02 Research and References¶
Conceptual Foundations¶
Ritual, Presence, and Memory¶
Ritual practices cultivate presence by transforming ordinary actions into moments of attention and reflection. Anthropologist Victor Turner describes ritual as a performative process through which meaning emerges from repeated bodily and symbolic acts (Turner, 1969). Rather than existing only in language or thought, ritual knowledge is enacted through voice, movement, and material engagement.
Gratitude functions as a practice of presence: to express gratitude requires noticing, naming, and inhabiting the present moment. Through repetition, these acts of awareness become embedded in bodily memory. Paul Connerton argues that societies remember through “incorporating practices,” in which memory is carried by posture, gesture, and habitual action rather than by written records alone (Connerton, 1989).
Gratitude Loom draws from these perspectives by framing weaving as a ritual of cultivated presence that generates material memory. Spoken gratitude and mindful movement shape woven patterns through a responsive system, allowing moments of awareness to become physical traces preserved in textile form. Each textile becomes a record not only of what was said, but of how it was embodied through rhythm, timing, and attention.
By linking ritual, presence, and memory, this project explores how contemporary technologies can support reflective practices rather than accelerate them. Instead of prioritizing efficiency, Gratitude Loom proposes a human-centered system in which repetition, slowness, and embodiment become central to how meaning is produced and remembered.
References
Turner, Victor. The Ritual Process: Structure and Anti-Structure. Chicago: Aldine Publishing, 1969.
Connerton, Paul. How Societies Remember. Cambridge: Cambridge University Press, 1989.
Existing Gratitude Practices¶
Across both modern wellness practices and many traditional and Indigenous cultures, gratitude is expressed through spoken words, songs, gestures, and the making of objects such as textiles, baskets, and offerings. These practices show that gratitude is often embodied through voice, body movement, and material creation, rather than existing only as a private thought. In the Gratitude Loom project, these ideas are brought into an interactive weaving system where spoken gratitude becomes sound input, hand movement becomes pattern, and the woven textile becomes a physical record of the ritual. This research explores how gratitude can be experienced as a shared interaction between voice, body, and material.
Research table of existing gratitude practices across modern and traditional cultures, focusing on voice, bodily action, and material expression. — Pattaraporn (Porpla) Kittisapkajon
Craft as a Knowledge System¶
Craft practices such as weaving operate as knowledge systems that encode cultural memory, skill, and meaning through bodily movement and material process. As Richard Sennett argues in The Craftsman, knowledge in craft emerges through repetition, attention, and the intimate relationship between hand and material, where making becomes a form of thinking rather than mere production (Sennett, 2008).
Similarly, Kristina Höök’s work on somaesthetic interaction design emphasizes that the body itself is a site of knowledge, where understanding arises through sensation, movement, and lived experience rather than abstract instruction alone (Höök, 2018). In weaving, pattern structures function as both visual forms and procedural knowledge, translated through gesture and rhythm into textile structure.
Gratitude Loom draws from these perspectives by treating weaving as a living archive of intention and ritual. Spoken gratitude and mindful movement become inputs into a system that produces material patterns, allowing emotional and temporal experiences to be recorded in textile form. In this way, the loom functions as both a craft tool and a knowledge interface, transforming embodied reflection into a shared material record.
References
Sennett, Richard. The Craftsman. New Haven: Yale University Press, 2008.
Höök, Kristina. Designing with the Body: Somaesthetic Interaction Design. Cambridge, MA: MIT Press, 2018.
AI as Co-Regulator / Collaborator¶
Recent work in art and human–computer interaction suggests that artificial intelligence does not need to function as an autonomous creator or an automated tool. Instead, AI can be designed as a collaborative partner that participates in creative processes through interaction, feedback, and adaptation. In this view, intelligence does not exist only inside the machine but emerges through the relationship between human and system.
Artist-researcher Sougwen Chung provides a key example of this approach. In her drawing and robotics projects, Chung creates systems in which machines respond to her gestures in real time. Rather than using AI to generate finished artworks independently, she treats the machine as something that “draws back.” The artwork is created through an ongoing exchange between human movement and machine behavior. Chung frames this process as a new form of intelligence based on flow, adaptation, and shared agency, rather than automation or efficiency.
This perspective challenges the idea that creativity belongs solely to either humans or machines. Instead, authorship becomes distributed across a feedback loop: human action influences machine response, and machine response in turn shapes human action. The result is not a pre-determined output but an emergent pattern formed through interaction. Such systems emphasize responsiveness, rhythm, and negotiation rather than control.
