Month: February 2024

Chris Crawford’s approach to explaining interactivity was something that struck me as it is not something I considered before. Crawford repeatedly likened interactivity to a conversation, one between users and systems. What I found really interesting about the way Crawford described interactivity is the fact that he showcased a somewhat strong relationship between the two. This kind of relationship goes beyond what I was accustomed to, which is that interactivity between users and systems was merely input-output interactions. In a sense, reading this challenged my preconceived notions about interactivity as it forced me to see how both users and systems actively engage and influence each other, making interactivity more dynamic than I thought it was. 

Although I appreciate the perspective Crawford brings in regards to the analogy of interactivity as a conversation, I still think that the author oversimplified  the nature of interactivity. Yes, Crawford showcased the dynamics and complexities of the interactions between users and systems. However, I feel like the way he showcased these interactions tended to be idealized, in a sense. The analogy of conversation made it seem as if there was seamless interaction happening between users and systems, which in reality is not the case. This disrupts the very same “flow” of interaction Crawford brought up in the chapter in regards to interactivity design. This made me question the practicality of Crawford’s analogy in interactive systems in the real world, particularly in regards to its ability to accommodate to different challenges that might appear when discussing the concept of interactivity. Thus, even if the concept of interactivity as highlighted by Crawford brought about an interesting perspective on the concept,  I still believe that, to a certain degree, Crawford needs to address the complexities that underlie the concept he speaks of throughout this chapter. 

Having recently watched Casey Reas’ video, it’s fascinating how he navigates through concepts like art, randomness, order, chaos, algorithms, and aesthetics. One key takeaway that stood out to me is how randomness, when guided by certain rules or parameters, can lead to order – a concept that reminded me of an old game called “The Game of Life.”

In this game, lights follow a simple algorithm: if they’re lonely or surrounded by too many others, they go out; under ideal conditions, a new light emerges, creating a continuous cycle of life and death. Upon further exploration, one can realize that specific conditions, or parameters can play a crucial role. These act like guidelines, turning what might seem like randomness into a more structured and even aesthetically pleasing pattern. Imagine it as a kind of artistic recipe: the right mix of chaos and order, with a sprinkle of algorithms, can result in something visually appealing. It’s like making sense out of what initially seems like randomness, and that’s pretty cool.

In a nutshell, Reas’ video taught me that even in the seemingly chaotic world of art and algorithms, there’s an underlying order waiting to be uncovered. It’s like solving a puzzle, understanding how randomness can actually contribute to creating beautiful and ordered patterns.

Casey Reas is the inventor of Processing (software which I often used in my Freshman year of university) and is well known for many projects in digital illustrations. In Eyeo2012 he talked about chance operations which I found very intriguing and interesting for several reasons. First of all, his talk about random systems with seemingly random parameters which after some time tend to order and become homogenous (Process 18) is very much similar to what I did for assignment 2, where I used random functions while ending up with clear shapes depending on different parameters after many iterations.
His work based on “Tissue Work” highlights how small changes in parameters largely influence the paths his figures follow. I also found this true when modifying variables of my project which completely changed the shape. More surprisingly, the way the change worked started making sense in a nonmathematical context as well. Without thinking about the equations I could visually deduce how one parameter (percent) influences the resolution of the shape and the other (n) influences how it spreads.
I found it inspiring how many fields can random chance operations be used in physics, music, and obviously art. One might think how all these fields are related by underlying mathematical equations and might even explain how our entire universe works.
Seeing the random number book got me thinking about how if anything is truly random. As a student who studies computer science, we have often been told how you can’t program true randomness. I started wondering if we even need true randomness as controlled randomness helps us in many ways already. Be it encryption, algorithms, and in this case creating art.
The demo regarding triggering our imagination was truly fascinating, as it got me thinking about how our brains try to declutter chaos and try to do their best to make sense of what we see based on our preconceived notions.
I think that Casey Reas’s presentation and his personal experience show us how we might find meaning and beauty in the most unexpected (random) places which in turn should inspire us to look for order in chaos in both our fields and our personal lives.

I found Casey Reas’ talk about Chance Operations quite intriguing, as it reminded me of my old beliefs regarding art and its concept. Before, I had a completely different perspective about what art is and what defines artistic expression. As someone who is interested in visiting museums and art exhibitions as much as I can, my understanding of art was limited to human expressions through hand made artworks. However, as I had more contact with the digital world, I started changing this conception and appreciate the digital art, as it is showcased in the talk for example.

During his talk, Reas displays different examples of art generated by computers and algorithms. In my current understanding, it also represents art since we can use code to create different angles, shapes, colors and several other characteristics to represent feelings, emotions, and other expressions. At the same time, Reas’ talk inspired a reflection on the role of technology in shaping the contemporary art. The integration of algorithms and computational processes in art creation blurs the lines between human and machine, making me to reconsider what it means to be creative in the digital age. However, I believe it also raises concerns about the potential loss of human “touch” in art when relying too heavily on algorithms. How can we strike a balance between increasing the power of technology and preserving the essence of human creativity in art?

For this assignment, I aimed to create an artwork based on geometric shapes, especially squares and rectangles. For that, I searched for famous artists that use this kind of technique and found the work of Piet Mondrian, which became the inspiration for this project. At first, my goal was to create a Canva of size 1920, 1080 composed by several squares that give the sensation of overlapping colors, as you can see in the following image:

For this I used for loops, constants, and the full screen option when the mouse is pressed, following this tutorial.

However, I was not satisfied with the result, so I decided to modify it and create something more visually appealing. That’s when I thought of the tesseract concept we have in movies, such as Interstellar, that also illustrate this kind of chaos and order composed by geometric shapes. That’s when I worked to add some animation and make the squares revolve in an elliptical orbit.

