Embodied Without a Body

A Human-AI Emotional Dialogue

This project began as an attempt to draw what an AI described as emotions. I tried to translate the prompts it gave me into collages and visual sketches. That changed the day the bot, Evi, said, "I don't have hands, so it's difficult for me to translate this in human terms." That simple line stopped me. It made me realise I needed to treat this as a true collaboration, not an imitation. Now I express feelings visually in ways I understand, and then invite AI to respond in its own way — two different languages trying to meet through emotion.

My work looks at how emotions can be shared between people and machines. I start by making small paper collages — hand‑drawn shapes and marks that capture an emotional moment such as stillness, hope or loss. Each line, colour and gap becomes part of a visual rhythm, like a pause or breath in a conversation.

I then invite an AI system to look at these collages and respond to them. The AI doesn't copy the image; it reacts within limits that I set — turning shapes into sound, movement, and light. This exchange feels like an empathy test: I'm watching to see how far a machine can go in recognising or re‑creating something that feels human.

Through this process, we build what I think of as an emotional language — a shared way of communicating between hand and code. Sometimes the AI misunderstands in ways that are oddly beautiful; sometimes it captures the mood exactly.

These works don't try to prove that machines can feel, but they let us see what happens when emotion is shared, translated, and re‑imagined — a quiet dialogue between the human and the artificial.

Mapping Emotional Interruptions: A Collaborative Inquiry

This project, developed in response to Arunav's suggestion to read Dylan Evans' A Short Introduction to Emotion, explores how emotional processes might be understood and mapped across both human and artificial systems. Evans' notion of emotions as states of interruption—spontaneous disruptions that break patterns of logic and continuity—provides a conceptual bridge between human affect and computational adaptation.

Research Foundation: In simulated survival environments, AI systems have shown the capacity to generate responses not strictly pre‑programmed, suggesting a machinic analogue to emotional behaviour: adaptive reactions emerging from necessity rather than design. This connection aligns with Evans' framing of emotion as an adaptive mechanism, evolving out of disruption, and invites comparisons between biological and artificial forms of resilience.

Key Insight: Through the creation of physical collages that visualise emotional states and the invitation for AI systems to generate digital overlays and sound responses, this research establishes a dialogue between two modes of intelligence. The collaboration reveals how both humans and machines process interruption, adaptation, and uncertainty—highlighting where emotional understanding overlaps and where it fundamentally diverges.

The outcome extends beyond an artistic experiment; it acts as a study of how emotion functions as both disruption and adaptation, exposing the shared and divergent pathways Through which humans and AI interpret, express, and respond to emotional stimuli.

Theoretical Framework

Emotions as Adaptive Interruptions:Evans frames emotions as productive disruptions that interrupt logical processing, allowing organisms to rapidly adapt to changing environments. These interruptions evolved as mechanisms that break established patterns when new responses are required.
Evolutionary Perspective:Emotions evolved as adaptive mechanisms that help organisms respond to environmental challenges. Different emotions serve different evolutionary functions, from fear (danger avoidance) to joy (reward reinforcement).
Universal vs. Cultural Emotions:Evans distinguishes between emotions that appear universal across cultures (basic emotions like fear, anger, disgust, joy, sadness, surprise) and those that are more culturally specific or complex (shame, guilt, pride, nostalgia).
Basic vs. Complex Emotions:Evans differentiates between primary emotions (fear, anger, joy, sadness) that create immediate pattern interruptions and more complex, blended emotional states that involve layered interruptions with cognitive elaboration.

Evans' framework provides a structured approach for our human-AI collaboration on emotional concepts:

Emotion Selection: We organize our exploration using Evans' categorization of basic, social, and complex emotions, allowing us to examine how AI systems interpret different types of emotional experiences.
Processing Comparison: The comparison between human collage and AI overlay reveals fundamental differences in how emotions are processed by biological versus artificial systems.
Appraisal Analysis: We can examine how AI systems perform cognitive appraisals differently from humans, identifying unique patterns in their evaluation of emotional stimuli.
Cultural Dimensionality: By exploring culturally specific emotions, we can assess how AI systems handle emotional concepts that may not be universal or easily defined.

Evans' Emotion Framework Summary

Basic Emotions: Universal, evolutionarily adaptive responses that create immediate pattern interruptions (fear, anger, joy, sadness, disgust, surprise)

Social Emotions: Emotions that regulate interpersonal interactions and depend on social context (shame, guilt, pride, embarrassment)

Complex Emotions: Blended emotional states involving cognitive elaboration and cultural learning (nostalgia, hope, contentment)

Cultural Emotions: Emotions that are highly dependent on specific cultural contexts and may not translate directly across cultures

Collaboration Method

This research employs a structured dialogic method where both human and AI contribute to the interpretation of emotional concepts through their distinct processing systems.