Research in co-creative and embodied interaction design similarly argues that intelligent systems can support reflection and attentiveness instead of replacing human decision-making. When computational systems respond to bodily input — such as voice, movement, or timing — they can function as co-regulators, helping guide the pace and structure of an activity while leaving meaning and intention with the human participant.
Within Gratitude Loom, AI is framed as a co-regulator rather than a pattern generator. The system does not independently design weaving patterns; instead, it modulates existing weave grammars in response to human voice and ritualized movement. Pattern variation emerges through a continuous feedback loop between human intention, machine response, and material execution. In this way, the woven textile becomes a physical trace of collaboration between human, machine, and material.
By treating AI as a collaborative participant embedded within craft and ritual, the project explores a model of intelligence grounded in relationship and embodiment. This approach shifts AI away from automation toward a form of creative partnership that supports mindfulness, repetition, and shared meaning through making.
References
“Seeing Double — Bridging Dualities with Relational…” YouTube video, April 27, 2025, Sougwen Chung on Human-Machine Collaboration, posted by Singapore Computer Society, 1:09:23, https://www.youtube.com/watch?v=pnjx0X8dJGQ .
Historical & Material Lineage¶
Loom Anatomy — 4 Shaft Table Loom¶
For this project, I selected a 4-shaft table loom because it offers a balance between simplicity and structural complexity. The loom is beginner-friendly while still enabling the creation of varied woven patterns through controlled shaft movement.
Understanding the anatomy of the loom is essential to designing Gratitude Loom as a human–machine system. Each component—such as the shafts, beater, warp beam, and cloth beam—defines how bodily actions are translated into woven structure. In this project, the loom becomes not only a tool for making textiles but also a physical interface where voice, movement, and algorithmic logic converge.
Historically, looms have functioned as early programmable systems, most notably through the Jacquard mechanism. By working with a 4-shaft loom, this project explores how pattern logic can be guided by computational processes while preserving the embodied role of the human weaver. The loom therefore operates as both a material archive of gratitude and a structural system shaped by ritual interaction.
The diagram below illustrates the basic anatomy of a table loom, which informs both the physical and conceptual design of the Gratitude Loom system.
The anatomy of a table loom. Source: Deborah Chandler, Learning to Weave.
References
Chandler, Deborah. Learning to Weave. Loveland, CO: Interweave Press, 1995.
Dixon, Anne. The Handweaver’s Pattern Directory: Over 600 Weaves for Four-Shaft Looms. Loveland, CO: Interweave Press, 1994.
Jacquard Loom / Programmable Machines¶
The Jacquard loom, invented in the early 19th century by Joseph Marie Jacquard, is widely recognized as one of the first programmable machines. It used punched cards to control which warp threads were lifted during weaving, allowing complex patterns to be produced automatically. Each card encoded a row of the textile pattern, functioning as a physical form of binary logic.
This system directly influenced the development of early computing. Charles Babbage adopted the punched card mechanism of the Jacquard loom in his designs for the Analytical Engine, and the concept of machine-readable instructions later shaped modern computer programming.
Binary and the Jacquard Mechanism – demonstration of punched card pattern control. Source: Macclesfield Museums (Silk Museum).
The Jacquard loom represents an early shift from human pattern control to machine automation through punched cards. Gratitude Loom responds to this history by reintroducing voice and bodily ritual as active inputs into pattern formation through responsive AI guidance.
By connecting weaving’s historical role in computation with contemporary human–machine collaboration, this project explores how future technologies might support presence, reflection, and embodied interaction rather than efficiency alone.
Pattern Logic & Computational Systems¶
Woven Pattern Logic¶
Woven patterns operate as structured systems of rules that determine how warp and weft threads intersect to produce visual and material form. In Learning to Weave, Deborah Chandler describes weaving patterns as sequences of ordered actions governed by shaft movements and treadling instructions, where each row of weaving follows a defined logic of repetition and variation (Chandler, 1995). These pattern systems function as procedural knowledge, translating abstract design into physical structure through the weaver’s embodied practice.
Anne Dixon’s The Handweaver’s Pattern Directory further demonstrates how complex woven designs emerge from systematic combinations of shaft lifts and thread arrangements. The book presents over 600 weave structures for four-shaft looms, revealing how a limited set of mechanical parameters can generate extensive pattern diversity (Dixon, 1994). Each pattern operates as a modular rule set that can be altered through changes in sequence, rhythm, and repetition.
