Culturally Relevant Making

Prompt Battle 1 — Our first generative AI prompt battle.

This summer we invited 13 Cambridge, MA youth from diverse backgrounds to explore and learn the fundamentals of generative artificial intelligence or GenAI. This experience created space for youth to bring their identities and interests into creative computing in ways that allows them to see themselves in GenAI. They worked together and addressed questions such as: What is generative AI and where do we see it in the art world? How does working with AI tools affect creativity? Can AI teach us how to be more creative? What are the benefits and harms of GenAI?

This in-person, pre-college course came about from Lesley STEAM’s collaboration with Cambridge Youth Programs. CYP staff recruited the students and youth counselors who assisted our team. Every day for one week, from 9:30am – 5:30pm, CYP youth (students) met at Lesley University’s College of Art and Design or LA+D. The youth earned 2 Lesley college credits and received stipends for their participation. The skills they learned can be applied to other classes they can take such as art and computer science. Students can also explore GenAI applications for entrepreneurship opportunities.

face sensing AI in scratch — Learning how to use face sensing AI in Scratch.

LSTEAM/CYP facilitated activities such as face-sensing AI using the Scratch programming language, GenAI design thinking, and participating in events using text, image and music GenAI tools. Class activities culminated in capstone “project pitches” and presentations. Main objectives of the class included:

Learning the fundamentals of generative artificial intelligence or GenAI.
Exploring design thinking for GenAI (empathize, define, ideate, prototype, test)
Referencing, applying and combining artistic styles to generate new images, text, and music.
Explore bias/anti-bias, copyright and intellectual property issues in GenAI.

Joy Buolamwini talks about racial bias in AI.

We began the course by learning about GenAI that uses machine learning models to create new content that includes images, text, music and video/animation. A machine learning model is a program that finds patterns, or makes decisions from a previously unseen dataset. Facial recognition—identifying and measuring facial features in an image—is one of the more obvious applications of machine learning. Students watched and discussed the film Coded Bias that shows how many facial recognition technologies do not accurately detect certain faces such as darker-skinned women.

GenAI Art Tools & Daily Challenges

Throughout the course, students had access to and used several GenAI art tools including Adobe Firefly, Deep Dream Generator, ChatGPT, Udio, and PoseNet. Each day focused on a specific GenAI art tool, which uses a large language model or LLM that is used to train a neural network on massive amounts of data. We looked at several videos that explained what AI art is and how it came to be such as this one: AI Art, Explained. Daily challenges provided students with tasks to accomplish. Each morning we opened with a cypher (circle) to give students a chance to share their expectations, interests, and concerns. We also closed with a cypher to share our accomplishments and challenges for the day.

A cypher doesn’t need a stage or designated area in which to take place, they can, and do, form anywhere; at parties, in clubs, outside on the concrete, in train stations, on a beach, in someone’s living room. Spontaneous in its forming, all that [performers] need is space and they will cypher. —Emmanuel Adelekun, Red Bull

Each day students were tasked to read articles such as a blog post written by Nettrice about “BBL Drizzy”, a song that recently made hip-hop history by accidentally sampling an AI-generated song written by @kingwillonius who was featured in WIRED magazine. Next, students learned how to use Udio to create their own AI-generated songs.

Visual Storytelling 3.0

Understanding language is very important when using generative AI tools. Students explored GenAI for visual storytelling, or the art of communicating messages, emotions, narratives and information in a way which reaches viewers at a deep and lasting level. Students learned how to write prompts in ChatGPT to create text for visual metaphors that helped them translate their ideas into more understandable forms. They also used Adobe Firefly and other image generation AI tools that are based on large language models or LLMs to help refine and steer their ideas towards desired results.

In order to generate compelling text and images students learned how to engineer prompts. Prompt engineering is a growing field that involves writing text that can be interpreted and understood by a generative AI model. Students learned how to add “boosters” or modifier words to their prompts to create more unique content. They also practiced this skill during prompt battles and when exploring different GenAI tools.