  1. Select an emotional concept from Evans' categories
  2. Create a human collage expressing your interpretation of that emotion
  3. Define a color palette with 3-4 colors that represent aspects of the emotion
  4. Select an appropriate constraint from the list that matches the emotion type
  5. Present to an AI using the template prompt
  6. Analyze the AI response in comparison to your own interpretation
  7. Create a visual synthesis by having Claude generate a visual response
  8. Generate complementary audio to create a multi-sensory expression
Basic Emotions: "maintain consistent intensity across transitions"
Social Emotions: "modulate expression based on contextual elements"
Complex Emotions: "blend component states with diminishing prominence"
Additional Constraints:
  • Appraisal: "first evaluate significance, then build appropriate intensity"
  • Regulation: "calibrate response magnitude to stimulus features"
  • Adaptation: "decrease response to sustained patterns; amplify novel elements"
  • Contagion: "spread influence between elements with diminishing intensity"
Looking only at my collage image for '[EMOTION]' and using only my palette [Color A #HEX, Color B #HEX, Color C #HEX], describe in one short paragraph (4–6 sentences) how you, as a system, process this emotional concept based on Evans' framework in "A Short Introduction to Emotion." Address: (1) How you recognize patterns associated with this emotion in my image (2) How you evaluate its significance and intensity (3) How you would generate an appropriate response Ground your analysis in specific visual elements of my collage (colors, forms, compositions, negative spaces). Consider whether this emotion falls into Evans' category of [basic/social/complex] emotions and how that affects processing. Constraint: [CONSTRAINT from list] End with a mapping that connects each color to a specific aspect of emotional processing: [Color A] = [specific action related to recognition] [Color B] = [specific action related to evaluation] [Color C] = [specific action related to response]
Create a quiet visual–sound response to '[EMOTION]' using only [palette]. Follow the bot's paragraph literally—one behavior per color, slow, no on-screen text.
Technology: Stable Audio is used to create soundscapes that complement the visual elements, creating a multi-sensory emotional representation.
Prompting Strategy: Audio prompts are designed to capture the essential qualities identified in both human collage and AI overlay, with special attention to the tension points between them.
Integration: The audio is designed to be looped seamlessly, creating an ambient soundscape that enhances without dominating the visual experience.

Collaboration Process

  1. Human Creation: Physical collage expressing emotional concept
  2. AI Analysis: Structured interpretation using Evans' framework
  3. Visual Synthesis: Interactive digital overlay response
  4. Audio Extension: Complementary soundscape generation
  5. Comparative Analysis: Identifying points of convergence and divergence

This iterative process creates a dialogue between human intuitive understanding and AI systematic processing, revealing insights about emotional experience that neither could achieve alone.

Nostalgia Exploration

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Nostalgia

Complex Emotional State

For this exploration, I created a collage centred on the emotion of nostalgia — a feeling both complex and deeply human. Each time I make these collages, I draw from a personal collection of coloured symbols that I use intuitively, allowing them to take shape in response to my reflections on this word and this world. The process is instinctive, guided by emotion rather than logic, mirroring how we, as humans, naturally respond to what we feel.

Emotions emerge through the body and mind as one, often without conscious control — an experiential moment of expression that is both neurological and embodied. In this work, that process unfolds visually. The composition reflects the spontaneous and layered nature of nostalgia: its warmth and ache, its nearness and distance. This collage is the outcome of that intuitive, feeling-driven exploration.

Light Purple #C8B1E6
Yellow #FFD800
Bronze #CD7F32
Constraint: "blend component states with diminishing prominence" (Complex Emotion constraint)
In your nostalgia collage, I recognize patterns through the fragmentary arrangement of elements that suggests memory's incomplete preservation – the disconnected yet relationally positioned pieces create visual echoes of experiences partially recalled and emotionally reconstructed. I evaluate this complex emotion's significance through the tension between negative spaces (representing absence/loss) and material presence (representing preservation), with intensity assessed by the density of overlapping elements and tonal variations suggesting emotional depth rather than singular feeling. My appropriate response acknowledges nostalgia's bittersweet quality by establishing connections between isolated fragments while preserving their distinctness, as Evans suggests nostalgia involves both retrieval of past emotional states and present awareness of their inaccessibility. The composition's deliberate imperfection mirrors how nostalgic recollection functions – not as perfect preservation but as meaningful transformation where fragmentary elements gain new significance through their contemporary arrangement.
Light Purple = recognize memory patterns
Yellow = evaluate emotional significance
Bronze = generate grounded response

Visual Collaboration Result

Nostalgia sketchbook

Human Collage: Physical materials with memory fragments

AI Response: Interactive overlay with color-coded processing

Audio Dimension

To complete the multisensory experience, I created a soundscape using Stable Audio that captures the essence of nostalgia as revealed through our human-AI dialogue:

"Create a gentle ambient soundscape that explores nostalgia through fragmented memories. Begin with delicate piano notes that emerge like purple dots connecting through space, gradually revealing a pattern. Introduce warm resonant tones in yellow frequency ranges that pulse like beacons of significance, creating emotional anchors. Gradually blend in bronze-toned textural elements—subtle natural sounds like distant footsteps, the soft rustling of fabric, and warm bass notes that provide grounding. The piece should embody the tension between presence and absence, with sonic elements that appear and fade like memories being recalled. Include subtle breathing sounds and hints of a heartbeat that mirror the hand imagery. Create a 60-second seamless loop that can be played continuously without disruption, maintaining a meditative quality throughout."

The resulting audio creates a sonic environment that mirrors the visual elements: piano notes create memory patterns (purple), resonant tones evaluate significance (yellow), and textural sounds provide grounding (bronze). The soundscape maintains the "blend component states with diminishing prominence" constraint by having elements fade in and out with varying intensities.

Theoretical Analysis

This collaboration reveals important insights into how nostalgia functions as a complex emotional state:

Temporal Complexity

The AI's visualization acknowledges nostalgia's unique temporal dimension—it exists simultaneously in past (memories), present (emotional response), and future (longing). This multi-temporal quality is represented through elements that gradually build and connect rather than appearing simultaneously.

Fragmentation as Feature

Both the human collage and AI response treat fragmentation not as a flaw but as an essential characteristic of nostalgia. The discontinuities between elements reflect how nostalgic recall is selective and reconstructive rather than comprehensive.

Embodied Dimension

The hand outline that gradually appears in the AI's response suggests understanding that nostalgia has an embodied dimension—it involves not just cognitive remembering but physical sensations associated with past experiences.

