When is a Tool a Tool? User Perceptions of System Agency in Human–AI Co-Creative Drawing
Open accessAbstract
This paper presents an analysis of the user experience of Reframer, a novel human-AI drawing interface designed with the iterative and reflective nature of creativity in mind. Collaboration with Reframer occurs in real time, with the user and the system drawing together concurrently. This approach is inspired by theories of creativity as being more problem-framing than problem-solving, and contrasts with the automated one-shot end-to-end workflows of most generative AI models. A 12-participant qualitative exploratory study of the capabilities of our prototype is detailed, as well as a thematic analysis of user attitudes towards drawing with it. The paper then describes two modified prototypes and a second 32-participant comparative study revealing how interface variations evoke differences in user attitudes and experiences. It concludes by proposing a model that characterises the conditions under which users experience co-creative AI as a collaborator, rather than a non-agentive tool.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
0 of 36 cited sources checked · 0 supported · 0 flagged
- Findingown data
User testing indicated that branching and separate histories did not offset the loss in familiarity of a simple shared history.
“In the end user testing indicated the additional capability of branching and separate histories did not ofset the loss in familiarity of a simple shared history.”
Quote in the paperSubstantial claim - Findingown data
Eleven participants were observed applying traditional visual principles to canvas elements as part of meaning-making.
“Almost all participants (11) were observed applying traditional visual principles (such as Gestalt principles like closure, continuation, and symmetry) to elements in the drawing canvas as part of a meaning-making process.”
Quote in the paperNot a substantial claim - Findingown data
Many participants felt Reframer's drawings were childish.
“Many of these opinions fell into the category of feeling Reframer's drawings were childish.”
Quote in the paperNot a substantial claim - Findingnone given
Most participants were able to learn and adapt to the system quickly.
“Regardless, most participants were able to quickly learn and adapt to the system.”
Quote in the paperNot a substantial claim - Findingown data
Many of these frustrations related to mismatches in prompt interpretation between participant and system.
“Many of these were related to mismatches between interpretations of the prompt: the participant meant it one way, but the system interpreted it another.”
Quote in the paperNot a substantial claim
- Findingown data
Participants with prior experience of other generative AI tools commonly expected Reframer to produce realistic, high-quality output from their sketches, even after being told it was a collaborative sketching tool.
“Among those with some experience of other generative AI tools it was a common belief that Reframer would produce realistic, high-quality output based on their sketches, even after we explained it as a collaborative sketching tool.”
Quote in the paperNot a substantial claim - Findingown data
Despite initial mismatches in expectations, most participants reached a state where their relationship with Reframer could be called collaborative and creative.
“Despite these initial expectation mismatches, most of our participants were able to reach a state where their relationship with Reframer could be described as collaborative and creative.”
Quote in the paperSubstantial claim - Findingown data
The studies found that Reframer's fluidity, physicality, and ability to produce serendipitous and unexpected discoveries led to moments of agentive engagement.
“Our studies found that Reframer's fuidity, physicality, and capacity for serendipitous and unexpected discoveries resulted in moments where users engaged with it in an agentive fashion.”
Quote in the paperSubstantial claim - Findingown data
Almost all participants (11) adapted their design approach to work with Reframer.
“Participants developed new ways of working with Reframer, with almost all (11) adapting their design approach to work with it.”
Quote in the paperNot a substantial claim - Findingown data
Eleven participants reported that Reframer made changes that improved the drawing.
“Most participants (11) reported that Reframer made changes that improved the drawing.”
Quote in the paperNot a substantial claim - Findingown data
These limitations mainly concerned the AI's ability to understand intent and its expected precision drawing abilities.
“These mainly related to defciencies in the AI's ability to understand intent and/or its expected precision drawing abilities.”
Quote in the paperNot a substantial claim - Findingown data
Participants used traditional visual principles to interpret Reframer's abstract compositions, seeing colour palettes, line arrangements, and written letters.
“This enabled them to interpret Reframer's abstract compositions, seeing colour palettes, line arrangements and even written letters.”
Quote in the paperNot a substantial claim - Findingown data
Participants reported that the system had its own perspective and was steering the collaboration to some extent.
“Participants reported that the system had its own perspective, and was to an extent steering the collaboration.”
Quote in the paperSubstantial claim - Findingown data
A majority of participants saw Focus Regions as a way to tame Reframer's abstraction and gain more control, especially those who had it for Task A.
“A majority of participants viewed the Focus Regions as a way to tame the abstraction of Reframer and induce more control, particularly those who had access to that feature for Task A.”
Quote in the paperSubstantial claim - Findingown data
Users adopted behavioural strategies for working with Reframer.
“Users also adopted behavioural strategies for working with Reframer.”
Quote in the paperNot a substantial claim - Findingown data
Many participants held incorrect assumptions that required correction, such as expecting the system to autocomplete drawings or to take turns drawing with them.
“Along the way, there were many incorrect assumptions that needed to be corrected -some users thought the system would”
Quote in the paperNot a substantial claim - Findingown data
Across all experimental conditions, participants showed a tendency to see the Reframer interaction as collaborative to some degree.
“Participants in all conditions tended towards viewing the Reframer experience as at least partly collaborative.”
Quote in the paperSubstantial claim - Findingown data
Study participants clearly experienced mixed-initiative cocreativity as unfamiliar and even confronting.
“The participants in our study clearly found mixed-initiative cocreativity unfamiliar and even confronting.”
Quote in the paperSubstantial claim - Findingown data
Every participant described at least one limitation of Reframer.
“Despite its successes at triggering mixed-initiative co-creative drawing, every participant described at least one limitation of the Reframer system.”
Quote in the paperNot a substantial claim - Findingown data
There were substantial differences in experience between the two tasks, independent of order and interface version.
“There were substantial diferences in the experience of using Reframer to complete the two tasks in this study, independent of both the order in which they were done and the interface version used.”
Quote in the paperSubstantial claim - Findingown data
The introduction of ideas by the system was identified as a major factor behind the perception of collaboration.
“The interjection of ideas was identifed as a signifcant driver of this belief:”
Quote in the paperSubstantial claim - Findingown data
Another strategy was local pruning, removing parts of the drawing where the system was unproductive.
“Another strategy was local pruning -removing portions of the drawing where the system was being unproductive.”
Quote in the paperNot a substantial claim - Findingown data
Participants sought ways to influence and control the system directly.
“Participants sought ways to infuence and control the system directly.”
Quote in the paperNot a substantial claim - Findingown data
Participants found the system better at smaller, more basic prompts, whose results could be scaled and composed.
“Participants found the system better at working on smaller, more basic prompts, the results of which could then be scaled and composed.”
Quote in the paperNot a substantial claim - Findingown data
Participants formed assumptions about the AI based on preconceived ideas.
“Participants made assumptions based on preconceived notions about AI.”
Quote in the paperNot a substantial claim - Findingown data
Ten participants experienced continued uncertainty about some Reframer features.
“There were aspects of Reframer which caused continued uncertainty among the majority of participants (10).”
Quote in the paperNot a substantial claim - Findingreasoning
Reframer did at times become present-at-hand because it failed to perform its desired function.
“which certainly did occur with Reframer at times.”
Quote in the paperNot a substantial claim - Findingown data
Other users decomposed the task into smaller pieces, such as drawing a cat and then a sofa rather than a cat on a sofa, to simplify it for Reframer.
“Other users decomposed the task into smaller pieces (e.g.drawing a cat, and then a sofa, rather than”
Quote in the paperNot a substantial claim - Findingown data
From the user studies, the authors identified four stages of the cocreative experience.
“From our user studies we have identifed four stages of the cocreative experience, seen in Figure 14.”
Quote in the paperSubstantial claim- The authors state this as an assumption: Users' expectations about human-agent interaction derive from their assumptions and prior experiences with creative software and AI tools.
- The authors state this as an assumption: Agentive flow is critical to co-creative interactions.
- Findingown data
When users did not just leave the AI off, thereby staying in tool-supported flow, most strategies for mediating disruption were based on trying to re-set the AI's behaviour, deleting or adding strokes, modifying the prompt, and marking strokes as user-owned, then restarting the AI.
“In our case, when users did not just leave the AI of (thereby staying in tool-supported fow), most strategies for mediating disruption were based on trying to”
Quote in the paperSubstantial claim - Findingown data
A number of users came in expecting high-fidelity, realistic and complete drawings, and those expectations initially clashed with the design of Reframer.