Together, these references frame weaving as a form of pattern logic comparable to algorithmic systems. The weaver follows structured instructions while allowing for improvisation and material feedback, producing outcomes that are both rule-based and responsive. This balance between constraint and variation informs Gratitude Loom’s approach to pattern generation, where spoken gratitude and bodily interaction influence how predefined pattern rules are activated through computational guidance.
By treating woven structures as logical systems rather than fixed designs, Gratitude Loom extends traditional weaving knowledge into a responsive human–machine framework. Pattern becomes not only a visual outcome but a record of interaction shaped by timing, attention, and ritual performance.
Basic Weave Structures as Pattern Grammar (Plain Weave & Twill)¶
Fundamental weave structures such as plain weave and twill form the basic grammar of woven pattern logic. These structures define how warp and weft threads interact through ordered sequences of shaft lifts and treadling instructions. Rather than functioning as decorative outcomes alone, weave structures operate as rule-based systems that translate abstract patterns into physical form.
Plain weave follows the simplest alternating logic of over–under repetition, producing a stable and uniform textile surface. Twill introduces variation by shifting this sequence across rows, creating diagonal pattern formations through controlled offset and repetition. These structures demonstrate how complex visual effects can emerge from a limited set of mechanical and logical rules.
On a four-shaft loom, only certain pattern combinations are structurally possible, while others are restricted by shaft count and thread arrangement. These constraints create a defined design space governed by mechanical and logical rules. Gratitude Loom builds upon this grammar by allowing voice and bodily interaction to activate and modulate pattern sequences within established weave structures, transforming traditional pattern logic into a responsive human–machine system.
By treating weave structures as pattern grammar, this project connects textile design with computational thinking, where rules, repetition, and variation form the basis for meaningful pattern generation.
| Weave Structure | Core Logic Rule | Shaft Requirement | Pattern Behavior | Structural Stability | What Works Well | What Does Not Work |
|---|---|---|---|---|---|---|
| Plain Weave | Alternating over–under sequence (1,2,1,2…) | Minimum 2 shafts (4 shafts can replicate) | Uniform, repetitive grid pattern | Very stable and balanced | Clear rhythm, slow repetition, ideal for ritual-based interaction | Limited visual variation, no directional patterning |
| Twill Weave | Offset sequence that shifts each row (e.g., 1-2-3-4 / 2-3-4-1) | Minimum 3–4 shafts | Diagonal or stepped pattern formation | Moderately stable, more flexible than plain weave | Directionality, variation, expressive pattern logic | More complex setup, sensitive to errors in sequence |
Design Constraints for Weavable Pattern Logic¶
For this prototype, Gratitude Loom focuses on basic weave structures—plain weave and twill—to ensure structural stability and conceptual clarity. While computational systems can generate infinite pattern variations, not all patterns are physically weavable or meaningful within textile logic. This project therefore establishes constraints to prevent unweavable, unstable, or aesthetically chaotic outcomes.
These constraints ensure that generated patterns remain balanced, structurally sound, and aligned with traditional weaving principles. By limiting pattern generation to valid weave grammars, Gratitude Loom treats weaving as a rule-based system rather than arbitrary visual output. This approach maintains coherence between computational logic and material practice.
| Issue to Avoid | Description | Why It Fails Structurally | Design Principle |
|---|---|---|---|
| Excessive floats | Long sequences of warp or weft threads without interlacing | Creates loose threads, weak fabric, and distortion | Limit float length to maintain textile stability |
| Unbalanced twill | Patterns that do not repeat evenly across shafts | Produces irregular tension and visual imbalance | Use symmetrical or offset treadling sequences |
| Random shaft combinations | Arbitrary lifting of shafts without rule structure | Results in unweavable or incoherent fabric | Follow defined weave grammars (plain, twill) |
| Aesthetic chaos | Too much variation without repetition | Breaks visual rhythm and ritual consistency | Preserve repetition and pattern continuity |
| Disconnection from textile logic | Patterns that ignore warp/weft interdependence | Produces designs that cannot be translated into physical weaving | Respect structural constraints of the loom |
References
Chandler, Deborah. Learning to Weave. Loveland, CO: Interweave Press, 1995.
Dixon, Anne. The Handweaver’s Pattern Directory: Over 600 Weaves for Four-Shaft Looms. Loveland, CO: Interweave Press, 1994.