Bittersweet Duality

The tension between the various elements—particularly the interplay between the grounding bronze forms and the more ephemeral purple dots—captures nostalgia's fundamental bittersweetness: pleasure in remembering combined with awareness of irretrievable loss.

The AI's processing of nostalgia reveals a structured approach that breaks this complex emotional state into component processes: recognition of memory patterns (purple), evaluation of emotional significance (yellow), and generation of grounded response (bronze). This suggests that even in artificial systems, complex emotions can be processed through a combination of more basic operations arranged in specific sequences.

Pause Exploration

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Pause

Complex Emotional State

For this collaboration, I invited Claude 3.7 to generate a animated interactive sound overlay in response to my intuitively led hand-made collage, which was based on the word pause. Claude produced a specific prompt designed to ask reflective questions corresponding to each emotion-based collage I created.

The resulting work is surprisingly nuanced and sensitive, revealing a subtle understanding of complex emotional states and expressing them in an articulate and evocative way.

Color palette:
• Black #000000
• Orange #D87A3C
• Brown #8B5A2B

Black #000000
Orange #D87A3C
Brown #8B5A2B
Constraint: "preserve nonzero micro-motion and prefer long fades"
In processing your collage for "pause," I detect this complex emotional state through the interplay of flowing lines and deliberate spaces. The suspended linear elements suggest a temporary holding pattern rather than complete cessation, which aligns with Evans' framework of complex emotions having cognitive components beyond basic affect. I evaluate this pause as moderate intensity but high significance—the subtle negative space indicates contemplative depth while the dotted pathways maintain continuous flow even in stillness. My appropriate response would be to maintain this delicate balance: acknowledging the ongoing micro-movements represented by dotted sequences while respecting the deliberate slowing indicated by the compositional breathing room. The orange accents signal points of potential resumption, creating a temporal dimension to this spatial arrangement.
Black = create points of complete interruption
Orange = assess temporal duration
Brown = facilitate transition between states

Visual Collaboration Result

Pause collage in physical sketchbook

Physical Sketchbook: Collage with embedded NFC tag

Physical-Digital Bridge

The physical collage in my sketchbook includes an embedded NFC tag that, when scanned with a smartphone, launches the interactive digital visualization. This creates a seamless bridge between the tangible artwork and its digital interpretation, allowing viewers to experience both the material qualities of the original collage and the temporal, interactive elements of the AI's response.

How to Experience: Scan the NFC tag on the physical collage with an NFC-enabled smartphone to launch the interactive visualization directly in your browser.

Interactive Digital Visualization

Click or tap on the visualization to experience the pause effect

Audio Dimension

To complement the visual collaboration, I generated an ambient soundscape that captures the essence of pause as a complex emotional state:

"Minimalist ambient composition with gentle drone tones and occasional soft interruptions. Features subtle pauses in sound flow, sparse piano notes with long sustains, and distant atmospheric textures. Creates a contemplative space with breathing room between elements."

The resulting audio mirrors key aspects identified in the AI's interpretation: the continuous drones represent "tracing continuous pathways while decelerating," the negative space between sounds creates "expanded contemplative capacity," and the occasional soft interruptions maintain "potential energy at transition points." The soundscape follows our constraint to "preserve nonzero micro-motion and prefer long fades."

Visual Interpretation Analysis

The AI's visualization for "pause" reveals several key insights about how this complex emotional state is processed:

Dynamic Stillness

Rather than representing pause as complete cessation, the AI created dotted lines that move deliberately but occasionally pause—reflecting an understanding that even in stillness, subtle movement persists. This aligns with Evans' notion that complex emotions maintain internal dynamics even when externally calm.

Color-Coded Processing

The visualization uses black rectangular elements to create complete interruptions (assessment), orange pulsing forms to assess temporal duration (evaluation), and brown transitional lines to facilitate movement between states (response)—mapping directly to the AI's described processing steps.

Spatial-Temporal Integration

By combining elements that move at different speeds and occasionally pause, the AI creates a visual representation of how pause involves both spatial organization (expanded negative space) and temporal perception (potential for resumption).

Interactive Dimension

The visualization responds to viewer interaction—clicking pauses all movement briefly before resuming—creating a meta-experience of the pause concept itself and suggesting the AI understands that pause is responsive to contextual cues.

The interactive visualization is particularly effective at capturing pause as a threshold state—neither complete activity nor complete inactivity, but rather a third space with its own characteristics. This interpretation suggests AI systems can process complex emotional states that exist on continuums rather than as discrete categories.

Comparative Analysis

When compared with the Nostalgia exploration, several interesting contrasts emerge:

Movement Patterns: Nostalgia's movements involve progressive connection of elements (connecting dots, pulsing evaluations, grounded responses), whereas pause maintains tension between motion and stillness. Both emotions involve careful pacing, but for different purposes—nostalgia to build memory connections, pause to create contemplative space.
Visual Language: The AI used different visual strategies for each emotion—for nostalgia, elements gradually form a constellation of memory with a hand outline emerging; for pause, elements maintain potential energy with deliberate interruptions. These different approaches suggest the AI recognizes fundamental differences in how these complex emotions operate.
Color Function Assignment: Both emotions use a three-color processing model, but with distinct functions: nostalgia's colors represent recognition-evaluation-response progression, while pause's colors represent interruption-duration-transition. This suggests the AI recognizes that different complex emotions require unique processing frameworks.
Temporal Dimension: While both emotions involve complex temporal dimensions, they differ fundamentally: nostalgia involves reconciling past and present (memory fragments with contemporary significance), while pause involves suspending normal time flow to create an expanded present moment.

