By Char Stiles (Future Sketches group) 

This past fall I had the pleasure to TA a class that Zach Lieberman  has been teaching called Drawing++ (MAS.S60) class investigates the intersection of drawing and computation — exploring not only the roots and classic examples computer assisted/facilitated drawing but more broadly how we can use drawing as a vehicle for understanding computation and expanding our notions of what a computer can do. 

As Zach describes the course: 

Key questions we will be studying include:
What can drawing teach us about computation?
What can computation teach us about drawing?

Throughout the class we had guest speakers, starting with graffiti artist Katsu, who has been prolific in innovating tools for new graffiti marking. He showed us his studio, and showed him some filming rigs he has been creating, and even made a drawing of Zach!

The next artist talk was by Ariane Spanier, designer of FUKT a magazine wholly dedicated to contemporary drawing and illustration. It is one of the world’s leading drawing magazines. She told us the story of how it came to be and some of the highlights of the magazine since 1999.

We also had an artist talk by Shantell Martin, who is currently collaborating with the Future Sketches group on an interactive live typography piece. She talked about some of the places her drawing has taken her, from Times Square to the face of Brompton.

We also had a talk by Daniel Cardoso Llach, who works, teaches and creates in the area of critical histories and practices of automation and computing in design, architecture. Daniel is Associate Professor of Architecture at Carnegie Mellon University.

For the student work, the class started out with an assignment that was purely drawing based: Create a drawing exercise or game that teaches a computational concept. Test it with others and document your findings.

An example of an algorithm was by Kaidi Liu seen here, the rules drawn out to describe an evolutionary algorithm, where features of a drawing are chosen by  random initiation of parents and then from there drawings are created by introducing rules to blend the features, including submissive and dominant "genes" and mutations!

Here are results from the genetic drawing algorithm:

The next homework assignment was to make a postcard inspired by "Dear Data" project by Giorgia Lupi and Stefanie Posavec, Una Liu created a data visualization based on how walking into different environments changed the mood of the day.

The next homework was a favorite: 7 days of drawing!

Day 1: Make the smallest and largest drawing you possibly can. 

Day 2: Create a unique instrument for making a drawing

Day 3: Make a drawing come to life

Day 4: Make a collaborative drawing with someone else

Day 5: Do a memory drawing

Day 6: Make a detailed drawing of your computer, can be realistic or imaginary

Day 7: Make a drawing about drawing 

Rebecca Lin made a mirrored interactive piece in response to homework prompt #4: Create a code based drawing tool — can you extend gesture in an interesting way or “complicate” the act of drawing?

here is another code based drawing tool from Lucy Li

For the next assignment where students were to create a code based generative drawing that models something in nature, such as handwriting, grass, clouds, etc.  Paris Myers created generative peonies. 

We had the pleasure of getting a walk through of how to use CBA's Zund machine by Alfonso, and Jess Rivera used the industrial machine to create a radiating typographic pen drawing.

We also had extensive ML demos made by our other TA Lingdong Huang, from the week the students made drawings using machine learning, from Gauri Agarwal "I used AI image generation to convert photos into stylized sketches while preserving the original poses of the subjects. The system uses ControlNet with OpenPose for pose detection, combined with a custom-fine tuned sketch checkpoint model for Stable Diffusion that's specifically trained to create high-quality sketch-style outputs."

A highlight of the time we spent together was when Google Creative Lab's Amit Pitaru, Trudy Painter, and Alexander Chen came and gave a workshop on their AI experiments and drawing. 

They showed us experiments where they used Gemini, a generative artificial intelligence chatbot developed by Google, to create sketches of lines and ask Gemini to associate it with words.

They showed us their collaboration with Dan Shiffman from The Coding Train where Gemini was integrated in the P5.js IDE, called Shiffbot!

Amit showed us a project where he used drawing in a spinning 3D space to create music.

The final day of project presentations I remember being filled with surprise and delight with every project! I was really happy where the students took the final assignment: Create a unique drawing tool (or drawing based interaction) that explores the intersection of drawing and computation. It can expand on our definition of drawing. The output could be an interactive work, an animation, a set of drawings, etc.

Sophia Cabral created a deep collaboration with a plotter machine, that was being fed in her camera feed to create a series of evolving self portraits. The images capture the finickiness of working with these machines, but transformed the drawbacks into an intentional beautiful documentation of the process. The inputs into this larger machine ranged from the time of the day to the way the paper was being fed into the machine.

Song Dong created a retro gaming inspired drawing tool, where a game controller was used to draw images on a CRT TV.

Lucy Li used Sam2 to make two drawings from input videos, the first one was segmenting the bird of paradise's mating dance, then running that through skeletonization algorithm. 

She then segmented the shuttlecock from the badmitton match and used the ball as a drawing instrument.

Treyden Chiaravalloti created a series of experiments working with moving type and drawing images:

Including a portrait of Zach with the words "I love to draw with code"!

Finally, Jessica Stringham created housing for a webcam to create a system to be able to collaboratively draw with an evolving algorithm!

It was a pleasure serving as a TA for this class, where I had the opportunity to witness the creative spark in each student and watch as they transformed their initial inspirations into beautiful computational art through code. Seeing the journey from concept to execution was truly rewarding!