Unstuck: Charting the Design Space of Generative AI-based Creativity
Interventions
MATTHEW K. HONG, PABLO PAREDES, SHABNAM HAKIMI, MONICA VAN, MATT KLENK, Toyota Research Institute, USA
Myriad generative AI (GenAI) products and research prototypes have demonstrated practical applications for amplifying humancreativity in various professional activities that span writing, music composition, graphic and product design. While many applicationsof GenAI for creativity support focus on augmenting or altering human-generated content, these tools do not directly address the core
challenge of "being stuck", a phenomenon that hinders creatives’ ability to generate original content. In this position paper, we offer
broader perspective on the concept of "being stuck" and insights into how GenAI can be leveraged to overcome barriers in the creative
process. More specifically, we draw from the HCI and Cognitive Science literature to provide a nuanced conceptualization of stuckness
and use this to propose a design space of GenAI-based interventions toward unleashing the potential of creative professionals.
CCS Concepts: • Applied computing → Media arts; • Human-centered computing → Interaction paradigms.
Additional Key Words and Phrases: generative ai, large language models, creativity, intervention

1

INTRODUCTION

While applications of Generative AI (GenAI) have been shown to be useful in supporting everyday creativity such as
creating a new recipe, the latest advances in GenAI technologies, combined with growing market demand for AI-infusedproducts [1], are beginning to truly disrupt professional creativity at a rapid pace. A recent report exemplifies this trend,suggesting that GenAI could potentially automate 26% of tasks in the arts, design, and media sectors [2].
GenAI-based creativity support tools allow individuals to guide text and image as well as audio and video generation
models with various input modalities and UI components to create various augmentations on their seed ideas. These
augmentations offer support for established activities with well-defined success metrics, such as proof editing or text
paraphrasing; they can extend to more complex use cases, such as empowering users to engage in novel creative
endeavors that would not be possible without such technological interventions, such as sketch-guided image synthesis
enabled by diffusion models. This type of support, however, may not be enough to support professional creatives, whose
goals are to (1) generate an artifact that is perceived to be novel, appropriate, useful and valuable by their professional
community (i.e., creative) and (2) push the boundaries of what is known and possible in their respective fields [14].
Creative individuals share unique characteristics that allow them to excel at creative tasks, but not without momentsof decreased performance. While the level of mastery of tools honed over their career often allows them to outperform
AI systems on creative tasks [3], even high-performing individuals using the right tools can become stuck and facea period of diminished creativity and inability to make meaningful progress in their work [15]. Designing creativity
interventions for professional creatives can be challenging because achieving creative leaps and generating truly creative
products often comes at the expense of being ’stuck’—a concept that is not well understood yet prevalent in their lives[8].
To this end, in this paper, we unpack what it means to be stuck, advocate for a greater need toward designingprofessional creativity interventions focused on helping people overcome stuckness, and chart a design space of
GenAI-based creativity interventions aimed at stimulating human cognition and creativity.
Licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). Copyright remains with the author(s).
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Unstuck: Charting the Design Space of Generative AI-based Creativity Interventions

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Fig. 1. The mapping space outlines a spectrum of factors contributing to stuckness, organized along two intersecting dimensions:acute to chronic, and endogenous to exogenous.

2

DEFINING AND CONCEPTUALIZING STUCKNESS

There is no single unified definition or consensus on what it means to be ‘stuck,’ yet it is a common, albeit varied,
experience. Colloquially, expressions of stuckness include creative block, being in a rut, frozen, dried up, burnout,
exhaustion, plateau, and blank canvas syndrome. In cognitive psychology, concepts of stuckness are expressed as
inhibition and resistance, to name a few [12, 17]. Stuckness has been studied extensively in creative cognition and design
research, leading to a culmination of concepts that include impasse, design fixation, functional fixedness, mental set, andpremature conceptualization [4, 7]. Many of these concepts point to the broad notion of stuckness as a hindrance tomental processes due to self-imposed or unconscious inhibition thereof or depletion of cognitive resources necessary
for an individual’s creative pursuit.
Defining stuckness is challenging, but we can broaden our understanding by looking at underlying factors andconditions that accompany stuckness in professional creativity. For example, looking at the intersection of chronicity
and endo-/exogenous factors, we can construct a 2-dimensional mapping space as seen above (Fig 1). Acute factors
are immediate and short-term, often situational, such as fixation on existing designs and time pressure. These arecontrasted with chronic factors, which are persistent and long-standing, including the effects of prior educationand psychopathological illness. The vertical axis represents the origin of these factors, with endogenous on top andexogenous at the bottom. Endogenous factors stem from within the individual, such as mindwandering, negative affect,
amotivation, and burnout. Exogenous factors, on the other hand, arise from external circumstances, including rewards,
distraction, and the quality of environmental sensory stimulation.
While not exhaustive, this map provides a framework for understanding the multifaceted nature of stuckness. Factorsthat influence one’s ability to become stuck can be grouped into different mental—emotional (e.g, negative affect),attentional (e.g., distraction), and motivational (e.g., burnout)—states that are internally and externally triggered, as
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well as varying in duration and intensity. Understanding such complex relationships is key to designing effective
interventions for creativity support.
3