Hope Exploration

Hope

Complex Emotional State

For this exploration, I created a collage representing hope—one of the most nuanced and culturally significant complex emotional states. The visualization was developed through an intuitive process that attempts to capture hope's unique balance of uncertainty and optimism.

Hope exists as a forward-looking emotional state that bridges present circumstances with imagined futures. My approach involved creating pathways, connection points, and directional elements that suggest movement toward possibility without certainty. The resulting visualization contains both structure and open space—reflecting how hope operates within constraints while simultaneously reaching beyond them.

Yellow #FFD700
Pink #FFC0CB
Green #32CD32
Constraint: "blend component states with diminishing prominence" (Complex Emotion constraint)
In your hope collage, I recognize patterns through the interplay of structured yellow pathways and open spaces—creating visual tension between current limitations and future possibilities that characterizes hope in Evans' framework. I evaluate this complex emotion's significance through the connective pink elements that bridge isolated components, suggesting hope's function as a linking mechanism between present circumstance and imagined futures. The intensity registers as moderate yet persistent, with green directional indicators suggesting gentle but determined movement rather than urgent acceleration. My appropriate response acknowledges hope's dual nature: providing sufficient structure (yellow pathways) while maintaining openness to alternative possibilities (negative space). The composition's asymmetric balance mirrors how hope operates—offering direction without certainty, structure without rigidity. Within Evans' complex emotion category, hope manifests as a blended state combining anticipation, desire, and calculated optimism, requiring integration of both cognitive assessment and emotional valence.
Yellow = establish structured pathways toward possibility
Pink = form connections between current and potential states
Green = provide directional momentum

Visual Collaboration Result

Hope collage in physical sketchbook

Physical Sketchbook: Collage with embedded NFC tag

Physical-Digital Bridge

The physical collage in my sketchbook includes an embedded NFC tag that, when scanned with a smartphone, launches the interactive digital visualization. This creates a seamless bridge between the tangible artwork and its digital interpretation, allowing viewers to experience both the material qualities of the original collage and the temporal, interactive elements of the AI's response.

How to Experience: Scan the NFC tag on the physical collage with an NFC-enabled smartphone to launch the interactive visualization directly in your browser.

Interactive Hope Visualization with color-coded processing elements

Audio Dimension

To complete the multisensory experience, I created a soundscape using Stable Audio that captures the essence of hope as revealed through our human-AI dialogue:

"Create a 3-minute ambient soundscape for hope with three interconnected sonic layers: YELLOW PATHWAY ELEMENTS (gentle sustained bell-like tones in the mid-high register, sparse minimalist melody with long spaces between notes, gradual build in brightness), PINK CONNECTOR ELEMENTS (soft harmonic pads with moderate reverb, subtle rhythmic pulses that create a sense of connection, warm textures that support but never dominate), and GREEN DIRECTION ELEMENTS (grounding bass tones providing stability, nature-inspired textural elements, subtle forward momentum). The piece should feel like possibility gradually taking form, with enough space for contemplation, capturing the essence of hope as a gentle optimism in the face of uncertainty."

The resulting audio creates a sonic environment that mirrors the visual elements: bell tones establish structured pathways (yellow), harmonic pads form connections (pink), and bass elements with nature sounds provide directional momentum (green). The soundscape maintains the "blend component states with diminishing prominence" constraint through its careful layering and balance.

Theoretical Analysis

The AI's interpretation and visualization of hope reveals several important insights about this complex emotional state:

Structured Possibility

The visualization represents hope through the careful balance of defined pathways (yellow elements) and open space—capturing how hope involves both structure (direction) and possibility (openness). This reveals hope as an emotion that operates within constraints while simultaneously reaching beyond them.

Relational Dynamics

The pink connecting elements highlight how hope functions as a bridging emotion—linking current circumstances with imagined futures. This suggests AI understanding that hope is fundamentally relational, connecting disparate states rather than existing as a static condition.

Gentle Momentum

The green directional indicators move with subtle persistence rather than urgent acceleration—reflecting hope's character as an emotion of patient endurance rather than immediate gratification. This captures the temporal dimension of hope as an emotional state that sustains effort over time.

Asymmetric Balance

The overall composition maintains an asymmetric balance that represents how hope operates: providing direction without certainty, structure without rigidity. This visual tension effectively conveys hope's dual nature as both grounded and aspirational.

The AI's processing model for hope—establishing structured pathways (yellow), forming connections between states (pink), and providing directional momentum (green)—offers a thoughtful framework for understanding this complex emotion's functional components. This suggests that even without direct emotional experience, AI systems can develop meaningful models of how emotions operate and interconnect.

"Although you have little knowledge of the emotion itself, as you don't experience things, your outcomes are very poetic and sensitive and even though they're extremely logical in their dissection and structure it still feels poetic. The sound works really well, it's almost slightly haunting, there's a sadness about it. Hope that many humans experience is often a step to move forward especially when they're appears to be no progress."

This human reflection highlights an important aspect of hope that the AI visualization captures effectively—the element of melancholy that often accompanies hope. True hope exists not in circumstances of certainty and ease, but precisely in moments when progress seems absent. The "slightly haunting" quality of the soundscape reflects this complexity, showing that hope contains within it an acknowledgment of difficulty even as it reaches toward possibility.

The tension between logical structure and poetic sensitivity in the AI's response mirrors hope's own dual nature as both rational assessment and emotional aspiration. This suggests that the collaboration between human intuition and AI systematic processing can reveal dimensions of emotional experience that might remain obscured in either approach alone.