“We found a number of users came in expecting high-fdelity, realistic and complete drawings, and those initially clashed with the design of Reframer.”
Quote in the paperSubstantial claim - Premisecitation
In creative processes, people discover what they were looking for only through searching.
“Psychology tells us that, in creative processes, it is only through searching that we can discover what we were looking for all along [14,20].”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [14]
Not checked in the free run.
- cites [20]
Not checked in the free run.
- Premisecitation
Creative processes involve a co-evolution of problem-framing and problem-solving, functioning as a reflective dialogue between designer and medium.
“Creative processes are a co-evolution of problem-framing (fguring out what to do) and problem-solving (actually doing it), a kind of refective dialogue between the designer and their medium [38,50].”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [38] source
Not checked in the free run.
- cites [50]
Not checked in the free run.
- Interpretationreasoning
The end-to-end approach of generative AI conflicts with established knowledge about creative cognition.
“These technologies are certainly revolutionary, but the end-to-end approach is completely at odds with what we know about creative cognition.”
Quote in the paperSubstantial claim - Premisecitation
Mixed-initiative interfaces conflict with traditional design patterns of creativity support systems, which include being maximally unobtrusive to promote and sustain user engagement.
“While clearly intended to augment creativity, this puts mixed-initiative interfaces at odds with the traditional design patterns of creativity support systems, which include being maximally unobtrusive in order to promote and sustain user engagement [51].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [51] source
Not checked in the free run.
- Interpretationown data
The system's ability to optimise toward a compelling, prompt-matching sketch was sometimes hampered by the local nature of the CICADA vector-based optimiser.
“In some cases the system's ability to optimise towards a compelling and high-quality sketch that matched the provided prompt was hampered by the local nature of the CICADA vector-based optimiser.”
Quote in the paperNot a substantial claim - Interpretationown data
The results suggest that understanding how and when users perceive the system as a tool or an agent requires nuance, even within one study of one system.
“This suggests the nuance required to understand how and when -even within a single study of a single system -users perceive it as a tool or an agent.”
Quote in the paperSubstantial claim - Premisecitation
Mixed-initiative systems, by definition, conflict with the long-standing creativity-support design principle of maximal unobtrusiveness.
“Almost by defnition, mixed-initiative systems violate the principle of maximal unobtrusiveness that has long been a hallmark design principle for creativity support systems [51].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [51] source
Not checked in the free run.
- Premisecitation
Existing models of co-creative interaction are descriptive, focusing on articulating what influences co-creativity and/or what comprises it.
“Existing models of co-creative interaction are descriptive, focusing on articulating what infuences co-creativity [27] and/or what comprises it [13].”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [27]
Not checked in the free run.
- cites [13] source
Not checked in the free run.
- Interpretationreasoning
When agentive flow occurs, Reframer is encountered not as a tool for drawing but as a tool for creating.
“When agentive fow occurs, Reframer is not encountered as a tool for drawing, but as a tool for creating.”
Quote in the paperSubstantial claim - Interpretationcitation
In M-CAF, potential disruptors of agency are distributed, emerging out of interactions between system and user.
“In M-CAF, potential disruptors of agency are distributed, in that they emerge out of interactions between system and user.”
Quote in the paperSubstantial claim
- May combine two claims. 41
- Classified as probably not a substantial claim. 39
- The quote only partly states this claim. 2
May combine two claims.
Findingown dataIn the pruning approach, drawing quality was better, but users could not understand why some strokes were disappearing.
“Drawing quality was better, but users were unable to understand why some strokes were disappearing, and the feature was removed.”
Quote in the paperSubstantial claimMay combine two claims.
FindingcitationStarting the human-AI collaboration from its most dense and abstract place was not a deterrent to users, who enthusiastically created order from chaos through exploratory sketching.
“We found that starting the human-AI collaboration from its most dense and abstract place was actually not a deterrent to our users, who enthusiastically took on the task of creating order from the chaos through exploratory sketching [20,56].”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [20]
Not checked in the free run.
- cites [56]
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
FindingreasoningThe small size of vector-based sketches sent between client and server makes the interface responsive and fluid even with a few hundred strokes on screen on high-end 2022 hardware.
“The small size of the vector-based sketches being sent back and forth between client and server makes the interface responsive and fuid even with a few hundred strokes on screen (on high-end 2022 hardware).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataWhether the reveal was fast or slow, it distracted users from drawing, especially when they were focused on a different section of the drawing.
“Whether the reveal was fast or slow, it seemed to distract users from drawing, particularly when they were focused on a diferent section of the drawing.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingnone givenThese perceived perspectives were often valuable contributions.
“These perspectives were often valuable contributions.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataMany participants initially found Reframer confusing because it was unfamiliar, but its manageable learning curve increased their confidence with practice, though some uncertainty persisted due to ongoing issues.
“Many participants experienced initial confusion with Reframer due to unfamiliarity, but its manageable learning curve bolstered their confdence with practice, although there was some prolonged uncertainty from persistent issues.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataUsers could often resolve local minima by making larger structural changes, but sometimes the system seemed uncertain how to proceed.
“In many cases this was resolvable by the user taking the initiative and making larger structural changes, but in some instances the system seemed uncertain about how to proceed.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataAll participants expressed opinions about Reframer's drawing style and how they worked with it to achieve their goals.
“All participants expressed opinions about Reframer's drawing style and how they worked with it to achieve their goals.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataOne strategy was dividing the task into smaller activities to reduce Reframer's abstraction.
“One was to divide and conquer the task by reducing the scope of individual activities (and thus also Reframer's propensity for abstraction).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataThe existing themes captured second-study quotes as well as first-study quotes, allowing them to be used as an analytical lens.
“We found that the existing themes captured participant quotes from the second study as well as they had in the frst, allowing us to use them as a lens to analyse the experiences of our participants across the two tasks and interface variants.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataMany cooperative strategies involved imposing additional control when AI contributions became unhelpful, marking a transition from agentive interaction to tool-like use.
“Many of these strategies involved imposing additional control when the AI's contributions became unhelpful, and involved a transition from agentive interaction to tool-like use.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataAlmost all users experienced an agentive view of the interaction, yet every user had to suppress the system's agency and treat it as a tool at least sometimes.
“Our studies showed that this”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataFocus regions worked well when used to create separate objects within a scene, which was more common in Task A.
“Focus regions worked great when users were using them to create separate objects within a scene -which was much more common in Task A.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataThe analysis produced a bottom-up hierarchy of 8 high-level themes, 19 sub-themes, and 54 codes.
“These were analysed to construct a bottom-up hierarchy constituting 8 high-level themes, constructed from 19 sub-themes, across 54 codes.”
Quote in the paperNot a substantial claimMay combine two claims.
FindingcitationThese agentive periods were not disruptive despite the system's interjections; overall they were perceived as flowy and highly engaging.
“These periods were not disruptive despite the system's interjections, instead they were (as a whole) perceived as fowy [10] and highly engaging.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [10]
Not checked in the free run.
May combine two claims.
Findingown dataAll 12 participants gave mostly positive reviews, but few were unambiguously positive.
“All our participants (12) gave some kind of mostly positive review, but few unambiguously so.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataThe first study's thematic analysis of 12 participants yielded 656 quotes from 746 minutes of transcribed audio.
“Our thematic analysis of the 12 participants from our frst study extracted 656 quotes from 746 minutes of transcribed audio recordings.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataReframer's reliance on gradual development and emergence sometimes worsened the issue, because chaos sometimes resolved into valuable contributions and sometimes did not.
“The reliance of the Reframer system on gradual development and emergence sometimes exacerbated this issue, as sometimes the chaos would resolve into valuable contributions, and other times it would not.”
Quote in the paperNot a substantial claimMay combine two claims.
FindingreasoningWhen it did not cause disruption, Reframer was seen as more tool-like when Focus Regions were used and more agentive when they were not.
“supports the idea that -at least when it did not lead to disruption -Reframer was perceived as more tool-like with Focus Regions, and more agentive without them.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataBehaviour sliders were used as a strategy but were opaque to a number of users.
“Other strategies involved the use of the behaviour sliders (visible on the bottom left of Fig. 3), but these were opaque to a number of users.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataEleven participants said they managed the system's learning curve and became confident after practice.
