How to build an evolving interactive system (art)?
How does user interaction/audience interaction can actively change the very nature of the system (or even generate a new one) rather than passively navigating/interacting with the system or minorly changing the pre-given range parameters? (Do we have to borrow generative ai/algorithms here?)

Metaphor from Scientific Experiments (Golden Ratio?)
DESIGNING ACTIVE-INTERACTION BASED EXPERIMENT IS ULTIMATELY REMINISCENT TO DESIGNING ACTIVE-INTERACTION BASED COMPUTATIONAL ARTWORK

Departing from traditional passive experiments → active user/audience engagement-based experiments
Designing Neuroscience/HCI experiment – in an active way, not a passive way – is almost reminiscent to building an active interactive art (not the passive one, not just a bodily interaction)

Type A: Semantic Interaction: Direct, Explicit, Button-based, GUI-based (Non-language) 
Type B: Phenomenological Interaction: Indirect, Implicit, Sensual, Human-Driven Motion, Facial, Touch, BCI Tangible Interaction 
Type C: Language-based Interaction: Text, Voice (LLM-Integrated)
Type D: Ambient Environmental Data

From Type B/D (Non-semantic interaction) to Type A/C (semantic interaction)
But not just about interaction modality being semantic – it’s also about how these interactions actually actively shape/alter/change/generate the systemic result, rather than minorly navigating within/changing minor parameters of the systems.
Experiment setting: Verifying if golden ratio – people like it in neuroscience way (is preference with golden ratio innate in our brains?)

Engagement Level 1. 
Traditional approach
A-B testing, 2-6 images (visual stimuli) given, user selects the most preferable image
Very passive engagement

Engagement Level 2.
Slider approach, simple gui-based approach, often used in hci experiments
User adjusts slider (of ratio), output visual stimuli morphs accordingly, user lands on the most comfortable ratio
More active, yet also comes with limitations. 
User changing the parameter of the system, whilst the system rule stays in

Engagement Level 3. 
Hypothetical, Experimental, Most active user engagement
Smth more than just two-dimensional navigation 
User should actively joy / explore the unexplored territory. And then end up with the optimal ratio that they think they’re comfortable with/aesthetically pleasing. (Neuroaesthetics) Not just performing for the sake of experiment – choosing one of many images, using a slider to pick one ratio – these are not really natural settings. You won’t do this for the sake of aesthetic pleasure, you do this bc this is an experiment setting and you get paid, and you are ordered to perform so… This new kind of experiment should be smth which you will be willing to do, or even, willing to pay to experience through (like gyrodrop! Like amusement park!) So good enough, so overwhelming enough, will-to-power.
The system should be able to accommodate/reflect/react upon unexpected user behaviours → User should have a great degree of freedom, beyond just merely adjusting parameters within pre-defined axes. (Slider Interaction). 
This is reminiscent to the moment when people used 10 sliders to generate an image (our old GAN disentanglement research) but suddenly text-to-image came out and the degree of freedom greatly increased
Still our scope of research should be within ‘golden ratio’ – perhaps should accommodate ratio adjustment? 
Up-down game?
Binary search, hot-cold game
Adaptive methods in psychophysics (e.g., staircase procedures) where the stimulus changes based on user feedback, converging to a threshold (the “just noticeable difference” or the “ideal ratio”).
What if we accommodate the LLM-based ratio adjustment process? User can speak whether the ratio is up or down – The up-down game that we used to do when we guess somebody’s birthday/cell number.
Does not have to be LLM - can be GUI also. Two buttons: Ratio up? Ratio down? 
Pitt’s law – user interaction? When user is navigating through the target – & when target is very small – user does not directly heads to the target, but rather, go backs & forth, 타겟을 앞으로 지나치기도, 뒤로 지나치기도 하면서 점차 범위를 좁혀나간다… but eventually reaches/converges within/nearby the target?
Other approaches?
Adjusting using different modality than slider?
Accelerometer? – phone shaking/smth shaking changes the parameter of the ratio of the visual stimuli?
Hand tracking? – Minority-report-like interaction? Hand direction changes the ratio?
Experiment within apple vision pro? 
Is there example where neuroscience study used apple vision pro/vr?
Eye tracking – eye tracking changes the ratio?
Limitation when we’re going to consider eye tracking as an experiment output variable – the adjusting input and output overlaps
Other approaches?
Conti’d oscillation/navigation btw Abstractive Stimuli ←> Descriptive Stimuli?