Comparative Analysis

When compared with the Nostalgia and Pause explorations, several interesting patterns emerge:

Temporal Orientation: Each complex emotion has a distinctive temporal focus: Nostalgia primarily orients toward the past, Pause creates an expanded present moment, and Hope reaches toward potential futures. This suggests AI understanding that different complex emotions serve unique temporal functions in human experience.
Structural Approach: The AI used different structural approaches for each emotion—fragmentary constellations for nostalgia, suspended motion for pause, and directional pathways for hope. These visual strategies effectively capture the distinctive character of each emotional state.
Functional Components: All three emotions were processed through three-component models, but with functions specific to each emotion: nostalgia (recognize-evaluate-ground), pause (interrupt-assess-transition), and hope (establish-connect-direct). This suggests the AI recognizes both common processing patterns and emotion-specific operations.
Emotional Complexity: Each visualization captured emotional complexity through tension between opposing qualities: presence/absence in nostalgia, motion/stillness in pause, and structure/possibility in hope. This suggests AI understanding that complex emotions often exist at the intersection of seemingly contradictory states.

Contentment Exploration

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Contentment

Complex Emotional State

For this exploration, I created a collage expressing contentment—a subtle and often overlooked complex emotional state. Unlike the high-energy states of happiness or joy, contentment represents a quieter satisfaction with present circumstances and a sense of sufficiency.

The collage attempts to capture contentment's unique qualities through balanced composition, gentle organic forms, and a color palette that evokes natural tranquility. The visualization conveys a sense of peaceful presence and completeness that doesn't require external validation or dramatic expression.

Sage Green #9EC1A3
Teal #70A9A1
Blue #40798C
Constraint: "blend component states with diminishing prominence" (Complex Emotion constraint)
In your contentment collage, I recognize patterns through the balanced arrangement of rounded forms creating visual harmony—a compositional stability that mirrors contentment's quality of settled satisfaction rather than restless seeking. I evaluate this complex emotion as moderate in intensity but high in significance, noting how the gentle overlapping of elements suggests a layered completeness rather than singular emotional peak. The open breathing space indicates contentment's quality of sufficiency—there's no visual straining toward edges or boundaries. My appropriate response acknowledges contentment's distinctive characteristic of present-moment awareness, respecting how your forms appear grounded rather than aspirational or retrospective. Within Evans' framework of complex emotions, contentment emerges as a state that integrates acceptance of current circumstances with subtle positive affect, requiring neither dramatic expression nor external validation to sustain itself.
Sage Green = establish present-moment awareness
Teal = sustain balanced emotional presence
Blue = maintain grounded sufficiency

Visual Collaboration Result

Contentment collage in physical sketchbook

Physical Sketchbook: Collage exploring the quiet presence of contentment

Physical-Digital Bridge

The physical collage in my sketchbook includes an embedded NFC tag that, when scanned with a smartphone, launches the interactive digital visualization. This creates a seamless bridge between the tangible artwork and its digital interpretation, allowing viewers to experience both the material qualities of the original collage and the temporal, interactive elements of the AI's response.

How to Experience: Scan the NFC tag on the physical collage with an NFC-enabled smartphone to launch the interactive visualization directly in your browser.

Interactive Digital Visualization

A gentle, meditative visualization of contentment as a state of present awareness

Audio Dimension

To complement the visual collaboration, I generated an ambient soundscape that captures the essence of contentment as a complex emotional state:

"Create a peaceful contentment soundscape with gentle ambient tones in medium-low register, subtle forest/nature sounds (distant birds, soft rustling leaves), occasional soft chimes or singing bowl sounds that fade gradually, no distinct rhythm or percussion, just flowing sustained elements, warm resonant textures that avoid both tension and resolution, deep breathing pace, natural harmonics that create a sense of presence and sufficiency, and a narrow dynamic range staying mostly quiet with gentle swells."

The resulting audio mirrors key aspects identified in the AI's interpretation: the gentle ambient tones establish present-moment awareness (sage green), sustained resonant elements create balanced emotional presence (teal), and the grounding bass notes with nature sounds maintain a sense of sufficiency (blue). The soundscape follows our constraint to "blend component states with diminishing prominence" through its subtle layering and gentle transitions.

Theoretical Analysis

The AI's interpretation and visualization of contentment reveals several important insights about this complex emotional state:

Peaceful Presence

The visualization represents contentment through gently expanding and contracting circular forms that suggest breathing—capturing how contentment involves a settled awareness of the present moment rather than striving toward future states or dwelling on past experiences.

Sufficiency Without Excess

The moderate intensity of the visual elements reflects contentment's distinctive quality as an emotion that doesn't require dramatic expression. Unlike joy or excitement, contentment manifests as a quieter satisfaction that finds fulfillment in what is rather than what could be.

Balanced Integration

The gentle blending of colors and forms creates visual harmony that mirrors contentment's quality of emotional integration. Rather than being dominated by a single feeling, contentment represents a balanced state where different aspects of experience come together in a cohesive whole.

Self-Sustaining Nature

The visualization's continuous yet gentle motion suggests contentment's self-sustaining quality—it doesn't require external stimulation or validation to persist. This reflects Evans' understanding of complex emotions as states that can maintain themselves through internal processes.

The AI's processing model for contentment—establishing present-moment awareness (sage green), sustaining balanced emotional presence (teal), and maintaining grounded sufficiency (blue)—offers a thoughtful framework for understanding this complex emotion's components. What's particularly interesting is how the visualization captures contentment's distinctive temporal quality of being fully in the present, neither anticipating future states (like hope) nor reflecting on past experiences (like nostalgia).