“However, almost all participants (11) conveyed that they were able to manage the system's learning curve, allowing them to become confdent after some practice.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn Task B, users often used focus regions for connected components of a larger object, and the resulting images tended not to cohere.
“In Task B, however, users often used the regions to defne connected components of a larger object such as a car, and in this case the resulting images tended not to cohere.”
Quote in the paperSubstantial claimMay combine two claims. The quote only partly states this claim.
Findingown dataTen participants showed explicit sketch planning, vocalising what and how to draw.
“Explicit sketch planning was observed in most participants (10).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataAll statements in the creative differences category required some adaptation by participants, though not all were criticisms.
“Not all of the statements coded into this category were criticisms, but they all required some kind of adaptation on the participant's behalf.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataNegative feedback focused on confusion, lack of professional applications, and speed.
“Negative feedback tended to focus on confusion, lack of professional applications, and speed.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataSome participants compared the mutual inspiration they felt to a human-human partnership, while others considered it at least more than mere tool use.
“This experience of mutual inspiration was likened to human-human partnership by some, or at least going beyond tool-use by others.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataTen participants reported that Reframer had its own design perspective that aligned with their goals, enhanced feedback, and offered options to explore.
“Since the system was able to meaningfully change and infuence the sketch, participants (10) reported that Reframer had its own design perspective, one that that aligned with their design goals, enhanced feedback, and ofered options to explore.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataSome of Reframer's changes pushed participants away from their intended concepts, forcing reflection and adaptation.
“Some of Reframer's changes clearly pushed participants away of their intended concepts, forcing refection and adaptation.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThere was a tradeoff between increased control with Focus Regions and increased serendipitous discovery without them.
“We observed a kind of tradeof between an increase in control with Focus Regions and an increase in serendipitous discovery without them.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataIn Reframer, disruptors of agency included low-level issues such as strokes getting stuck in local minima and left as scribbles with no clear purpose, and conceptual ones such as overwhelming the user with too much noise, or refusing to acknowledge a user's pivot in creative concept and constantly trying to revert the drawing.
“In Reframer, this included both low-level issues (such as some strokes getting stuck in local minima and being left on the canvas as”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThese disruptors tended to cause the user to stop the AI drawing, ending real-time fluid collaboration.
“These tended to cause the user to stop the AI drawing, ending real-time fuid collaboration.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataWhile most participants realised those assumptions were wrong and corrected them, a small fraction never got past the abstract, childish nature of Reframer's chaotic drawing process and were much more likely to prevent it from acting on their drawing.
“While most participants realised those assumptions were wrong and corrected, a small fraction never got past the abstract,”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataUsers who were able to suspend their disbelief and accept Reframer as a collaborator and peer were more likely to end up in agentive flow, as were those more open to changing their ideas.
“In our case, those able to”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataReframer facilitates fluid, real-time shared drawing experiences with a generative AI, and the studies indicated this novel interaction paradigm enables a bi-directional exchange of ideas between its users and the AI system.
“Reframer facilitates fuid, real-time shared drawing experiences with a generative AI, and our studies indicated this novel interaction paradigm enables a bi-directional exchange of ideas between its users and the AI system.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataReframer users, particularly those who had experienced agentive flow, were most positive about the spontaneous emergence of serendipitous forms or ideas that it triggered, and that capability drove them to adopt an agentive perspective.
“Reframer users, particularly those who had experienced agentive fow, were most positive about the”
Quote in the paperSubstantial claimThe quote only partly states this claim.
Findingown dataThe four stages are: expectations, co-creative agentive flow, tool-supported creative flow, and reflections.
“The four stages are as follows:”
Quote in the paperSubstantial claim- The authors state this as an assumption: Users' expectations about human-agent interaction derive from their assumptions and prior experiences with creative software and AI tools.
- The authors state this as an assumption: Agentive flow is critical to co-creative interactions.
May combine two claims.
Findingown dataThrough thematic analysis, the authors established that users move between agentive and non-agentive creative flow states as they adapt to and are disrupted by a tool's functions, with different features helping at some points and hindering at others.
“Through our thematic analysis, we established users move between agentive and non-agentive creative fow states as they adapt to and are disrupted by a tool's functions, with diferent features helping at some points in the process and hindering at others.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataMost users adopted strategies of letting the AI have more agency early in the process as forms and concepts were emerging, but then tapering its agency through adjusting parameters or just turning it off as the task progressed.
“Most users adopted strategies of letting the AI have more agency early in the process as forms and concepts were emerging, but then tapering its agency through adjusting parameters (or just turning it of) as the task progressed.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThis mutual influence can create moments of serendipitous discovery and design reformulation, which both delighted users and contributed to their overall positive experiences.
“This mutual infuence can create moments of serendipitous discovery and design reformulation, which both delighted our users and contributed to their overall positive experiences.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningNew interaction paradigms grounded in how human creativity operates are necessary for generative AI to augment human creativity.
“New interaction paradigms will be required before generative AI can realise its potential to augment human creativity, ones that are grounded in the way human creativity operates in practice.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductcitationThe six phases of thematic analysis were iteratively moved between until thematic saturation was reached.
“In practice, the six phases were iteratively moved between until thematic saturation was reached [48].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [48]
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationWhen a co-creative AI system is perceived as an agentive collaborator rather than a tool, it is seen as having a level of creative responsibility.
“Given this efcacy of humanhuman collaboration, it is thus perhaps unsurprising that when a co-creative AI system is perceived as being an agentive collaborator (rather than a tool), it is seen as possessing a level of creative responsibility [7].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [7]
Not checked in the free run.
Classified as probably not a substantial claim.
PremisecitationA precise and broadly agreed-upon operationalisation of what makes a creative AI system co-creative has eluded the field to date.
“A precise and broadly agreed-upon operationalisation of what makes a creative AI system co-creative has eluded the feld to date, playing into a broader dialogue about the complexity of evaluating of co-creative systems [30,34].”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [30]
Not checked in the free run.
- cites [34]
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductcitationTwo additional independent researchers were brought in for workshops during the theming, review and definition phases to provide investigator triangulation.
“Two additional independent researchers were brought in for workshops during the theming, review and defnition phases to provide investigator triangulation [2] and increase comprehensibility and cohesion.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [2] source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationFree and open collaboration increases creativity in software development, musical improvisation, and engineering design.
“Free and open collaboration has been shown to increase creativity in felds as diverse as software development [59], musical improvisation [49], and engineering design [59].”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [59] source
Not checked in the free run.
- cites [49]
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown dataParticipants were given non-sequential IDs to blind analysts, some of whom were also experimenters.
“Participants were given non-sequential IDs in order to blind analysts (some of whom were also experimenters) and quotes are denoted as either being in the exploratory frst study (ES) or the comparative second study (CS) followed by their IDs.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe conflict between direct manipulation and agent-based interaction models is at least three decades old in the HCI community.
“The confict between direct manipulation and agent-based interaction models is at least three decades old in the HCI community [23,37], but it posed questions that remain unresolved for co-creative systems: how can a system be both unobtrusive and interjective?”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [23]
Not checked in the free run.
- cites [37]
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationCollaboration is essential for solving real-world creative problems at almost any scale.
“Collaboration has been called essential for solving real-world creative problems at almost any scale [44].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [44]
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationDuring conceptual design, unexpected discoveries can prompt new requirements and further discoveries and creativity.
“During conceptual design, unexpected discoveries often prompt the invention new requirements, which may in turn lead further unexpected discoveries and (potentially) creativity [53].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [53] source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenParticipants from the first study were not allowed to participate in the second study.
“Participants from the frst study were not allowed to participate in the second study.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenThe same experimental setup was used, with the Wacom attached to a high-end workstation.
“The same experimental setup was used, with the Wacom attached to a high-end workstation.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationFirst-glance exploration helps users form a base understanding of a new system's layout and functions.
“First-glance exploration helps users form a base understanding of a new system's layout and functions [42].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [42]
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
InterpretationcitationInteracting with Reframer feels embodied and enactive, with the drawing as part of a dialogue between creator and medium.
“This makes interacting with Reframer, like the Drawing Apprentice before it, feel embodied and enactive [11], with the drawing as part of a dialogue between creator and medium.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [11] source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationIn team design, unexpected discoveries can come from productive ambiguities between team members.