GENAI INTERVENTIONS FOR BUILDING CREATIVE CAPACITY WITHINAs described above, professional creatives often face more challenges than their non-professional counterparts when
they are stuck, primarily due to high expectations set within their industries. Part of this expectation involves exercisingmastery over self-regulation techniques to manage various mental states. At the heart of these challenges is theamalgamation of an intense aversion to stuckness and suboptimal coping strategies that, while intended to mitigate
creativity-induced distress, can paradoxically exacerbate the issues at hand.
For instance, the ironic processing theory posits that deliberate efforts to suppress or avoid specific thoughts andemotions can backfire and lead to an increased focus and rumination about them [16]. In the context of creativity,
attempts to avoid certain thoughts (e.g., distraction) and emotions (e.g., anger)—examples of acute, endo-/exogenous
factors—about one’s work or creative capabilities may amplify the frequency and intensity of these undesired mental
states, leading to a counterproductive cycle that stifles creativity. Procrastination is another common manifestationof a maladpative coping mechanism that is often rooted in perfectionism (chronic, endogenous factor) [6]. Creative
individuals, aiming for flawless execution, may delay tasks due to a fear of falling short of their own high standards. Thisdelay not only impacts their creative processes but also contributes to chronic stress and anxiety, further complicating
the ability to self-regulate.
Addressing these challenges require new approaches to creativity support that focus on strengthening individual’scapacity for self-regulation, in addition to directly contributing to the generation of creative products. Interventions inthis realm could include mindfulness training, cognitive-behavioral strategies to tackle perfectionism, and techniques
to enhance emotional resilience. Below we discuss how GenAI might support the design of these interventions.
3.1

Affordances of GenAI for Intervention Design

With its ability to recognize patterns in existing data and generate new data, GenAI offers a unique set of affordances[11] that, when combined with other technologies, has the potential to maximize the effectiveness of interventions
aimed at helping professional creatives combat stuckness. In this paper, we discuss three such affordances that could
lead to improved engagement with the interventions.
Reducing Boredom and Habituation. Habituation refers to a reduction in physiological and behavioral responses
toward certain stimulus after prolonged and repeated exposure to it. In the context of intervention design, boredom andhabituation are primary drivers of reduced effectiveness in long term deployments. Changing the form, presentation,and timing of content delivery with GenAI can be an effective strategy for increasing or sustaining user engagement[10]. For example, instead of cycling through a bank of media content, GenAI can help produce unexpected patterns
within distinct families of stimuli and content to reduce habituation and boredom. Adjusting the temperature parameter
would allow for greater control over when to reduce or increase predictability in the presented content.
Personalization. Another way to improve the effectiveness of interventions is to improve the contextual relevance ofthe presented content. Research in HCI has shown that personalization can be a helpful strategy to increase the efficacy
of interventions [13]. Drawing on contextual data about the individual such as demographic attributes, preferences,behavioral and mental states, GenAI can dynamically produce tailored messages, recommendations, or other content
that resonate with the individual’s current context. This can enhance engagement and the relevance of interventions,
ultimately increasing their effectiveness in the long run.
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Unstuck: Charting the Design Space of Generative AI-based Creativity Interventions

Shared autonomy
Interruptions
Peripheral
No workflow
interruption

Just-in-time (JIT)
Minimal workflow
interruption

OfflineComplete workflow
interruption

Hong et al.

Assistive
Increasingly human-led, with data
presentation

NegotiatedMixed or conditional autonomy,
with decision support

Autonomous
Increasinglya machine-led

Slow breathing while working.

Slow breathing while working
with sensory stimuli.

Slow breathing while working,with adjustments to sensory
stimuli.

GenAI provides minimal
assistance with varying forms ofdata presentation

GenAI generates pleasant haptic/
audio/ visual displays synced withbreathing, offering personalizationon the go.

Small break to breathe fresh air.

Small break to breathe fresh air.

If requested, GenAI can propose a
new breathing pattern or
voice-guided breathing activity.

GenAI proposes and modifies thebreathing metaphor, e.g., “Aye,mate, let’s breathe like a pirate!”

Deep breathing exercises in a
mindfulness class.

Immersive “awe” room withmultimodal stimuli to modify BR
and inspire.

If requested, GenAI acts as a DJ
and generates backgroundaccompanying music.

GenAI generates personalized andinspirational multimedia “awe”
content that changes invariably.

GenAI initiates BR adjustment via
gradual modulation of music
volume or BPM.
The system interrupts work andoverlays a short breathing
guidance video.
GenAI creates a tailor-madeguided breathing video.
The system changes theworkplace environment (deskheight, temperature, lights,
music), to change tonic BR.
GenAI chooses the mix ofenvironmental parameters.