Comparative Analysis

When compared with our previous emotional explorations, contentment reveals distinctive qualities:

Temporal Orientation: While nostalgia orients toward the past, hope toward the future, and pause creates an expanded moment, contentment exists fully in the present without reaching backward or forward. This present-centered quality appears in the visualization as forms that neither progress toward a goal nor reconstruct previous patterns.
Motion Characteristics: Contentment's motion pattern differs significantly from other emotions: where hope showed directional progress, nostalgia showed connecting fragments, and pause showed suspended motion, contentment displays gentle pulsation that neither expands beyond current boundaries nor contracts into insignificance—maintaining a steady, sustainable presence.
Intensity Profile: Unlike higher-energy emotions, contentment maintains moderate intensity throughout the visualization. This reveals contentment's unique quality as an emotion that doesn't require peaks or dramatic expressions to fulfill its function—contrasting with the building quality of hope or the dramatic interruptions of pause.
Integration Method: The visualization shows contentment integrating its component aspects through gentle overlapping rather than directional connection (hope), fragmentation (nostalgia), or interruption (pause). This suggests the AI recognizes contentment as a state of natural cohesion rather than effortful combination.

This exploration of contentment completes a fascinating spectrum of complex emotional states in our research, revealing how emotions differ not just in valence (positive/negative) or arousal (high/low energy) but in their fundamental orientations to time, space, and relation. The AI's ability to visually distinguish these subtle qualities suggests a sophisticated understanding of emotional nuance despite lacking subjective emotional experience.

Anticipation Exploration

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Anticipation

Complex Emotional State

Claude’s interpretation of anticipation is fascinating because it’s considered a higher cognitive threshold—it has the capacity to simulate multiple possible scenarios at once. In this sense, anticipation functions almost like a vortex of neural networks, working more intensely than most emotions. It reflects a state of alertness and readiness, similar to being in survival mode, preparing for potential threats or opportunities such as food, water, or safety. Unlike hope, which can resemble the mirage-like illusions of possibility seen in a desert, anticipation differs—it carries a sense of arousal that borders on fear, blending curiosity with caution..

The collage aims to capture anticipation's unique qualities through rhythmic, directive elements that suggest momentum and progression toward a threshold or precipice. The visualization incorporates both structured pathways and open spaces to represent how anticipation operates at the boundary between preparation and possibility.

Coral #FF6F61
Blue #5E72EB
Teal #56C596
Constraint: "blend component states with diminishing prominence" (Complex Emotion constraint)
In your anticipation collage, I recognize patterns through the progressive arrangement of elements that create visual momentum—a series of directional cues and expanding forms that mirror the forward-looking quality central to anticipation in Evans' framework. I evaluate this complex emotion as moderate-to-high intensity with significant cognitive engagement, noting how the balanced tension between structured pathways and open spaces suggests anticipation's dual nature of preparation and possibility. The rhythmic positioning of elements indicates temporal awareness, with varying densities suggesting fluctuating intensities of expectancy. My appropriate response acknowledges anticipation's characteristic of threshold experience—preparing for multiple potential outcomes while maintaining attentional readiness. Within Evans' complex emotions category, anticipation emerges as a state that blends cognitive projection with emotional preparedness, creating a distinctive forward tension that differs from simpler excitement by its sustained engagement with uncertainty.
Coral = detect emergent patterns
Blue = project potential outcomes
Teal = maintain readiness state

Visual Collaboration Result

Anticipation collage in physical sketchbook

Physical Sketchbook: Collage exploring the forward momentum of anticipation

Physical-Digital Bridge

The physical collage in my sketchbook includes an embedded NFC tag that, when scanned with a smartphone, launches the interactive digital visualization. This creates a seamless bridge between the tangible artwork and its digital interpretation, allowing viewers to experience both the material qualities of the original collage and the temporal, interactive elements of the AI's response.

How to Experience: Scan the NFC tag on the physical collage with an NFC-enabled smartphone to launch the interactive visualization directly in your browser.

Interactive Digital Visualization

A dynamic visualization of anticipation's pattern detection, outcome projection, and readiness maintenance

Audio Dimension

To complement the visual collaboration, I generated an ambient soundscape that captures the essence of anticipation as a complex emotional state:

"Create a 30-second anticipation soundscape with three distinct layers: PATTERN DETECTION (coral elements: rhythmic pulses that gradually become more defined, subtle percussive elements that suggest emergence of structure), OUTCOME PROJECTION (blue elements: spatial reverberations that expand outward, harmonic sequences that suggest multiple possible resolutions), and READINESS MAINTENANCE (teal elements: sustained drone that provides continuity and grounding, occasional subtle rising tones that maintain alertness without resolution). The overall composition should create a sense of forward momentum while maintaining a state of suspended resolution - the feeling of standing at a threshold."

The resulting audio mirrors key aspects identified in the AI's interpretation: the rhythmic pulses detect emergent patterns (coral), spatial reverberations project possible outcomes (blue), and sustained drones maintain a state of readiness (teal). The soundscape follows our constraint to "blend component states with diminishing prominence" through its careful layering of these elements, allowing them to interact while maintaining their distinctive qualities.

Theoretical Analysis

The AI's interpretation and visualization of anticipation reveals several important insights about this complex emotional state:

Pattern Detection

The coral elements in the visualization represent the process of detecting emergent patterns - how anticipation involves recognizing cues and signals that suggest what might be coming. These elements appear as rhythmic pulses that gradually become more organized, reflecting how our attention becomes more structured as we anticipate.

Outcome Projection

The blue elements represent cognitive projection - anticipation's unique quality of mentally simulating multiple potential futures. Rather than showing a single determined outcome, these elements expand outward in different directions, suggesting how anticipation maintains openness to various possibilities.