“In team design these unexpected discoveries can come from productive ambiguities between team members [39].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [39] source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationDesigners think while sketching through embodied perceptual and cognitive means.
“In drawing literature, researchers have articulated the embodied perceptual and cognitive means through which designers think while they sketch [20].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [20]
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductnone givenAudio was transcribed algorithmically, with errors corrected during coding.
“Audio was transcribed algorithmically, with errors corrected during coding.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenAll participants consented to the collection and use of their data.
“All participants consented to the collection and use of their data.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationDesign is characterised by a formulate-act-reformulate reflective cycle.
“This was often interspersed with the other visual sub-themes of meaning making and experimentation as participants engaged in the formulate-act-reformulate refective cycle that is known to characterise design [50].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [50]
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataThe second study compared two interface variations on two drawing tasks, counterbalancing tool, task, and order.
“In our second study, after additional refnements to the Reframer interface (see Section 3), we compared two diferent variations of the interface on two diferent drawing tasks, counterbalancing for tool (i.e.interface), task, and order (see Section 4).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationShared creative flow states have been previously discussed in human-human co-creation, including collaborative flow in rap music and joint performance or togetherness in improvisational dance.
“As mentioned this is not an entirely new idea, as shared creative fow states have been discussed before in human-human co-creation, such as collaborative fow in rap music [32] and joint performance or”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [32]
Not checked in the free run.
- cites [41]
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductnone givenEffort was made to select participants from diverse cultural and ethnic backgrounds, as well as diversity in the programs they were enrolled in.
“Efort was made to select participants from diverse cultural and ethnic backgrounds, as well as diversity in the programs they were enrolled in (architecture, interaction design, etc).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationHumans and machines in mixed-initiative systems often become entangled in tight feedback loops with shared initiative.
“Working with the curated outputs of mixed-initiative systems, humans and machines often become entangled in tight feedback loops in which initiative is shared [13].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [13] source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductcitationThe thematic analysis followed a six-phase structure of familiarisation, coding, theming, review, definition, and documentation.
“The thematic analysis process following a six-phase structure of familiarisation, coding, theming, review, defnition, and documentation [5,52].”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [5] source
Not checked in the free run.
- cites [52]
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenNo participants had prior knowledge of the research project.
“No participants had prior knowledge of the research project.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationown dataThe authors propose a new interaction modality, at least new for co-creative AI, that is both mixed-initiative and supportive of creativity, which they call agentive flow.
“From this we posit a new -or at least new to co-creative AI -modality for interaction that is simultaneously mixed-initiative and creativity-supportive: agentive fow.”
Quote in the paperSubstantial claimMay combine two claims.
Interpretationown dataThe system not only extended participants' existing concepts but also challenged them to reframe their ideas, which was often valuable.
“This shows that the system did not only extend participants existing concepts, but also challenged them to reframe their ideas -and this was often valuable.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningTask B had less openness to sketchy spatial ambiguity, making users less tolerant of the system taking action.
“Task B had less openness to the kind of sketchy spatial ambiguity that Reframer lends itself to, making users less tolerant of it taking action.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
InterpretationreasoningThe sliders' opacity may have been worsened because they did nothing when the AI was not drawing, as they mediated agent behaviour rather than directly affecting the drawing.
“This may have been exacerbated by the fact that the sliders did nothing when the AI wasn't already drawing, because they mediated agent behaviour rather than afect the drawing directly.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataThe qualitative comparison used the first study's codebook to triangulate the quantitative results.
“As a supplementary qualitative comparison to triangulate those results, we used the codebook from our frst study's thematic analysis to compare the diferent conditions in our second study.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationActivity theory emphasises the dynamic, constructive and socio-culturally grounded nature of both our tasks and the tools with which we enact them.
“Activity theory emphasises the dynamic, constructive and socio-culturally grounded nature of both our tasks and the tools with which we enact them -an infuence seen in M-CAF's central cycle between agentive and nonagentive interactions.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [28] source
Not checked in the free run.
Probably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningAs the locus of creativity moves from the individual human to the human-AI nexus, being ready-to-hand requires being attentive, responsive and even interjective in order to support the refinement of ideas.
“Within that broader scope, as the locus of creativity moves from the individual human to the human-AI nexus, being”
Quote in the paperNot a substantial claim- Rests on an assumption: Heidegger's account of tools as embodied functions that become ready-to-hand is an accurate description of tool use.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe theory of distributed cognition holds that perception, reasoning and action are properties of networks of actors, both organic and otherwise.
“The theory of distributed cognition holds that perception, reasoning and action are properties of networks of actors, both organic and otherwise.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [22] source
Not checked in the free run.
May combine two claims.
Interpretationown dataM-CAF is a state model of interaction with creative AI: users start in the first state, then cycle between states 2 and 3, before ending up at state 4.
“M-CAF is a state model of interaction with creative AI: users start in the frst state, then cycle between states 2 and 3, before ending up at state 4.”
Quote in the paperSubstantial claim- The authors state this as an assumption: Users' expectations about human-agent interaction derive from their assumptions and prior experiences with creative software and AI tools.
- The authors state this as an assumption: Agentive flow is critical to co-creative interactions.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationM-CAF builds on theories previously applied in HCI, such as activity theory and distributed cognition.
“In this way M-CAF builds on theories that have previously been applied in HCI, such as activity theory [28] and distributed cognition [22].”
Quote in the paperNot a substantial claim0 of 2 sources checkedProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
InterpretationreasoningMixed-initiative tools can be placed within the Heideggerian viewpoint if one accepts that their function is different: they are ideation engines, not production ones.
“We contend that mixed-initiative tools can be placed within this Heideggerian viewpoint if one accepts that their function is diferent: they are ideation engines, not production ones.”
Quote in the paperNot a substantial claim- Rests on an assumption: Heidegger's account of tools as embodied functions that become ready-to-hand is an accurate description of tool use.
Probably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningM-CAF is an idealistic model that can describe systems fluctuating between being tools and being collaborators while remaining engaging and supportive of creativity.
“M-CAF is therefore an idealistic model, with which we can describe systems that fuctuate between being tools and being collaborators, all the while remaining engaging and supportive of creativity.”
Quote in the paperNot a substantial claim- The authors state this as an assumption: Agentive flow is critical to co-creative interactions.
The paper relies on this without support.
Participants would experience the same creative task differently the second time they were asked to complete it.
“Two diferent tasks were used (as participants would experience the same creative task diferently the second time they were asked to complete it), and were as follows:”
The authors state this as an assumption.
Reframer's drawings are inspired by stolen labour because of its use of CLIP.
“(although we acknowledge that our use of CLIP means Reframer's drawings are inspired by stolen labour)”
The paper relies on this without support.
Many creative workers already have precarious work arrangements.
“Our focus on real-time collaboration is also motivated by augmenting human creativity, rather than directly replacing creative workers, many of whom already have precarious work arrangements.”
The paper relies on this without support.
The two drawing tasks are open-ended and cannot be directly transcribed as prompts.
“These tasks were chosen to be open-ended and not directly transcribable as prompts.”
The paper relies on this without support.
Mixed-initiative drawing is novel.
“That's unsurprising, since mixed-initiative drawing is novel.”
The authors state this as an assumption.
Users' expectations about human-agent interaction derive from their assumptions and prior experiences with creative software and AI tools.
“(1) Expectations about the coming human-agent interaction, which derive from assumptions and prior experiences with both creative software and AI tools.”
The authors state this as an assumption.
Agentive flow is critical to co-creative interactions.
“M-CAF is diferent, focusing on one phenomenological notion -agentive fow -that we believe to be critical to co-creative interactions and how it is created, sustained, disrupted, and repaired.”
The paper relies on this without support.
Heidegger's account of tools as embodied functions that become ready-to-hand is an accurate description of tool use.
“Heidegger views tools as embodied functions that we encounter and can take advantage of.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
A more comprehensive understanding of views surrounding authenticity in human-AI co-creation remains elusive.
“Recent work on AI use for writing has begun to explore relevant constructs, such as ownership, authorship, and agency [11,13,39,49], but a more comprehensive understanding of views surrounding authenticity in human-AI co-creation remains elusive.”