Table 1. Example of a GenAI delivery method for negative affect regulation modulated by slow breathing

Interactive and Immersive experiences. Chronic manifestations of stuckness (e.g., perfectionism) may require
prolonged exposure to a rich set of experiences that can be difficult to design, scale, and maintain. Given the rapid
emergence of multimodal generative models (e.g., Google Gemini1 , Open AI Sora2 ), we can expect GenAI to create richdigital experiences that provide proxy simulations of the physical world tailored to the user’s preference, state and othercontext. This can include partial to fully immersive environments, or other interactive content, which can increase
motivation and intervention efficacy over static content [5]. On the other hand, GenAI can also alter our perceptions ofreality by introducing subtle changes to the individual’s surrounding environment [9]. Adding subtle animations to
the periphery of a computer screen, or changing the volume, pitch, bpm of music that is being played are examples inwhich GenAI can offer subtle changes without introducing huge disruptions to ongoing creative activities.
3.2

Morphology and Delivery of GenAI Interventions

To deliver GenAI interventions with different intensity, frequency, and duration levels, they should be designed taking
into consideration at least two elements: level of interruption and shared autonomy. Interruption levels can vary fromnone (peripheral), minimal (just-in-time), to complete (taking the user offline) interruption. On the spectrum of sharedautonomy, interventions can be assistive (increasingly human-led), negotiated (either low autonomy or conditionallyautonomous depending on the situation), or autonomous (increasingly machine-led). A potential third element, the1 https://gemini.google.com/
2 https://openai.com/sora

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Unstuck: Charting the Design Space of Generative AI-based Creativity Interventions

Shared autonomy
Interruptions
Peripheral
No workflow
interruption

Hong et al.

Assistive
Increasingly human-led, with data
presentation

NegotiatedMixed or conditional autonomy,
with decision support

Autonomous
Increasinglya machine-led

Remind user of the current role
they are playing (e.g., detective).

Suggest different roles users canplay (e.g., space detective,archeologist, etc.).

Eliminate distracting elements
and make the work environment
linked to a role-playing character.

GenAI proposes and generates
soundtracks or character themesthat reinforce the alternative rolethat the user chooses to play (e.g.,Noir music for a detective role).

GenAI changes the work space toresemble the world of therole-playing character andmodifies the focus of the task
(blurs in/out).

Small break to practice adopting
a new role.

Small break to iterate on various
ways to assume the new role.

Display and project assumed role
onto live video feed (e.g.,
instagram detective filter).

GenAI proposes and generates a
few speech dialogues of the user
demonstrating the role in different
ways.

The system interrupts distracted
work and takes user through a
guided, immersive role playscenario.

Practice adopting new role infully immersive environment(e.g., VR) away from any
workspaces.

Enacting role in a partially or
fully immersive environment
with multimodal stimuli.

System displays assumed role

Just-in-time (JIT)
Minimal workflow
interruption

OfflineComplete workflow
interruption

User selects from pre-generated
avatars, objects, scenery, musicthat complements the assumed
role.

GenAI proposes and generates
different role-play scenarios forusers to experience that becomes
more challenging as the user
grows into their role (e.g., more
complicated cases as the user
learns how to be a detective).

GenAI scaffolds social interactions
that allow the user to play the rolein different scenarios (e.g., GenAI
plays an assistant detective asking
the user about the case, such as a
Watson to the user’s Sherlock).
The system interrupts distracted
work with a countdown andprimes the person to engage in a
fully immersive experience.
GenAI chooses the best
combination of environmental
parameters and the role-playing
metaphor.

Table 2. Example of a GenAI delivery method for regulating perfectionism modulated by role-playing exercises

level of immersion (uni- to multi-modal), usually depends on the limitations imposed by the prior two. Tables 1 and
2 illustrate examples of different intervention morphologies and delivery mechanisms to manage negative affect andperfectionism.
An essential intervention design consideration is how to maximize long-term adherence. Combining GenAI withother mechanisms, such as reinforcement learning, allows for automatic personal and contextual dynamics segmentation
to improve long-term adherence. For example, a multi-armed bandit algorithm could explore a suite of just-in-time
interventions (e.g., breathing, stretching, cognitive re-framing, etc.). As it converges and exploits successful interventions(e.g., breathing), GenAI could modify the intervention metaphor to make them more appealing (e.g., breath as if you are
under water, or like a sailor against the wind).
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Finally, as mentioned earlier, our aim is to support individuals build capacity for self-regulation by gradually andadaptively tapering off system autonomy toward restoring control back to human-led levels.
4

CONCLUSION

In this paper, we describe an early foray into mapping the design space of GenAI-based creativity interventions to
support creative professionals overcome stuckness. For future work, we aim to develop a suite of interventions thatbuild upon this design space.
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