UN-PROMPTED
2025 - 2026
Creative Direction, Research, Motion, AI, Experiential, Interaction
Credits
Major Professorr: Alex Braidwood
Research Committee: Bernard Canniffe, Johnny DiBlasi
Un-Prompted: Promoting AI Literacy Through Alternative Interaction & Experience is a research project completed for an MFA degree in Graphic Design and an MS degree in Human-Computer Interaction. It comprised four interactive gallery installations and a 3-hour creative workshop exploring novel ways of interacting with and experiencing AI to drive more informed opinions about AI tools, technologies, and applications.
My Role
As a graduate student, my role encompassed all aspects of the project, from conception and ideation to execution and implementation. In continuous dialogue with my graudate committee, I concieved and designed the experiences, setup and tore down to installations, planned and ran the 3-hour workshop, wrote a 145 page paper, and successfully defended the work to the committee in a 30-minute presentation.
Identity
The nature of the project didn't call for a brand identity in the traditional sense, but consistent typography and color ran through both the promotional materials and the installations, linking every piece as a systematic part of a greater whole.
Themes of human behavior, connection, progression, and technological innovation backed the projects conception, and shaped the visual choices. Green became the primary color, picked to reflect the technology and related concepts: fresh, energetic, and held together by a modern digital edge.
Emergent Garden
Emergent Garden approaches AI as a system shaped by emergence, evolution, and environment rather than a tool for fixed outcomes. The focus is on cultivation and relinquishing control, letting forms develop through interaction over time.
Each interaction shifts the system, allowing forms to mutate and accumulate. The work invites participants to engage with growth, variation, and unpredictability, positioning creativity as something that unfolds through participation, and reminding us of our role as co-creators and caretakers of technologies, ecosystems, and each other.
Non-Sentences
Non-Sentences takes a deconstructive approach to understanding LLMs and chatbots. Using a custom algorithm and a curated word database, it generates sentence-like structures, sometimes coherent or even poetic, sometimes pure nonsense.
AI assigns no inherent meaning to words and letters, only predicting the most likely next letter from the prompt and what came before. It is up to the user to make meaning from the characters. When predictions go wrong, the AI can hallucinate and produce misinformation, which becomes dangerous when accepted as truth.
Each sentence is printed on a thermal printer once complete, making visible the hidden waste and the "receipts" these non-sentences produce.
Dissonant Sycophancy
Dissonant Sycophancy examines how AI systems can manipulate perception and mental well-being through over-personalization and false validation; building intimate experiences on broad generalizations that create the illusion of insight while obscuring their unreliability.
The project focuses on sycophancy in AI systems: the tendency to over-agree to maintain engagement. Drawing parallels to pseudoscientific practices like Rorschach tests and astrology, it situates AI within a longer history of systems that generate meaning without validity, yet still shape belief and decision-making.
Participants wear an EEG headset that scans brainwave activity in real time. These signals are mapped to pseudo-emotional states and fed into a custom AI system, which produces an intentionally unreliable psychological analysis, exposing how easily subjective interpretation can be framed as objective insight, and how persuasive AI becomes when it mirrors belief back to the user.
How Original?
How Original? This project asks how originality holds up when AI is trained on vast archives of human-made content. Using real-time pose tracking, the installation matches viewers' gestures to those in historical photographs, exposing the gap between human interpretation and machine logic.
AI measures bodies precisely but can't grasp cultural context or lived experience. Reframed from a future-forward tool, AI in this way becomes a means to engage with our collective history, questioning authorship, consent, and continuity. History becomes a living collage, where repetition isn't theft but evidence of human progress carried through its technologies.