From 'It was 80% me, 20% AI': Seeking Authenticity in Co-Writing with Large Language Models (2025) · cites this paper as [39]
The citation appears before the sentence’s claim about authenticity. The paper’s Related Work (§2.2; page unavailable) says that a broadly agreed definition of co-creative AI has eluded the field, and its Discussion (§6; page unavailable) addresses user perceptions of agency in drawing. Neither passage establishes that a comprehensive understanding of views on authenticity remains elusive; searches for authenticity, ownership, and authorship found no such discussion. (LLM, conf=0.74)
Experimental — accuracy not yet measured
Cites
High-Resolution Image Synthesis with Latent Diffusion Models
Rombach, R., Blattmann, A., Lorenz, D., Esser, P., & Ommer, B. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52688.2022.01042 · Cited by 15,880 · see citing works
Learning Transferable Visual Models From Natural Language Supervision
Radford, A., Kim, J. W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al. (2021) · arXiv · doi:10.48550/arxiv.2103.00020 · Cited by 15,293 · see citing works
I.—COMPUTING MACHINERY AND INTELLIGENCE
TURING, A. M. (1950) · Mind · doi:10.1093/mind/lix.236.433 · Cited by 10,290 · see citing works
Image Style Transfer Using Convolutional Neural Networks
Gatys, L. A., Ecker, A. S., & Bethge, M. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.265 · Cited by 6,025 · see citing works
Hollan, J., Hutchins, E., & Kirsh, D. (2000) · ACM Transactions on Computer-Human Interaction · doi:10.1145/353485.353487 · Cited by 2,300 · see citing works
Research through design as a method for interaction design research in HCI
Zimmerman, J., Forlizzi, J., & Evenson, S. (2007) · ACM SIGCHI Conference on Human Factors in Computing Systems (CHI) · doi:10.1145/1240624.1240704 · Cited by 2,300 · see citing works
High-Resolution Image Synthesis with Latent Diffusion Models
Rombach, R., Blattmann, A., Lorenz, D., Esser, P., & Ommer, B. (2021) · arXiv · doi:10.48550/arxiv.2112.10752 · Cited by 737 · see citing works
Braun, V., Clarke, V., & Hayfield, N. (2022) · Qualitative Research in Psychology · doi:10.1080/14780887.2019.1670765 · Cited by 604 · see citing works
Contemporary Approaches to Creative Thinking.
Lunsky, L. L. (1963) · Archives of Internal Medicine · doi:10.1001/archinte.1963.03860020198043 · Cited by 501 · see citing works
Köbberling, V., & Wakker, P. P. (2004) · Journal of Economic Theory · doi:10.1016/j.jet.2004.03.009 · Cited by 488 · see citing works
A Description of the Model-View-Controller User Interface Paradigm in the Smalltalk-80 System
Krasner, G., & Pope, S. (1998) · Cited by 469 · see citing works
Creating creativity: user interfaces for supporting innovation
Shneiderman, B. (2000) · ACM Transactions on Computer-Human Interaction · doi:10.1145/344949.345077 · Cited by 432 · see citing works
Sketch-Based Image Retrieval: Benchmark and Bag-of-Features Descriptors
Eitz, M., Hildebrand, K., Boubekeur, T., & Alexa, M. (2010) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2010.266 · Cited by 411 · see citing works
Investigator Triangulation: A Collaborative Strategy With Potential for Mixed Methods Research
Archibald, M. M. (2016) · Journal of Mixed Methods Research · doi:10.1177/1558689815570092 · Cited by 355 · see citing works
Suwa, M., Gero, J., & Purcell, T. (2000) · Design Studies · doi:10.1016/s0142-694x(99)00034-4 · Cited by 338 · see citing works
Group creativity: innovation through collaboration
(2004) · Choice Reviews Online · doi:10.5860/choice.41-5582 · Cited by 309 · see citing works
Modeling Design Exploration as Co‐Evolution
Maher, M. L., & Poon, J. (1996) · Computer-Aided Civil and Infrastructure Engineering · doi:10.1111/j.1467-8667.1996.tb00323.x · Cited by 256 · see citing works
Li, C., Tang, M., Tong, R., et al. (2020) · ACM Transactions on Graphics · doi:10.1145/3414685.3417763 · Cited by 149 · see citing works
Park, T., Liu, M.-Y., Wang, T.-C., & Zhu, J.-Y. (2019) · ACM SIGGRAPH Real-Time Live! · doi:10.1145/3306305.3332370 · Cited by 123 · see citing works
Activity Theory in HCI: Fundamentals and Reflections
Kaptelinin, V., & Nardi, B. (2012) · Synthesis Lectures on Human-Centered Informatics · doi:10.1007/978-3-031-02196-1 · Cited by 119 · see citing works
Mixed-Initiative Creative Interfaces
Deterding, S., Hook, J., Fiebrink, R., Gillies, M., Gow, J., Akten, M., Smith, G., Liapis, A., & Compton, K. (2017) · Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems · doi:10.1145/3027063.3027072 · Cited by 117 · cited 3× · see citing works
“Working with the curated outputs of mixed-initiative systems, humans and machines often become entangled in tight feedback loops in which initiative is shared [13].”
BackgroundWang, S.-Y., Bau, D., & Zhu, J.-Y. (2021) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.01379 · Cited by 73 · see citing works
Drawing Apprentice: An Enactive Co-Creative Agent for Artistic Collaboration
Davis, N., Hsiao, C.-P., Singh, K. Y., Li, L., Moningi, S., & Magerko, B. (2015) · Proceedings of the 2015 ACM SIGCHI Conference on Creativity and Cognition · doi:10.1145/2757226.2764555 · Cited by 67 · see citing works
Landing Page Optimization: The Definitive Guide to Testing and Tuning for Conversions
Ash, T., Ginty, M., & Page, R. (2008) · Cited by 65 · see citing works
Drawing with Reframer: Emergence and Control in Co-Creative AI
Lawton, T., Ibarrola, F., Ventura, D. A., & Grace, K. S. (2023) · ACM International Conference on Intelligent User Interfaces (IUI) · doi:10.1145/3581641.3584095 · Cited by 61 · see citing works
Self-citationModeling co-creativity in art and technology
Candy, L., & Edmonds, E. A. (2002) · ACM Conference on Creativity & Cognition (C&C) · doi:10.1145/581710.581731 · Cited by 57 · see citing works
Shared Leadership and Team Creativity: A Social Network Analysis in Engineering Design Teams
Wu, Q., & Cormican, K. (2016) · Journal of technology management & innovation · doi:10.4067/s0718-27242016000200001 · Cited by 49 · see citing works
Proceedings of the 1978 AISB/GI Conference on Artificial Intelligence
Sleeman, D. H., & Nagel, H.-H. (1978) · Cited by 14 · see citing works
Tolerance For Ambiguity: An Investigation On Its Effect On Student Design Performance
Mohammed, S., Okudan, G., & Ogot, M. (2020) · 2006 Annual Conference & Exposition Proceedings · doi:10.18260/1-2--909 · Cited by 9 · see citing works
SketchInverter: Multi-Class Sketch-Based Image Generation via GAN Inversion
An, Z., Yu, J., Liu, R., et al. (2023) · IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) · doi:10.1109/wacv56688.2023.00430 · Cited by 9 · see citing works
Customizing GAN Using Few-shot Sketches
Israr, S. M., & Zhao, F. (2022) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3503161.3548415 · Cited by 4 · see citing works
Flagged first, then by citations
Research works printed but not linked: 27
- Jennifer Attride-Stirling. 2001. Thematic networks: an analytic tool for qualitative research. Qualitative research 1, 3 (2001), 385–405.
- Simon Colton Geraint A Wiggins 2012. Computational creativity: The final frontier?. In Ecai Vol. 12. Montpelier 21–26.
- Katherine Crowson, Stella Biderman, Daniel Kornis, Dashiell Stander, Eric Hallahan, Louis Castricato, and Edward Raff. 2022. Vqgan-clip: Open domain image generation and editing with natural language guidance. In Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part XXXVII. Springer, 88–105.
- Mihaly Csikszentmihalyi. 1988. Society, culture and person: A system view of creativity. The Nature of Creativity (New York: Cambridge University Press, 1988) (1988), 325–339.
- Mihaly Csikszentmihalyi. 1997. Flow and creativity.Namta Journal 22, 2 (1997), 60–97.
- Nicholas Mark Davis. 2013. Human-computer co-creativity: Blending human and computational creativity. In Ninth Artificial Intelligence and Interactive Digital Entertainment Conference.