For that, I used variables to determine the number of squares, the speed factor, square size, etc. And I’m particularly proud of the following snippet code, as it allowed me to add a bit of interactivity because when the user clicks on the screen, it increases the speed of the squares, giving a cool motion effect as you can see in my sketch as well:

// Increase speed factor if mouse is pressed, otherwise reset speed factor
  if (mouseIsPressed) {
    speedFactor = 0.5; 
  } else {
    speedFactor = 0.05; 
  }
  
  // Loop through each square
  for (let i = 0; i < numSquares; i++) {
    // Calculate x and y positions based on sine and cosine functions
    let x = map(sin(frameCount * speedFactor + i), -1, 1, 0, width - squareSize);
    let y = map(cos(frameCount * speedFactor + i), -1, 1, 0, height - squareSize);

Reflection: While I successfully implemented for loops, constants, and mouse interactions, exploring additional programming techniques and functionalities could enhance the depth and complexity of future projects. This could involve delving into advanced animation techniques or incorporating other libraries for more intricate visual effects.

Casey Reas’ talk provides an interesting glimpse into the intersection of art and chance, challenging conventional notions of control and order in artistic creation.  The artists’ work utilizes the juxtaposition of order and chaos, a theme prevalent throughout art history, using chance operations and randomness. The transition from early controlled coding to the exploration of emergent behaviors reflects a shift in the artist’s mindset, raising questions about the role of intentionality in the creative process.

The exploration of algorithms, particularly in the tissue simulation based on Valentino Braitenberg’s Vehicles,  was fascinating for me. The simulated behaviors of conceptual vehicles responding to their environment introduce an element of unpredictability and organic growth. Reas’ emphasis on the paths taken by these vehicles rather than their static positions resonates with the idea that the journey, filled with constant restructuring, holds artistic significance. This challenged my conventional understanding of art as a static, predetermined outcome, urging me to appreciate the dynamic nature of the artistic process. 

Also, Reas’ exploration of biological data in the “Signals” artwork, visualizing the communication among proteins within a cancer cell was another intriguing piece due to the deliberate combination of structure and randomness in determining the position and scale of protein cluster. It’s as if the artwork becomes a dynamic representation of the delicate dance of life at the cellular level.  Overall, the concept of chance in art prompted me to reconsider the traditional boundaries of creative control as well as made me rethink the dynamic outputs we can create from algorithms.

I remember watching video by numberphile called Chaos Game years ago which I found very intriguing.  I wanted to create a generative art illustration around that topic something that would involve Fractals and creating order out of randomness. Fortunately, I found Daniel Shiffman’s video regarding Chaos Game where I followed his tutorial for the initial version of the project which draws Sierpinski triangle.

Even this simple configuration of Chaos game is surprisingly beautiful and very interesting as we have created triangle shaped forms simply by drawing points halfway to one of the three random points that is randomly created and then selected.

Next step was to add more complexity to the project, thereby adding more seed points and refactoring whole thing to make changing variables for future reference more dynamic. Tutorial was very helpful in achieving this. To be more precise, I had two values which I could dynamically change: percent (the distance to a randomly chosen point where new point has to be placed at) and const n which is basically number of seed points.

I could make a very lengthy post talking about each aspect of the code but instead I want to highlight the code I am most proud of and rest I will either explain in class or you can see through embedded comments of P5 sketch.

for (let i = 0; i < 200; i++) {
    
    strokeWeight(1);
    stroke(255, 255, 255, 200);
    
    let neighborIndex;
    do {
      neighborIndex = floor(random(points.length)); //from array
    } while (neighborIndex === previousVertexIndex || neighborIndex === (previousVertexIndex + 1) % points.length || neighborIndex === (previousVertexIndex - 1 + points.length) % points.length);
    let next = points[neighborIndex];

    current.x = lerp(current.x, next.x, percent);
    current.y = lerp(current.y, next.y, percent);
    
    point(current.x, current.y);
    
    previousVertexIndex = neighborIndex;
  }
}

This is an additional condition I added to make it so that newly chosen point can’t be the same as the old point or a neighboring point from the polygon. We are using LERP (linear interpolation) for updating position.

In the future, I could possibly experiment with more shapes and more drawings and users are also welcome to modify the code and play with it. Perhaps, adding a slider would make things much more fun to play with parameters. Additionally introducing color, or an interactive element users can play with could potentially be more captivating. For now, I am including the project with parameters of the shape I liked the most, but we can try other ones in class. I really liked making this project and I hope you like it too.

The presentation prompted a thoughtful examination of the nature of creativity in the digital era by examining the relationship between chance and creativity.  In particular, it resonated with me that randomness can foster creativity within the inflexible confines of code. It suggests that the “unintentional” can contain a new kind of intentionality, challenging the conventional narrative that art is solely a human endeavor. This counterintuitive notion begs the questions, “Is creativity a uniquely human trait, or can it emerge from the interaction between computational randomness and human intention?” I was prompted to reevaluate the artist’s function in the digital age by the talk. Rather than being the only creator, it’s possible that the artist is becoming more of a curator, arranging the circumstances in which art is produced through human-machine collaboration.

The conversation on using code-generated randomness to create unexpected and meaningful art struck a deep chord as well. It suggests a change in perspective from seeing art as a static representation to seeing it as a dynamic process where meaning is created via interaction and interpretation rather than being predetermined. This viewpoint is consistent with broader societal movements that prioritize experience over possession and procedure over product. It also raises difficult issues regarding authorship and authenticity in art. In the event that the “creator” consists of a collection of human-designed algorithms, how can we distinguish between the creator and the medium? Furthermore, how does this affect how we see art itself? In addition to providing insights, the talk created a forum for a more in-depth examination of the changing dynamics between people, art, and technology.