What about Fibonacci? Fibonacci-like narrowing down?

Other hypothetical question:

The output of Golden Ratio Research – Should be two fold.

1. Research output - paper, journal publication
2. Interactive (artistic) experience - On top of the experiment setting, but smth more, maybe on the quotation on the essence of golden ratio.

(Explanation of Science/Visualisation) : (Art) = (NN Architecture Vis) : (SoTA) = (Golden Ratio Experiment) : (??????)

??? is the interactive artistic experience – our long term goal.
How to design this? (Not only the problem of narrative, but the matter of system design, state-based approach…)

How to Build an Evolving Interactive Art System (Conceptual Guidance):
You’re aiming for a transformative interaction model where user input doesn’t merely select from predefined outcomes or minorly tweak parameters but rather fundamentally evolves the underlying system or generates new emergent behavior.
Conceptual Foundation:
\t•\tPassive Interaction: Users explore fixed possibilities.
\t•\tActive Interaction: Users shape possibilities dynamically, influencing systemic behavior.
\t•\tEvolving System: User engagement continuously reshapes system logic or behavior.
You’re pushing toward “Level 3 Engagement,” emphasizing intuitive, exploratory interactions inspired by experiments in neuroscience and HCI but extending into immersive, artistic experiences.

Key Principles for Designing Evolving Interactive Systems:
1. Interaction Modality Spectrum:
\t•\tSemantic Explicit (Buttons, GUI)
\t•\tPhenomenological Implicit (Gesture, touch, body language)
\t•\tLanguage-Based (Voice, text, conversational LLM)
\t•\tEnvironmental & Ambient (Sensors, context-aware data)
Combining multiple modalities enriches user engagement and promotes dynamic evolution of system responses.
2. Active Influence over System Logic:
Move beyond user-driven parameter adjustments (like sliders) toward interactions that directly impact or redefine systemic rules, structures, and logic.
Examples:
\t•\tAdaptive Rule Systems: The user’s repeated interactions prompt the system to adjust underlying algorithms (like adaptive psychophysical methods but more radically creative).
\t•\tGenerative AI/LLM: LLM-integration allows user intentions, communicated via language or intuitive gestures, to actively reshape rules or generate entirely new artistic outputs dynamically.
3. Neuroscience-inspired Methodologies:
Adaptive psychophysical approaches (staircase, hot-cold guessing games, Pitt’s law-inspired oscillation around target points) offer meaningful models for achieving active exploration and iterative convergence toward preferences like the golden ratio.
4. Novel Interactive Approaches:
\t•\tNonlinear Interaction: Gesture tracking, shaking (accelerometer), eye tracking (though consider overlap between input-output), VR/AR interaction (Apple Vision Pro or similar).
\t•\tExploratory Navigation: Users navigate abstract vs. descriptive stimuli, oscillating toward self-discovery of preferences.
\t•\tFibonacci-inspired Interaction: Gradual narrowing down interactions following Fibonacci sequences, resonating conceptually with golden ratio research.

Artistic System Design Metaphor:
The scientific experiment metaphor you’re invoking—moving from passive observation toward actively designing experiments—is analogous to moving from traditional, predefined interactive systems toward evolving, emergent interactive art.
Your experimental neuroscience/HCI method → Interactive artistic experience → Emergent creative system (long-term goal)

Example Framework (Golden Ratio Experiment):
Step-by-Step Interaction Approach:
\t1.\tInitial Exploration (Implicit):
\t•\tUser gestures/movements indirectly alter visual stimuli. (Phenomenological)
\t2.\tSemantic Refinement (Explicit Interaction):
\t•\tGUI or voice to narrow down choices explicitly. (Semantic, Language)
\t3.\tEvolving Rules (Adaptive Logic):
\t•\tLLM or generative algorithms adapt, modifying their generation rules based on accumulated user patterns, pushing beyond preset parameters into emergent generative aesthetics.
\t4.\tFeedback Loop (Continuous Evolution):
\t•\tUser feedback continuously reshapes the underlying system logic, not just the visible parameters.

Output Goals (Two-fold):
\t•\tResearch Output: Neuroscience/HCI research paper.
\t•\tArtistic Output: Dynamic, interactive artwork allowing users to experience and contribute to the continuous evolution of the golden ratio aesthetic experience, making the “experiment” itself a captivating artistic journey.
Your long-term goal is designing the second output—an evolving, immersive artistic experience systemically influenced by user interactions.