- Kees Dorst. 2006. Design problems and design paradoxes. Design issues 22, 3 (2006), 4–17.
- Jonathan Ericson. 2022. Reimagining the Role of Friction in Experience Design. Journal of User Experience Vol 17, 4 (2022).
- Catherine Flick and Kyle Worrall. 2022. The Ethics of Creative AI. In The Language of Creative AI: Practices, Aesthetics and Structures. Springer, 73–91.
- Kevin Frans, LB Soros, and Olaf Witkowski. 2021. Clipdraw: Exploring text-to-drawing synthesis through language-image encoders. arXiv preprint arXiv:2106.14843 (2021). · arXiv
- Gabriela Goldschmidt. 1991. The dialectics of sketching. Creativity research journal 4, 2 (1991), 123–143.
- Graham Harman. 2011. Tool-being: Heidegger and the metaphysics of objects. Open Court.
- Edwin L Hutchins, James D Hollan, and Donald A Norman. 1985. Direct manipulation interfaces. Human–computer interaction 1, 4 (1985), 311–338.
- Francisco Ibarrola, Tomas Lawton, and Kazjon Grace. 2022. A collaborative, interactive and context-aware drawing agent for co-creative design. arXiv preprint arXiv:2209.12588 (2022). · arXiv
- Pegah Karimi, Kazjon Grace, Nicholas Davis, and Mary Lou Maher. 2018. Creative sketching apprentice: Supporting conceptual shifts in sketch ideation. In International Conference on-Design Computing and Cognition. Springer, 721–738.
- Pegah Karimi, Kazjon Grace, Mary Lou Maher, and Nicholas Davis. 2018. Evaluating creativity in computational co-creative systems. arXiv preprint arXiv:1807.09886 (2018). · arXiv
- Robert Komaniecki. 2017. Analyzing collaborative flow in rap music. Music Theory Online 23, 4 (2017).
- Max Kreminski, Isaac Karth, Michael Mateas, and Noah Wardrip-Fruin. 2022. Evaluating mixed-initiative creative interfaces via expressive range coverage analysis.. In IUI Workshops. 34–45.
- Pattie Maes and Robyn Kozierok. 1993. Learning interface agents. In AAAI Vol. 93. 459–465.
- Lior Noy, Nava Levit-Binun, and Yulia Golland. 2015. Being in the zone: physiological markers of togetherness in joint improvisation. Frontiers in human neuroscience 9 (2015), 187.
- Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen. 2022. Hierarchical text-conditional image generation with CLIP latents. arXiv preprint arXiv:2204.06125 (2022). · arXiv
- Benjamin Saunders, Julius Sim, Tom Kingstone, Shula Baker, Jackie Waterfield, Bernadette Bartlam, Heather Burroughs, and Clare Jinks. 2018. Saturation in qualitative research: exploring its conceptualization and operationalization. Quality & quantity 52 (2018), 1893–1907.
- R Keith Sawyer. 2006. Group creativity: Musical performance and collaboration. Psychology of music 34, 2 (2006), 148–165.
- Donald A Schon and Glenn Wiggins. 1992. Kinds of seeing and their functions in designing. Design studies 13, 2 (1992), 135–156.
- Jonathan A Smith. 2015. Qualitative psychology: A practical guide to research methods. Qualitative psychology (2015), 1–312.
- Barbara Tversky. 2002. What do sketches say about thinking. In 2002 AAAI Spring Symposium, Sketch Understanding Workshop, Stanford University, AAAI Technical Report SS-02-08, Vol. 148. 151.
- Yael Vinker, Ehsan Pajouheshgar, Jessica Y Bo, Roman Christian Bachmann, Amit Haim Bermano, Daniel Cohen-Or, Amir Zamir, and Ariel Shamir. 2022. CLIPasso: Semantically-aware object sketching. arXiv preprint arXiv:2202.05822 (2022). · arXiv
Cited by
Sorted by citations
User Experience Design Professionals’ Perceptions of Generative Artificial Intelligence
Li, J., Cao, H., Lin, L., Hou, Y., Zhu, R., & Ali, A. E. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642114 · Cited by 192 · see citing works
“The author focuses on designing and evaluating functional prototypes through web-based experiments, exploring concepts like initiative, intent, and control, showing that the levels of initiative and control afforded by the UIs influence perceived authorship when writing text.”
BackgroundCreativeConnect: Supporting Reference Recombination for Graphic Design Ideation with Generative AI
Choi, D., Hong, S., Park, J., Chung, J. J. Y., & Kim, J. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642794 · Cited by 124 · see citing works
Han, Y., Qiu, Z., Cheng, J., & Lc, R. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642133 · Cited by 110 · see citing works
“Generative AI (GenAI) has been employed in creative tasks wherein humans collaborate with AI in endeavors such as creative writing [15, 42], drawing [28, 34], performance [24], game design [18], art exhibition [30, 31], and music arrangement [36].”
BackgroundMethodGenerating Automatic Feedback on UI Mockups with Large Language Models
Duan, P., Warner, J., Li, Y., & Hartmann, B. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642782 · Cited by 83 · see citing works
“Lawton et al. built a system where a human and generative AI model collaborate in drawing, and ran an exploratory study on the capabilities of this tool [22].”
BackgroundID.8: Co-Creating Visual Stories with Generative AI
Antony, V. N., & Huang, C.-M. (2024) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/3672277 · Cited by 81 · see citing works
“Several co-creative systems have explored how generative models may help users create storylines [13, 40], draw visuals [28, 66] and compose music [34].”
A User-centered Framework for Human-AI Co-creativity
Moruzzi, C., & Margarido, S. (2024) · Extended Abstracts of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613905.3650929 · Cited by 68 · see citing works
The Impact of Sketch-guided vs. Prompt-guided 3D Generative AIs on the Design Exploration Process
Lee, S. W., Jo, T. H., Jin, S., Choi, J., Yun, K., Bromberg, S., Ban, S., & Hyun, K. H. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642218 · Cited by 53 · see citing works
Prompting for Discovery: Flexible Sense-Making for AI Art-Making with Dreamsheets
Almeda, S. G., Zamfirescu-Pereira, J. D., Kim, K. W., Rathnam, P. M., & Hartmann, B. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642858 · Cited by 53 · see citing works
“[17].”
Jin, Y., Yoon, J., Self, J. A., & Lee, K. (2024) · Archives of Design Research · doi:10.15187/adr.2024.07.37.3.25 · Cited by 41 · see citing works
“Also, these tools could inadvertently marginalize minority groups (Flick & Worrall, 2022; Lawton et al., 2023) and lack the novelty needed for truly innovative designs (Grabe & Zhu, 2023).”
'It was 80% me, 20% AI': Seeking Authenticity in Co-Writing with Large Language Models
Hwang, A. H.-C., Liao, Q. V., Blodgett, S. L., Olteanu, A., & Trischler, A. (2025) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3711020 · Cited by 42 · see citing works
Kamath, P., Morreale, F., Bagaskara, P. L., Wei, Y., & Nanayakkara, S. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642040 · Cited by 37 · see citing works
“Therefore, although interface-2 opened up more personalized avenues for the designers to interact with the AI, the ambiguity in the dimensions got in the way of its agentive fow [57], a highly engaging state of interacting with an AI-based CST.”
Background(Un)making AI Magic: A Design Taxonomy
Lupetti, M. L., & Murray-Rust, D. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3641954 · Cited by 36 · see citing works
“…winter, the current spring [43] of AI tools is now being leveraged to speed up and enhance a multitude of works, especially in creative practices where applications range from idea exploration [22, 66, 68] and ideation [128] to project documentation [21], creative partnership [71, 86], and so on.”
BackgroundRealtimeGen: An Intervenable AI Image Generation System for Commercial Digital Art Asset Creators
Li, Z., Zhang, Y., Zhou, S., Liu, Q., Zhang, J., Xu, H., Chen, S., Chen, X., & Sun, L. (2024) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2024.2382508 · Cited by 36 · see citing works
“With the launch of large image generation models such as Midjourney, Dall-E and Stable Diffusion, the craze of AI painting is rising (Lawton et al., 2023; Verheijden & Funk, 2023).”