Sequences of Weaving Process¶
According to Deborah Chandler’s Learning to Weave, the fundamental sequence of actions in weaving consists of three recurring steps: changing the shed, throwing the shuttle, and beating the weft into place (Chandler, 1995). These actions form a rhythmic loop that structures both the physical making of cloth and the embodied experience of weaving.
While these steps remain consistent, their order can vary depending on technique and personal preference. Some weavers beat the weft while the shed is still open, which reduces draw-in and creates a softer structure. Others close the shed before beating, which locks the threads more firmly into place and produces a tighter fabric. Each sequence has practical and aesthetic consequences, and no single method is universally correct.
What is essential is not the specific order chosen, but the consistency of the sequence. Repetition establishes rhythm, stability, and coherence in the woven structure. This highlights weaving as a temporal and procedural system in which meaning and form emerge through ordered bodily action rather than isolated gestures.
In the context of Gratitude Loom, the weaving sequence becomes part of the ritual logic of the system. The act of changing the shed, throwing the shuttle, and beating the weft is not only a technical process but a performative structure that supports presence, attention, and embodied interaction. By framing weaving as a sequence-based practice, the project emphasizes how pattern and memory arise from repeated, intentional movement over time.
References
Chandler, Deborah. Learning to Weave. Loveland, CO: Interweave Press, 1995.
AI as Rule-Based Pattern Engine¶
Rule-based systems have long been used in computational design to generate structured variation through defined constraints rather than unrestricted form-making. In generative and algorithmic art research, patterns emerge from formal grammars composed of rules, parameters, and iterative processes (Galanter, 2003; McCormack & Dorin, 2001). These systems demonstrate how complexity can arise from limited and well-defined logical structures.
Within textile traditions, weaving itself operates as a rule-based pattern system. As Deborah Chandler describes in Learning to Weave, woven structures are governed by ordered sequences of shaft lifts and treadling instructions that must follow strict structural logic (Chandler, 1995). Anne Dixon’s The Handweaver’s Pattern Directory further illustrates how hundreds of pattern variations can be produced through systematic combinations of a small number of shafts and rule-based sequences (Dixon, 1994). These references position weaving as a material grammar comparable to computational rule systems.
Recent research in human–computer interaction and embodied interaction design has emphasized that intelligent systems need not function as autonomous decision-makers but can instead operate as constrained partners within human-centered processes (Höök, 2018). In such frameworks, computational systems respond to bodily input and support reflective engagement rather than automation or efficiency alone.
Framing AI as a rule-based pattern engine situates Gratitude Loom within this lineage of constrained generative systems. Rather than producing arbitrary outputs, the computational layer operates within established weave grammars such as plain weave and twill, ensuring that pattern generation remains structurally coherent and materially grounded. Human input—through voice and ritualized movement—acts as a parameter that activates and modulates these pattern rules.
This approach aligns computational intelligence with craft knowledge, suggesting a model of human–machine collaboration in which algorithms function as guides within a predefined grammar rather than as independent creators. By embedding AI within textile logic and ritual structure, the project explores how intelligent systems can support attentiveness, repetition, and embodied meaning instead of prioritizing speed or automation.
| Element | Role in System |
|---|---|
| Weave Grammar | Defines valid pattern rules (plain weave, twill) |
| AI Engine | Selects and modulates pattern sequences within rules |
| Human Input | Voice rhythm, timing, and ritual completion |
| Constraints | Prevents unweavable or chaotic patterns |
| Output | Structurally coherent woven textile |
| Feedback | Visual and tactile reflection for the user |
References
Chandler, Deborah. Learning to Weave. Loveland, CO: Interweave Press, 1995.
Dixon, Anne. The Handweaver’s Pattern Directory: Over 600 Weaves for Four-Shaft Looms. Loveland, CO: Interweave Press, 1994.
Galanter, Philip. “What Is Generative Art? Complexity Theory as a Context for Art Theory.” GA2003 – 6th Generative Art Conference, 2003.
McCormack, Jon, and Alan Dorin. “Art, Emergence, and the Computational Sublime.” Proceedings of the 2nd Iteration Conference on Generative Systems in the Electronic Arts, 2001.
Höök, Kristina. Designing with the Body: Somaesthetic Interaction Design. Cambridge, MA: MIT Press, 2018.
Inspirations¶
Human-Machine Collaboration¶
Sougwen Chung collaborates with robots on large-scale paintings