Quantifying co-creative writing experiences

Kantosalo, Anna; Riihiaho, Sirpa

doi:10.1080/14626268.2019.1575243

Cited by 13 publications

(20 citation statements)

References 7 publications

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“…[19, p.9] We believe such evaluations of human-AI synergy should go beyond one-shot performance measures. As implied by many of the uses cases listed by Seeber et al [80], human-centered AI systems are often deployed in socio-organizational contexts that require longitudinal use [20,41,43], such as product design [93], game design [4], and engineering [20, Section 3.2.2]. Thus, we would expect that over time and through interaction with each other, human-AI teams would improve their performance through a mutual learning process.…”

Section: Toward Human-ai Synergymentioning

confidence: 99%

The Programmer's Assistant: Conversational Interaction with a Large Language Model for Software Development

Ross,

Martinez,

Houde

et al. 2023

Preprint

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Large language models (LLMs) have recently been applied in software engineering to perform tasks such as translating code between programming languages, generating code from natural language, and autocompleting code as it is being written. When used within development tools, these systems typically treat each model invocation independently from all previous invocations, and only a specific limited functionality is exposed within the user interface. This approach to user interaction misses an opportunity for users to more deeply engage with the model by having the context of their previous interactions, as well as the context of their code, inform the model's responses. We developed a prototype system -the Programmer's Assistant -in order to explore the utility of conversational interactions grounded in code, as well as software engineers' receptiveness to the idea of conversing with, rather than invoking, a code-fluent LLM. Through an evaluation with 42 participants with varied levels of programming experience, we found that our system was capable of conducting extended, multi-turn discussions, and that it enabled additional knowledge and capabilities beyond code generation to emerge from the LLM. Despite skeptical initial expectations for conversational programming assistance, participants were impressed by the breadth of the assistant's capabilities, the quality of its responses, and its potential for improving their productivity. Our work demonstrates the unique potential of conversational interactions with LLMs for co-creative processes like software development.CCS Concepts: • Human-centered computing → HCI theory, concepts and models; • Software and its engineering → Designing software; • Computing methodologies → Generative and developmental approaches.

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Section: Toward Human-ai Synergymentioning

confidence: 99%

The Programmer's Assistant: Conversational Interaction with a Large Language Model for Software Development

Ross,

Martinez,

Houde

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Here, we introduce the field of computational creativity into geography and discuss how it can be understood spatially. Computational creativity is considered a subfield of AI (e.g., Colton & Wiggins, 2012; Kantosalo, 2019). Operationally, AI includes such functions as data acquisition, interpretation and processing, and it is able to ‘decide’ the best actions to take to achieve the given goal.…”

Section: Geography and The Spatialities Of Creativitymentioning

confidence: 99%

“…Building on the findings above and the studies of co‐creativity in the field of computational creativity (Davis, 2021; Feldman, 2017; Kantosalo, 2019; Kantosalo & Toivonen, 2016), we develop our theoretical contribution to creative geographies by presenting the concept of co‐creative spatiality , by which we mean a contextualised spatiality being created in the sites and relations, at and beyond the interface, where humans and AI collaborate in a shared creative process. To understand co‐creative spatiality and AI's influence on it, we now return to our results and discuss them further from spatial and techno‐material perspectives.…”

Section: Co‐creative Spatiality In the Sites And Relations Of Human–a...mentioning

confidence: 99%

Creative geographies in the age of AI: Co‐creative spatiality and the emerging techno‐material relations between artists and artificial intelligence

Lundman

Nordström

2023

Trans Inst British Geog

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Artificial intelligence (AI) expands the more‐than‐human perspective on creativity and creative geographies, as new techno‐material relations and spatialities are formed when humans and AI create together. In this paper, we suggest the concept of ‘co‐creative spatiality’ to refer to the special sites, relations and processes of human–AI collaboration in artistic creative practice. Our study builds on interviews with 26 Finland‐based artists who have used AI in their artistic work. In our analysis, we focus on the questions of what, how, where, who and with of creativity, through which we study the spatialities of creativity and their links to AI. We discuss, how the emerging techno‐materialities of AI affect co‐creative spatiality by stretching the boundaries of (human) imagination and sparking creativity across new imaginative terrains. Co‐creative spatiality reveals novel and unfamiliar collaborations that constitute our material worlds and, therefore, we believe it invites geographical analysis from all those interested in the transformations of creative and artistic practices in the age of AI.

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“…Here, the study designer first specifies what is meant by creativity and then defines the criteria for how it can be (perceptually) assessed. Moreover, combining observations (by the experimenter) and self-reporting of the participants has been known to produce apt results in studies assessing human experience while using creative systems (Kantosalo and Riihiaho, 2019).…”

Section: Perceived Creativity Assessment (Dv)mentioning

confidence: 99%

How Does Embodiment Affect the Human Perception of Computational Creativity? An Experimental Study Framework

Linkola¹,

Guckelsberger²,

Männistö³

et al. 2022

Preprint

Self Cite

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Which factors influence the human assessment of creativity exhibited by a computational system is a core question of computational creativity (CC) research. Recently, the system's embodiment has been put forward as such a factor, but empirical studies of its effect are lacking. To this end, we propose an experimental framework which isolates the effect of embodiment on the perception of creativity from its effect on creativity per se. We not only manipulate the system's embodiment, but also the perceptual evidence as the basis for the human creativity assessment. We motivate the core framework with embodiment and perceptual evidence as independent and the creative process as controlled variable, and we provide recommendations on measuring the assessment of creativity as dependent variable. We hope the framework will inspire others to study the human perception of embodied CC in a principled manner.

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Quantifying co-creative writing experiences

Cited by 13 publications

References 7 publications

The Programmer's Assistant: Conversational Interaction with a Large Language Model for Software Development

The Programmer's Assistant: Conversational Interaction with a Large Language Model for Software Development

Creative geographies in the age of AI: Co‐creative spatiality and the emerging techno‐material relations between artists and artificial intelligence

How Does Embodiment Affect the Human Perception of Computational Creativity? An Experimental Study Framework

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