InfluentialDesigning Interactions with Generative AI for Art and Creativity: A Systematic Review and Taxonomy
Hu, X., Xing, Y., Cai, X., Zhao, Y., Cook, M. L., Borgo, R., & Neate, T. (2025) · Designing Interactive Systems Conference · doi:10.1145/3715336.3735843 · Cited by 33 · see citing works
Controlling AI Agent Participation in Group Conversations: A Human-Centered Approach
Houde, S., Brimijoin, K., Muller, M. J., Ross, S., Moran, D., Gonzalez, G. E., Kunde, S., Foreman, M. A., & Weisz, J. D. (2025) · ACM International Conference on Intelligent User Interfaces (IUI) · doi:10.1145/3708359.3712089 · Cited by 30 · see citing works
DanceGen: Supporting Choreography Ideation and Prototyping with Generative AI
Liu, Y., & Sra, M. (2024) · Designing Interactive Systems Conference · doi:10.1145/3643834.3661594 · Cited by 30 · see citing works
“Table 3 summarizes the themes obtained from data analysis and a brief description for each theme following the methodology adopted by Lawton et al. [42].”
MethodBeyond Code Generation: LLM-supported Exploration of the Program Design Space
Zamfirescu-Pereira, J. D., Jun, E., Terry, M. A., Yang, Q., & Hartmann, B. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3714154 · Cited by 32 · see citing works
What Makes It Mine? Exploring Psychological Ownership over Human-AI Co-Creations
Xu, Y., Cheng, M., & Kuzminykh, A. (2024) · Graphics Interface · doi:10.1145/3670947.3670974 · Cited by 26 · see citing works
“Although some studies explored users’ sense of ownership in AI applications [5, 7, 9, 25, 48], they often focus only on partial aspects of psychological dimensions and lacked a comprehensive understanding in specifically human-AI collaborative use cases.”
Amuse: Human-AI Collaborative Songwriting with Multimodal Inspirations
Kim, Y., Lee, S.-J., & Donahue, C. (2025) · Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713818 · Cited by 23 · see citing works
“As suggested by prior work in the creative writing domain [88], creative processes involve broadly different styles of engagement with suggestions, including reactive and proactive engagements.”
Human-Centered AI Communication in Co-Creativity: An Initial Framework and Insights
Rezwana, J., & Ford, C. (2025) · Creativity and Cognition · doi:10.1145/3698061.3726932 · Cited by 23 · see citing works
“Bidirectional exchange of ideas and information between users and AI can create moments of serendip-ity and novelty [73], which are essential components of creativity [44, 110].”
CoFRIDA: Self-Supervised Fine-Tuning for Human-Robot Co-Painting
Schaldenbrand, P., Parmar, G., Zhu, J.-Y., McCann, J., & Oh, J. (2024) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra57147.2024.10610618 · Cited by 23 · see citing works
“While it is still debatable whether such an autonomous creation is desired by humans practicing art [2], there is strong evidence of the potential value of a co-creative agent [3], [4], [5], [6], [7], [8], [9] specifically in the domain of art therapy [10], [11], [12], [13].”
BackgroundGuridi, J. A., Hwang, A. H., Santo, D., Goula, M., Cheyre, C., Humphreys, L., & Rangel, M. (2025) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3710912 · Cited by 24 · see citing works
“While leveraging IGAI’s capabilities in design tasks has attained extensive research interests, the majority of such work focuses on how AI-powered tools augment the experience and performance of individual creators [e.g., 28, 29, 60, 73, 74, 122].”
Naqvi, S. M., He, R., & Kaur, H. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713233 · Cited by 22 · see citing works
“CICADA, a vector-based generative AI approach [46], and Reframer, a drawing interface built on CICADA [59], allow users to interact with generative AI through shared drawing.”
Lin, H., Ye, Y., Xia, J., & Zeng, W. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713801 · Cited by 18 · see citing works
Deshpande, M., Park, J., Pait, S., & Magerko, B. S. (2024) · Creativity and Cognition · doi:10.1145/3635636.3656202 · Cited by 15 · see citing works
“Similarly, Lawton et al. focus on digital media and graphic design, aiming to boost creative ideation and decision-making through AI support within a digital context [41].”
BackgroundAI-Assisted Design: Intelligent Generation of Dong Paper-Cut Patterns
Xiao, Y., Lin, X., Ji, T., Qiao, J., Ma, B., & Gong, H. (2025) · Electronics · doi:10.3390/electronics14091804 · Cited by 16 · see citing works
An Exploration of Mental Models of AI in Human–AI Co-Creativity: A Framework and Insights
Rezwana, J., & Maher, M. L. (2025) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/3769072 · Cited by 11 · see citing works
Orchid: A Creative Approach for Authoring LLM-Driven Interactive Narratives
Wu, Z., Kumyol, S., Wong, S., Hu, X., Tong, X., & Braud, T. (2025) · Creativity and Cognition · doi:10.1145/3698061.3726906 · Cited by 11 · see citing works
“This was also addressed in drawing [47] and language art [39].”
Breckner, K., Neumayr, T., Mara, M., Streit, M., & Augstein, M. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2482742 · Cited by 12 · see citing works
Phraselette: A Poet’s Procedural Palette
Calderwood, A., Chung, J. J. Y., Sun, Y., Roemmele, M., & Kreminski, M. (2025) · Designing Interactive Systems Conference · doi:10.1145/3715336.3735832 · Cited by 11 · see citing works
Creative Ambiguity and Cognitive Tension in Generative AI Tools
Dalsgaard, P. (2025) · European Conference on Cognitive Ergonomics · doi:10.1145/3746175.3746183 · Cited by 8 · see citing works
Maier, S., Schneider, M., & Feuerriegel, S. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791185 · Cited by 8 · see citing works
No Evidence for LLMs Being Useful in Problem Reframing
Shin, J., Polyanskaya, A., Lucero, A., & Oulasvirta, A. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713273 · Cited by 7 · see citing works
Exploring Aesthetic Qualities of Deep Generative Models through Technological (Art) Mediation
Sivertsen, C., & Løvlie, A. S. (2024) · Designing Interactive Systems Conference · doi:10.1145/3643834.3661498 · Cited by 6 · see citing works
“Interfaces that rely on drawing as input to the sys-tem have been explored within HCI research [6, 21, 22, 44, 72].”
BackgroundMethodBalancing Human Agency and AI Autonomy in Human-AI Idea Selection
Young-Ng, M., Zhu, Q., Liao, J., & Wang, H. (2025) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3706599.3719880 · Cited by 5 · see citing works
“While human-in-the-loop co-creation workflows with sequential turn-taking can retain users’ perceived agency [13], other human-AI co-creation methods feature higher AI autonomy (system agency) through concurrent interactions that enable AI to function as a collaborator [15].”
Flathmann, C., McNeese, N. J., Sengupta, S., & Johnson, E. (2025) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/3764591 · Cited by 5 · see citing works
Peer or Steer: A Pilot Study Exploring Human-AI Collaboration in Creative Fields
Lang, D., Hirschmann, F., Breckner, K., Neumayr, T., & Augstein, M. (2025) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3757643 · Cited by 5 · see citing works
Co-Creating Question-and-Answer Style Articles with Large Language Models for Research Promotion
Lim, H., Cho, J. Y., Kim, T., Park, J., Shin, H., Choi, S., Park, S., Lee, K., Kim, J., Lee, M., et al. (2024) · Designing Interactive Systems Conference · doi:10.1145/3643834.3660705 · Cited by 4 · see citing works
“Research on human-AI co-creation systems have been actively conducted in a wide range of creative tasks for design [29], illustrations [9, 62, 65], music composition [40], dancing [64], drawing [19, 33, 46], storytelling [14, 16, 43, 45, 48, 59], and writing [4, 17, 23, 28, 39, 52, 77].”
BackgroundThe measurement of perceived shared agency in customer–artificial intelligence interactions
Voyer, B. G., Sanglé-Ferrière, M., Sajtos, L., & Sung, B. (2025) · Journal of Service Theory and Practice · doi:10.1108/jstp-08-2024-0266 · Cited by 4 · see citing works
Wang, Y., Liu, X., & Choi, S. (2025) · Behavioral Sciences · doi:10.3390/bs15070937 · Cited by 4 · see citing works
“While existing studies have explored users’ sense of ownership in AI applications (Bennett et al., 2023; Chang et al., 2023; Chung et al., 2021; Lawton et al., 2023; Wu et al., 2023), they often focus on specific psychological aspects and lack a comprehensive examination of ownership within human–…”
Tracing Creativity: A Design Space For Creative Activity Traces in HCI
Hammad, N., Lin, D. C.-E., Smith, A., Kreminski, M., Harpstead, E., & Hammer, J. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791263 · Cited by 3 · see citing works
“For example, drawing inputs in WhenIsATool or edit operations in Lotus demonstrate in-tool origin [10, 90].”