Prompt Battles

Many of the students were very interested in honing their prompt engineering skills, so we engaged them in prompt battles, or events in which people compete against each other using text-to-image GenAI tools to create images based on text prompts. Our events, which were very popular with the CYP youth, allowed the participants to show off their prompt skills, and the audience (peers) chose the winners from each head-to-head match. The person who won the most matches by the end of each battle won a prize (but everyone got something).

prompt battle slide — Example of a head-to-head prompt battle

We held two prompt battles, one on Tuesday afternoon and another on Thursday afternoon. We used these events to measure how much progress the participants were making with their prompt engineering. We were looking for legibility, breadth, scope, and clarity in their written prompts. Students learned that, above and beyond the written prompts, the participants with the best modifiers or “boosters” often won their matches. People can’t simply rely on the GenAI tool alone.

Coding with ML5.js

Some of the CYP youth were very interested in coding beyond Scratch/face sensing, so we explored ml5.js, an open source library with a goal of making machine learning approachable for artists, creative coders, and students. The “ml” in ml5.js stands for machine learning, a subset of artificial intelligence, and “js” stands for Javascript, which is a programming language and core technology of the Web, alongside HTML and CSS. A key feature of ml5.js is its ability to run pre-trained machine learning models for web-based interaction. These models can classify images, identify body poses, recognize facial landmarks, hand positions, and more. Students were given an option to use these models as they were, or as a starting point for further learning along with ml5.js’s neural network module which enables training their own models.

carnival ai movement app — Movement Painting with the Carnival AI app.

In addition to learning how to code with mL5.js, students learned how p5.js, a JavaScript library for creative coding, is used to make interactive visuals in web browsers. They used the PoseNet Sketchbook and Carnival AI app to explore pose estimation or PoseNet, which estimates the 2D position or spatial location of human body key points from visuals such as images and videos. The Carnival AI app celebrates and engages movement and dance in and from Black and Caribbean communities and creates visual art. The youth could also use p5.js to code using PoseNet.

AI Design Thinking & Final Pitch Projects

To help students brainstorm their own GenAI projects we used AI Ideation Cards created with input from the AIxDesign community. These cards help designers and others leverage AI capabilities, including 7 categories with questions (prompts), definitions, and example use cases. After coming up with a topic, each student was instructed to select a category that best matched their idea. Students imagined AI capabilities as superpowers and thought about how GenAI could help solve their challenges in new, unique, or better ways. Students were given Post-It notes, worksheets, and index cards to work out their ideas. They also used Gen AI tools to visualize and plan their final projects.

context awareness scenario — Context Awareness AI scenario card and example project.

Student's final pitch — Student presents final project pitch.

Near the end of the week, students worked individually or in groups on their final pitches. Examples include healthcare: providing a comprehensive pain assessment that enhances diagnostic accuracy and personalized treatment plans; food: using personality quizzes and surveys to provide appropriate recipes; and music: giving everyone a chance to share their voices with the world using a high-quality recording tool. Students presented their project pitches on the last day.

Please Note: This work has been made possible through collaboration with Cambridge Youth Programs and Lesley University’s College of Art & Design’s PreCollege Program and the generous support of the STAR Initiative.

Setting up the Paintbrush Bot — PHOTO: Setting up a paintbrush bot (with LSTEAM director Sue Cusack)

This summer we invited 12 Somerville High School (SHS) students from diverse backgrounds to explore the combination of three-dimensional art, machine learning artificial intelligence (AI), and robotics. The in-person course built upon an existing collaboration with SHS teachers Karen Leary (math) and Laura Peters (robotics) and Lesley STEAM. Every day for two weeks SHS students met the SHS/LSTEAM at Lesley University’s College of Art and Design or LA+D. Like the 2021 course, students earned 4 Lesley college credits that were matched by 2.5 math or 2.5 art credits. The skills they learned can be applied to other classes they can take during the school year such as math, art, robotics, and computer science.

SHS/LSTEAM facilitated activities such as 3D art & design, face-sensing AI using the Scratch programming language, and robotics. Class activities culminated in a capstone “moving 3D sculpture” project. The main objectives of the class were for students to:

Show an understanding of 3D art & design using craft material & art supplies.
Demonstrate knowledge of robotics by building robots that alter the environment through art.
Demonstrate their knowledge of machine learning AI, especially through face-sensing in Scratch.
Show an understanding of the iterative design process by rebuilding/repurposing their robot for new ends.

We began the course by learning about 3D art & design elements and principles. Students learned about 3D artists such as Lee Bontecou, Heather Hart, Olalekan Jeyifous, and Sanford Biggers. Next, students presented their research, especially which elements/principles they identified in their chosen artist’s works. Later, they learned about Joy Buolamwini, a coder who uses art and research to illuminate the social implications of artificial intelligence.

