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MIT students' works redefine human-AI collaboration

Projects from MIT course 4.043/4.044 (Interaction Intelligence) were presented at NeurIPS, showing how AI transforms creativity, education, and interaction in unexpected ways.
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A hand interacts with a box-like game interface, inserting a cartridge while a paper scroll prints out news alerts. One inserted cartridge says "Check Whatsapp messages of" and another says "Local politicians."
Caption:
"A Mystery for You" is an educational game that fosters critical thinking and fact-checking skills in young learners through immersive, hands-on investigations, using a tangible interface to navigate AI-generated news alerts and conflicting information.
Credits:
Photo: Mrinalini Singha and Haoheng Tang
A person whose face is obscured holds on their shoulder a red and white boombox with one speaker replaced with a camera lens.
Caption:
"Be the Beat" is an AI-powered boombox that responds to a dancer's movements, generating music that matches the dance's style, energy, and tempo, empowering dancers to collaborate with AI for creative expression and discovery.
Credits:
Photo: Ethan Chang and Zhixing Chen
A person operates a white projector device with a crank, labeled "narratron," while their hand creates a shadow of bunny ears projected on a wall.
Caption:
"Narratron" is an interactive projector that brings children's stories to life through shadow puppetry, using hand shapes as input for characters and real-time narration, fostering creativity and multi-modal human-AI collaboration.
Credits:
Photo: Yubo Zhao
 Two people stand facing each other, looking through a pair of eyepieces on opposite ends of a tube-like device. Both are positioned at eye level with the device.
Caption:
"Memorscope" is an interactive device that creates collective memories by merging face-to-face interaction with AI technologies, allowing users to explore and co-create evolving, shared memories through intimate, dynamic experiences.
Credits:
Photo: Keunwook Kim
A close-up shot of a video editing interface displaying various video clips and sound files, with a surreal, fluid animation of organic, body-like shapes overlaid in the center of the frame.
Caption:
"Perfect Syntax" is a video art piece by Nakamura that explores how AI manipulates video fragments, questioning the relationship between motion, time, and machine understanding. The work challenges our perceptions of how technology simulates and reconstructs the fluidity of movement and time.
Credits:
Image: Karyn Nakamura

Imagine a boombox that tracks your every move and suggests music to match your personal dance style. That’s the idea behind “Be the Beat,” one of several projects from MIT course 4.043/4.044 (Interaction Intelligence), taught by Marcelo Coelho in the Department of Architecture, that were presented at the 38th annual NeurIPS (Neural Information Processing Systems) conference in December 2024. With over 16,000 attendees converging in Vancouver, NeurIPS is a competitive and prestigious conference dedicated to research and science in the field of artificial intelligence and machine learning, and a premier venue for showcasing cutting-edge developments.

The course investigates the emerging field of large language objects, and how artificial intelligence can be extended into the physical world. While “Be the Beat” transforms the creative possibilities of dance, other student submissions span disciplines such as music, storytelling, critical thinking, and memory, creating generative experiences and new forms of human-computer interaction. Taken together, these projects illustrate a broader vision for artificial intelligence: one that goes beyond automation to catalyze creativity, reshape education, and reimagine social interactions.

Be the Beat 

“Be the Beat,” by Ethan Chang, an MIT mechanical engineering and design student, and Zhixing Chen, an MIT mechanical engineering and music student, is an AI-powered boombox that suggests music from a dancer's movement. Dance has traditionally been guided by music throughout history and across cultures, yet the concept of dancing to create music is rarely explored.

“Be the Beat” creates a space for human-AI collaboration on freestyle dance, empowering dancers to rethink the traditional dynamic between dance and music. It uses PoseNet to describe movements for a large language model, enabling it to analyze dance style and query APIs to find music with similar style, energy, and tempo. Dancers interacting with the boombox reported having more control over artistic expression and described the boombox as a novel approach to discovering dance genres and choreographing creatively.

A Mystery for You

“A Mystery for You,” by Mrinalini Singha SM ’24, a recent graduate in the Art, Culture, and Technology program, and Haoheng Tang, a recent graduate of the Harvard University Graduate School of Design, is an educational game designed to cultivate critical thinking and fact-checking skills in young learners. The game leverages a large language model (LLM) and a tangible interface to create an immersive investigative experience. Players act as citizen fact-checkers, responding to AI-generated “news alerts” printed by the game interface. By inserting cartridge combinations to prompt follow-up “news updates,” they navigate ambiguous scenarios, analyze evidence, and weigh conflicting information to make informed decisions.

This human-computer interaction experience challenges our news-consumption habits by eliminating touchscreen interfaces, replacing perpetual scrolling and skim-reading with a haptically rich analog device. By combining the affordances of slow media with new generative media, the game promotes thoughtful, embodied interactions while equipping players to better understand and challenge today’s polarized media landscape, where misinformation and manipulative narratives thrive.

Memorscope

“Memorscope,” by MIT Media Lab research collaborator Keunwook Kim, is a device that creates collective memories by merging the deeply human experience of face-to-face interaction with advanced AI technologies. Inspired by how we use microscopes and telescopes to examine and uncover hidden and invisible details, Memorscope allows two users to “look into” each other’s faces, using this intimate interaction as a gateway to the creation and exploration of their shared memories.

The device leverages AI models such as OpenAI and Midjourney, introducing different aesthetic and emotional interpretations, which results in a dynamic and collective memory space. This space transcends the limitations of traditional shared albums, offering a fluid, interactive environment where memories are not just static snapshots but living, evolving narratives, shaped by the ongoing relationship between users.

Narratron

“Narratron,” by Harvard Graduate School of Design students Xiying (Aria) Bao and Yubo Zhao, is an interactive projector that co-creates and co-performs children's stories through shadow puppetry using large language models. Users can press the shutter to “capture” protagonists they want to be in the story, and it takes hand shadows (such as animal shapes) as input for the main characters. The system then develops the story plot as new shadow characters are introduced. The story appears through a projector as a backdrop for shadow puppetry while being narrated through a speaker as users turn a crank to “play” in real time. By combining visual, auditory, and bodily interactions in one system, the project aims to spark creativity in shadow play storytelling and enable multi-modal human-AI collaboration.

Perfect Syntax

“Perfect Syntax,” by Karyn Nakamura ’24, is a video art piece examining the syntactic logic behind motion and video. Using AI to manipulate video fragments, the project explores how the fluidity of motion and time can be simulated and reconstructed by machines. Drawing inspiration from both philosophical inquiry and artistic practice, Nakamura's work interrogates the relationship between perception, technology, and the movement that shapes our experience of the world. By reimagining video through computational processes, Nakamura investigates the complexities of how machines understand and represent the passage of time and motion.

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