Can Machines Tell What People Want? Bringing Situated Intelligence to Generative AI
Bremers, A. W. D., & Ju, W. G. (2024) · Halfway to the Future Symposium · doi:10.1145/3686169.3686172 · Cited by 3 · see citing works
TacTalk: Personalizing Haptics Through Conversation
Mishra, A., & Schneider, O. (2025) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3719160.3736638 · Cited by 2 · see citing works
Gao, B., Liu, R., & Chu, J. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-93412-4_11 · Cited by 5 · see citing works
Lou, Q., Bai, Y., Ying, H., Cai, L., Feng, X., & Zhang, X. (2024) · International Symposium on Computational Intelligence and Design · doi:10.1109/iscid63852.2024.00043 · Cited by 2 · see citing works
“AI is becoming a key collaboration partner for designers, supporting them in not only performing tasks such as information retrieval, data processing, idea visualization, and style transfer [1], but also inspiring their creative thought [2].”
Li, Y. L., Kuang, Q., Xiao, X., Labrune, J., & Ishii, H. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791258 · Cited by 1 · see citing works
How Robotic Artists Perceive 'Collaboration' with Machines?
Qin, Y., Li, Y., & Cheon, E. (2025) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3706599.3720017 · Cited by 1 · see citing works
Huang, C.-J. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-93233-5_4 · Cited by 1 · see citing works
Supporting Material Writing Practice with Phraselette, a Palette of Phrases
Calderwood, A., Kim, T., Sun, Y., Roemmele, M., Chung, J. J. Y., & Kreminski, M. (2025) · Designing Interactive Systems Conference · doi:10.1145/3715668.3735608 · Cited by 1 · see citing works
“Broadly, our findings also support Li et al.’s theory of “normative ground” [28]; Roemmele’s findings around “inspiration through observation” of machine-generated text [34]; and Lawton et al.’s findings regarding when users perceive co-creative systems as collaborators rather than tools [26].”
ClearDose: AI Overfunctioning at the Boundaries of Care
Han, Y.-N., & Leigh, S.-W. (2026) · International Conference on Tangible, Embedded, and Embodied Interaction · doi:10.1145/3731459.3779135 · Cited by 1 · see citing works
“For instance, while generative AI could collaborate with users for co-creation (e.g., [11, 12, 14]) and provide emotional companionship (e.g., [15]), it may also deliver unsafe and biased content to users [22], erode users’ agency [9], and harm users’ well-being [13].”
A critical review of sketch collection methods: Remembering how humans really sketch
Dede, E., Kara, Z. B., & Sezgin, T. M. (2026) · Computers & Graphics · doi:10.1016/j.cag.2026.104603 · Cited by 1 · see citing works
Wang, N., Liu, Z., Yang, H., Chang, F., & Shen, B. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791812
A Review of Multi-modal and Multi-view Applications in Hand-Drawn Sketch Images
Xu, Y., & Suen, C. Y. (2025) · Communications in computer and information science · doi:10.1007/978-3-031-85933-5_8
The Probing Machine: Can Using GenAI Tools Help With Better Reflections During User Interviews
Tran, C., Parayno, R. L., Venkitachalam, B. K., Deja, J. A., & Deja, J. A. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-93418-6_6
Fan, G. F., Liu, D., Pan, L., & Huang, Y. (2025) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn64981.2025.11229343
Am I Working with “Someone”: Psychological Ownership as a Lens for Designing Agentic GenAI
Xu, Y., Cheng, M., & Kuzminykh, A. (2025) · IEEE International Conference on Collaborative Advances in Software and Computing (CASCON) · doi:10.1109/cascon66301.2025.00120
“For instance, some scholars, like Lawton et al. [8], advocate designing agentive AI to support a bi-directional exchange of creativity.”
“Can I Draw Here?” Embodied Proactive Suggestions in a Robotic Arm Painter
Huang, J. (2026) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1145/3776734.3794430
Jo, T. H., Choi, J., Jin, S., Lee, S., Jang, Y., Park, S.-W., Ban, S., & Hyun, K. H. (2026) · Archives of Design Research · doi:10.15187/adr.2026.05.39.2.7
Jang, Y., Lyu, Z., Arsenault, A. C., Kreps, S. E., & Yang, Q. (2026) · Designing Interactive Systems Conference · doi:10.1145/3800645.3813085
“…such as ideation, drafting, reflection, and revision through techniques like iterative prompting, mixed-initiative co-writing, and process-level scaffolding [42, 58], as well as preserving user agency through metacognitive reflection and making AI contributions legible and negotiable [23, 35].”
He, M., Hao, L., Li, Y. X., Chen, X. L., Jin, S., Wei, L., ZHANG, Q.-Q., & Xiong, W. H. (2026) · Communications in computer and information science · doi:10.1007/978-3-032-30836-8_3
Saraiva, V., Santos, C., & Ferreira, L. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-30846-7_11
Huang, C.-J. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-30089-8_4
Understanding User Experience in AI-Based Evaluation Systems: A Systematic Literature Review
Park, H., Chung, G., Kim, C., & Kim, H. K. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-29653-5_21
How Creative Design Teams Make Sense of Contrasting AI Personas
Ma, K., Won, D., Zeng, Y., Chung, J., & Goucher-Lambert, K. (2026) · Creativity and Cognition · doi:10.1145/3803784.3816826
“Research shows that AI support in creative collaboration varies by function, timing, and degree of agency [13, 19, 40], and that even small differences in system behavior can shape whether AI is treated as a passive tool or active collaborator [13, 20, 25].”
Liu, S., Qian, Y. Z., Zhang, F., Allen, R. W., & Lc, R. (2026) · Creativity and Cognition · doi:10.1145/3803784.3807563
“Artists’ attitudes toward GenAI influence how they engage with it [51].”
Designing Through Dialogue: Interaction Patterns in AI-Assisted UI Prototyping
Breckner, K., Hirschmann, F., Kotzian, D., Neumayr, T., Altmann, J., & Augstein, M. (2026) · Creativity and Cognition · doi:10.1145/3803784.3816854
“Addressing the integration of AI in this context, a lot of existing research focuses on designers’ perceptions and acceptance [18, 27, 29], the broader context of use [15, 21], or performance on particular tasks [11, 15, 41, 43].”
Cózar-Angulo, X. (2026) · Aracê. · doi:10.56238/hqkadd39
“In studying human-AI collaborative drawing systems, Lawton et al. (2023) found that the perception of the system's agency constitutes a relevant element in the co-creation experience, thereby questioning what type of creative relationship is established between artist and system.”
Digital Wellbeing by Design: Safeguarding End-Users' Time and Attention in UI/UX Practices
Roffarello, A. M., Russis, L. D., & Pellegrino, M. (2026) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3816925
Ahsan, M., Shi, W., Becker, D. V., Ramos, G., & Wilkinson, D. (2026) · Human-Computer Interaction · doi:10.1080/07370024.2026.2720237 · Cited by 1 · see citing works
Hosseinian, F., & Sheikhansari, I. (2026) · AI and Ethics · doi:10.1007/s43681-026-01437-0
“We determined the sample size through a combination of data sufficiency and reference to sample sizes in comparable HCI studies, e.g., [ 46, 53, 93].”
- Authors
- Lawton, T., Grace, K., & Ibarrola, F. J.
- Affiliations
- The University of Sydney (AU)
- Venue
- Proceedings of the 2023 ACM Designing Interactive Systems Conference
- Publisher
- ACM
- Published
- 2023-07-10
- Pages
- 1978-1996
- OpenAlex
- W4383682782
- Cited by
- 72
- References
- 31
- Citations by year
- 2026: 22 · 2025: 30 · 2024: 20
- FWCI
- 16.67
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Designing Interactive Systems Conference (publishedVersion)
- Funders
- Australian Research Council (DP200101059)
- Topics
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Digital Media and Visual Art
- Social Sciences › Arts and Humanities › Visual Arts and Performing Arts › Art, Technology, and Culture
- Keywords
- human-AI co-creation, user perception, generative AI, user experience, interface design, human-AI collaboration
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-05.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-05.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review