based on lucid dreaming and psychological methods, other ideas are based on a possible dream device.

Those experiments should also encourage you to try it out yourself. A simple step-by-step guide and goals that I set for myself should help you to become a professional dreamer yourself. You can find all the experiments on my project blog.

At some point during my self-experimentation phase, I asked myself again, what is actually the most satisfying experience we can have with dreams? And where do we already interact with our dreams? Of course it’s dreaming itself but as I found out in my research also dream sharing. As soon as I started to talk to someone about what I‘m currently investigating, they interrupted me with something like: “Oh interesting… I had a very weird dream last night.” Or, “I recently had this dream about somebody, but I don’t know if I should tell it to this person”. Dream Sharing seems a very important factor in processing our dreams. Following this idea I thought about three different scenarios and rapid prototyping ideas.

A dream platform where you could actively share any kind of dreams with other fellow dreamers. More profoundly, this idea would involve a device to share your dream reports to others or save them for later. A small record and play system that is notifying you when you receive a dream. Similar to Snapchat – you could only listen to the dreams once.

Building upon this idea, I started to tweet my dream reports and also share my thoughts about dreaming, my daydreams and other dream related content.

How can we reflect on our dreams just after awakening but as well during the day? Is a dream/day journal useful? How can we share our dreams with others? How can we build collective stories?

Based on my self-experiments and my dream journal, I also wanted to find out how other people dream. A cultural probe helped me in this research phase.

It started with a blog post that I shared over social media, where I was looking for fellow creative dreamers that would like to know how we may dream in the future or how to enhance dreams for creative problem-solving tasks. Furthermore, I also asked some of my friends if they were also interested in.

From the beginning, it was vital for me to not only have close friends that would participate in this probe but also people I don‘t know at all or just briefly – for this I used my network on Linkedin, where I got in contact with some unknown dreamers.

With nowadays technology and also the growing quantified-self market, analyzing data is a big thing. So I thought it’s probably only a matter of time till we start analyzing our dreams with Artificial Intelligence. Based on my research and self-experiment, I came to the conclusion that emotions are the most valuable experience we have in dreams but also that those emotions can be very sensitive and individual.

I started a simple experiment, where I analyzed my dream reports on emotions with the help of IBMs Watson AI and the open API called Tone Analyzer.

The Tone Analyzer uses linguistic analysis to detect three types of tones in written text: emotions, social tendencies, and writing style. With the help of this service, someone can understand the emotional context of conversations and communications. You should use this insight to respond appropriately.

With the help the low code development platform Stamplay, I’ve managed to connect text messages send within Telegram App to a corresponding Dream Analyzer Bot with IBMs Tone Analyzer API. Those messages would then be analyzed for five emotional states.

For each emotion, a score of less 0.5 indicates that the emotion is unlikely to be perceived in the content. Likewise, a score greater than 0.75 indicates a high likelihood that the emotion will be perceived.

Afterwards, a bot can send a message with the analyzed data back to the dreamer or can even give more personal feedback.

A more speculative idea of this could be a Dream Prediction AI, which I already mention in my self-experimentation phase.

A further iteration of the dream analytic idea became a rapid prototype of a Dream Analyzing Bot. Dreamers can share their dreams with the bot, and according to the dream report, the bot gives the users back some emotional data. The bot works through text messaging app Telegram, connected with the Tone-Analyzer API from IBMs Watson.

The goal was to find out how those analytics represent the feelings you may have during your dream or just after awakening. I was also interested in finding out if it is valuable to trust the emotional output of a bot only from a dream description. At some point, I also implemented emojis that the dreamer receives when one emotion is very high.

I was aware that the API is not really meant to find out how someone felt during an event and more focusing on how something is formulated and written.

The analytics are depending heavily on how a dreamer is describing the dream – the content of the dream. More precise and thoughtful dream reports that already include feelings gave other results as very brief, unemotional descriptions of dreams.

The analytics also represent somehow, how someone else could interpret the emotional state of an external dream when hearing it for the first time.

User tests also validated my assumption. However what was way more interesting to observe was, that after some people saw the results from the bot, they were a little bit perplexed and unsure if the results would be more accurate than their real feelings. A lot of people also asked what‘s behind the bot and how it works. Funnily simple answers like: „It‘s a Tone Analyzer from IBM Watson“, were already enough for the users. A lot of people also asked what‘s behind the bot and how it works. Funnily simple answers like: „It‘s a Tone Analyzer from IBM Watson“, were already enough for the users.

After a few self-experiments, I came to the conclusion that no visualization comes close to what we experience in dreams. Also, when sharing dreams, the perception of dreams is very individual for all of us. However, it is interesting that even blind people have sort of a similar understanding of the world as people with sight. That’s probably the cause because of the descriptions and storytellings blind people get from people with sight. For example, A sun has to be round and is shining.

An interesting investigation from graphic designer and artist Tobias Gutmann shows that a lot of people are stuck with a conventional representation of the world. He asked people with different cultural backgrounds to draw a house and a world. The similarities and differences between people with different background and especially kids are impressive.

I came to the conclusion that the perception of the world can be very individual. Especially when compared with kids, people from non-western countries or even computers.

The same applies to dreams. As dreams are fractals from something, we maybe have experienced or not and put together in a way that most of the time doesn’t really make sense. There are gaps between our dream stories that we try to fill with the information we gather from non-dreams. You could go further and say that as soon as you share a dream, it is no more your dream but now the dream of someone else. Because this person is interpreting the dream from a different angle.

I set myself the goal to find out how we can generate a (kind of) language for dreams with creative coding. Therefore I‘ve investigated some time to learn and refresh my creative coding skills and generative art forms in general.

I did a few iterations testing different visual outputs with tutorials, open source codes and my coding knowledge from the past. I played around with simple meta-balls, more complex 3D supershapes, experimented with voroni shapes, perlin noise and flow fields. At some point I came over fractal flames. A tutorial from Tsulej helped me to handle those in processing.

The output was minimalistic, yet the gorgeous generative look of a point grid that I could manipulate and enhance with some tweaks. The emerging shapes do vary a lot from each other, only with some small math changes. Therefore those would differentiate and leave enough space for interpretation.

In the next step, I wanted to find out if specific movements or shapes could be retraced to particular emotions or would have similarities.

Through variations and math formulas, you can generate different shapes in fractal flames. I investigated more time into finding out how I could use those generative drawings in my final project and how I could implement them into a device.