Diverse 3D artists — PHOTO: Lee Bontecou, Heather Hart, Sanford Biggers & Olalekan Jeyifous

Study finds gender and skin-type bias in commercial artificial-intelligence systems | MIT News | Massachusetts Institute of Technology — PHOTO: Joy Buolamwini via MIT News

For the first week, students explored 3D art & design (see above) in the morning. During the afternoons, with support from SHS/LSTEAM and Lesley A+D alum Bo Liang, students explored Scratch block coding, robotics, and digital fabrication such as 3D printing and laser cutting. They created kinetic sculptures that addressed a social justice issue or movement that is critical to them or their community. Then, they built robots using an entry-level kit that requires no soldering. They controlled their robots using face sensing AI. Face Sensing in Scratch let’s users create projects that respond to their eyes, nose, and other parts of their face. For the course, students used face-sensing to control their 3D art robots.

#movement kinetic sculpture — PHOTO: #movement Kinetic Sculpture on climate change

Students were given a design brief, which outlines capstone design deliverables and constraints. In design cyphers (also called circles or breakouts) the students brainstormed themes, then used sketches, web search images, notes, and found objects to visualize and present their ideas. The concept of the cypher comes from hip-hop culture:

To cypher is to rap, break, beatbox tightly together in a circle where each person just might get a moment in the spotlight. To cypher is to borrow and to lend, to playfully freewheel through whilst taking an exacting care for each word and carefully considering all the sounds, meanings, and interpretations. It is to fight back, to borrow, to steal, to represent, and to collaborate, whilst suddenly—surprisingly—at times aggressively claiming your own voice, your own right to speak. —Paul Watkins and Rebecca Caines

Working in cyphers, or smaller teams gave students the space to explore self-concept, which refers to the ways young people perceive their behaviors, abilities, and unique characteristics. Students learned how to use Adobe Illustrator for 2D design projects and Fusion 360 for 3D modeling. In the LA+D fab lab they learned how to 3D print and laser cut objects.

PHOTO: Working in the LA+D fab lab with Bo Laing

Later during the first week students worked with their peers and SHS/LSTEAM to synthesize what they learned in 3D art & design with their A.I. robot builds. This was done through prototyping to quickly iterate upon their initial designs. They had plenty of open work time that was dedicated to this activity and they participated in a collaborative peer review. The latter combines culturally relevant pedagogy and design thinking. Culturally relevant instruction modifies standard curricula to center students’ identity development, cultures, and participation. Design thinking helps students understand design constraints, challenge assumptions, redefine problems and create solutions to prototype and test.

Scaling up and building a prototype — PHOTO: Building an art bot PHOTO: Peer review preparation

Final capstone construction — PHOTO: Building an art bot PHOTO: Peer review preparation

The collaborative peer review process consisted of gallery walks, with each group providing constructive critiques for peer projects. Individually and in teams, they answered worksheet questions about the projects they saw. Students, in their groups, were given enough time to read and discuss their peers’ feedback. They were given time to respond to peer feedback through iteration on their initial prototypes. Students participated in peer reviews at the end of the first week and as a final review/capstone presentation on the next to last day of the course.

Working on capstone projects — PHOTO: Students work on their capstone projects

PHOTO: Final capstone project presentation

Examples of the students’ final 3D art bots include a paintbrush art bot, a “happy-faced Bobox”, a drawing giraffe, a spider clock, a fashionable head-turning robot, and and a moving sculpture modeled from Star War’s original R2D2 robot (see image below). The latter was shared with Ahmed Best who played the character Jar Jar Binks who appears throughout the Star Wars prequel trilogy and recently a Jedi in The Mandalorian.

Oliver's R2D2 & Ahmed Best — PHOTOS: R2D2 moving sculpture (left) & Ahmed Best (right)

To learn more, check out some of the students’ final capstone projects (3D art bots):

This work has been made possible through collaboration with Somerville High School and Lesley University’s College of Art & Design’s PreCollege Program and the generous support of SomerPromise at the City of Somerville and the Biogen Foundation’s STAR Initiative.

Category: Culturally Relevant Making

2024 Summer Pre-College Creative AI & Design Course