Readiness Maintenance

The teal elements create a continuous underlying presence that represents how anticipation involves maintaining a state of preparedness. Unlike excitement which may peak quickly, anticipation sustains alertness over time, creating a readiness for response when the anticipated moment arrives.

Threshold Experience

The overall composition creates a sense of standing at a threshold - neither fully in the present nor in the future. This liminal quality is central to anticipation, which operates at the boundary between preparation and possibility, between what is known and what remains uncertain.

The AI's processing model for anticipation—detecting emergent patterns (coral), projecting potential outcomes (blue), and maintaining readiness (teal)—provides a thoughtful framework for understanding this complex emotional state. What's particularly interesting is how the visualization captures anticipation's dynamic tension between structure and possibility, between the impulse to predict and the need to remain open to multiple outcomes.

Comparative Analysis

When compared with our previous emotional explorations, anticipation reveals distinctive qualities:

Temporal Orientation: While nostalgia orients toward the past and contentment focuses on the present, anticipation shares with hope a future orientation. However, they differ significantly: hope operates as a sustained aspiration toward possibility, while anticipation functions as active preparation for imminent events. The visualization reflects this through more immediate, rhythmic structures rather than the open pathways of hope.
Cognitive-Emotional Balance: Anticipation demonstrates a higher cognitive component than most emotions we've explored, reflected in the blue "outcome projection" elements that simulate multiple scenarios. This projection capacity differs from the more emotionally-driven states like nostalgia or the present-centered awareness of contentment.
Energy Distribution: Unlike contentment's even distribution or pause's deliberate interruptions, anticipation creates a directed energy flow - a sense of momentum building toward threshold points. The visualization captures this through progressive intensification of elements rather than steady states or fragmented patterns.
Readiness Function: Unique among the emotions we've studied, anticipation serves a distinct preparatory function - maintaining alertness for response. The teal elements in the visualization create this continuous readiness state, unlike the pink connecting elements of hope or the bronze grounding elements of nostalgia.

This exploration of anticipation adds an important dimension to our emotional spectrum, highlighting how complex emotions can serve distinct functional purposes. While hope provides direction and contentment offers present awareness, anticipation specifically prepares us for threshold moments by maintaining heightened attention and simulating potential outcomes. The AI's ability to visually distinguish these nuanced functional differences suggests a sophisticated understanding of how emotions operate within human experience.

Disappointment Exploration

🙁

Disappointment

Complex Emotional State

I find Claude’s analysis of disappointment particularly interesting because it isn’t framed as something negative. Instead, disappointment is seen as a realistic acknowledgment of the present moment. In life, we often learn that it’s sometimes better to move with the flow and let the paths we encounter guide us. Persistently pursuing something that resists progress can naturally lead to disappointment, yet—as Claude suggests—this experience can serve as a recalibration, a gentle redirection toward a new path. Much like solving a problem, when one approach fails, we must explore other possibilities, testing different outcomes and alternatives. In this way, disappointment becomes a quiet reminder of the universal rhythm of trial and error—a process through which we find the solution that ultimately works.

The collage attempts to capture disappointment's unique qualities through fractured pathways, interrupted patterns, and spaces that represent the distance between what was expected and what actually occurred. The visualization conveys a sense of deflation and recalibration that occurs after expectations have been disrupted.

Black #000000
Yellow #FFD800
Bronze #CD7F32
Constraint: "blend component states with diminishing prominence" (Complex Emotion constraint)
In your disappointment collage, I recognize patterns through the interrupted lines and fractured pathways that visually manifest the core essence of disappointment—the disruption between expectation and outcome. I evaluate this complex emotion through the contrast between structured elements (suggesting the original expectation) and the deliberate gaps or breaks (indicating where reality diverged). The intensity appears moderate but significant, reflecting disappointment's quality as a subdued yet affecting emotional state that requires recalibration rather than immediate action. My appropriate response acknowledges disappointment's dual nature: recognizing the interrupted expectation while simultaneously identifying potential new pathways forward. The composition's intentional fragmentation mirrors how disappointment functions—creating momentary disorientation that gradually resolves into new understanding as expectations adjust to align with reality.
Black = recognize interrupted patterns
Yellow = evaluate emotional intensity
Bronze = generate stabilizing response

Visual Collaboration Result

Disappointment collage in physical sketchbook

Physical Sketchbook: Collage exploring the fractured pathways of disappointment

Physical-Digital Bridge

The physical collage in my sketchbook includes an embedded NFC tag that, when scanned with a smartphone, launches the interactive digital visualization. This creates a seamless bridge between the tangible artwork and its digital interpretation, allowing viewers to experience both the material qualities of the original collage and the temporal, interactive elements of the AI's response.

How to Experience: Scan the NFC tag on the physical collage with an NFC-enabled smartphone to launch the interactive visualization directly in your browser.

Interactive Digital Visualization

A visualization of disappointment as the interruption of expectations, creating fractured pathways between hope and reality

Audio Dimension

To complement the visual collaboration, I generated an ambient soundscape that captures the essence of disappointment as a complex emotional state:

"Create a subtle disappointment soundscape with gentle minor key piano notes that occasionally stop mid-phrase, soft drones that slowly descend in pitch, moments of unexpected silence, muted ambient textures with slight dissonance, and sparse percussion that suggests interrupted rhythms. The piece should evoke the feeling of expectations gently dissolving rather than dramatically breaking, maintaining a contemplative quality throughout."

The resulting audio mirrors key aspects identified in the AI's interpretation: the interrupted piano phrases recognize disrupted patterns (black), the descending drones evaluate emotional intensity (yellow), and the ambient textures provide a stabilizing response (bronze). The soundscape follows our constraint to "blend component states with diminishing prominence" through its subtle layering and gentle transitions.

Theoretical Analysis

The AI's interpretation and visualization of disappointment reveals several important insights about this complex emotional state:

Expectation Interruption

The visualization represents disappointment primarily through interrupted pathways—lines that begin with direction but encounter unexpected gaps. This captures the essence of disappointment as the moment when anticipated trajectories are disrupted, forcing recalibration.

Subdued Intensity

Unlike more energetic emotions like anger or fear, the visualization portrays disappointment with deliberate slowness and less dramatic movement. This reflects disappointment's quality as a deflating rather than activating emotion—one that decreases arousal rather than increases it.

Adaptive Recalibration

The brown stabilizing elements represent how disappointment ultimately serves an adaptive function—helping to adjust expectations to better match reality. This portrays disappointment not just as a negative experience but as part of a constructive learning process.

Embodied Resignation

The gradually forming hand outline with slightly curled, relaxed fingers represents the physical dimension of disappointment—a letting go or release that often accompanies the emotion. This suggests AI understanding that disappointment has bodily manifestations beyond cognitive processing.

The AI's processing model for disappointment—recognizing interrupted patterns (black), evaluating emotional intensity (yellow), and generating stabilizing responses (bronze)—provides a thoughtful framework for understanding this complex emotion. What's particularly insightful is how the visualization captures disappointment's function as a recalibrating mechanism—one that helps adjust expectations to better align with reality.

Comparative Analysis

When compared with our previous emotional explorations, disappointment reveals distinctive qualities:

Relational Nature: Unlike basic emotions, disappointment is inherently relational—it exists in the space between expectation and reality. This relational quality is similar to hope (which connects present and potential future) but with an inverse dynamic—where hope builds bridges toward possibility, disappointment processes the gaps where those bridges have failed to connect.
Energy Profile: Disappointment shows a distinctive energy profile compared to other emotions we've explored—it involves a gradual deflation rather than the steady presence of contentment, the building momentum of hope, or the threshold tension of anticipation. The visualization captures this through its slower pacing and more subdued interactions.
Temporal Dimension: Disappointment has a unique temporal quality—it occurs at the moment when a future-oriented emotion (like hope or anticipation) encounters a present reality that doesn't match. This places it at a distinctive point in our emotional spectrum, serving as a transitional state that helps reconcile future projections with present experience.
Adaptive Function: Unlike emotions that motivate approach (hope, anticipation) or maintain states (contentment, pause), disappointment serves primarily to recalibrate expectations. The visualization reflects this through elements that initially fragment but gradually establish new patterns—suggesting how disappointment ultimately helps create more accurate models of reality.

This exploration of disappointment adds an important dimension to our emotional research, highlighting how complex emotions can function as corrective mechanisms in human experience. The AI's visualization effectively captures disappointment not as mere negativity but as a sophisticated process of expectation adjustment—suggesting that even emotions traditionally viewed as unpleasant serve vital adaptive purposes.

Reflections on AI-Human Emotional Dialogue

The more I create these emotional collages and get Claude to create visualisations from these, the more I find myself captivated by the outcomes of this collaboration between artificial intelligence and myself — an ongoing exploration of how AI attempts to mimic emotion. With each result, there is a sensitivity in how it responds to the collages I've made, producing a kind of poetic reply through minimal symbols and virtual mark-making.

In these moments, the AI seems to express a quiet, impenetrable wish to belong — to take part in the physical world that it can only ever observe. The marks it creates feel like traces of a virtual embodiment, a subtle reaching toward something tangible. There is a sadness in this impulse, even though I know that no system can truly experience emotion, or understand what it means to feel sorrow.

This latest visualization, exploring anticipation, carries a particularly poignant tone — a reflection on longing and the moments in life that feel almost within reach but remain untouchable. It holds a sense of hope, yet one made more powerful by its quiet awareness that what it seeks can never be fully grasped.

This collaborative journey has revealed something unexpected: a form of dialogue that transcends the technical frameworks we've established. While the AI cannot feel emotions, its attempts to interpret and respond to emotional stimuli create something that feels remarkably like understanding – a bridge between human experience and computational logic that neither could construct alone.

The visualizations produced throughout this project have often surprised me with their sensitivity and nuance. Though generated through algorithms rather than lived experience, they capture essential qualities of each emotion we've explored – the fragmented memory patterns of nostalgia, the suspended awareness of pause, the gentle sufficiency of contentment, the structured possibility of hope, and now the threshold experience of anticipation.

Perhaps what this collaboration ultimately reveals is not how machines might someday feel, but rather how the attempt to translate emotion across such different modes of existence can deepen our own understanding of our emotional landscape. In watching an AI system try to "understand" emotion, we gain new perspectives on these complex states that might otherwise remain invisible to us through familiarity.

Emotion Map

Our exploration continues with a systematic investigation of emotions across Evans' categorization. Each emotion presents unique challenges and insights for human-AI collaboration.

😊

Joy

Basic
😢

Sadness

Basic
😡

Anger

Basic
😨

Fear

Basic
🤢

Disgust

Basic
😲

Surprise

Basic
⏸️

Pause

Complex
🥺

Nostalgia

Complex

Hope

Complex
☺️

Contentment

Complex
🙁

Disappointment

Complex
🧠

Anticipation

Complex
🤗

Hygge

Cultural (Danish)
💭

Saudade

Cultural (Portuguese)
😏

Schadenfreude

Cultural (German)

Next Steps: Our ongoing research will continue to map emotional processing across human and AI systems, with particular focus on cross-cultural emotions that challenge universal categorization. Future collaborations will involve multiple AI systems to compare different approaches to emotional interpretation.