An Exploration of Machine Learning in Art and Design DOI

Rumeysa Zeynep Araçlı Dursun,

Uğur Bakan

Advances in human and social aspects of technology book series, Год журнала: 2024, Номер unknown, С. 205 - 236

Опубликована: Окт. 4, 2024

The paper delves into the profound impact of Artificial Intelligence (AI) on various creative domains, emphasizing its transformative potential in reshaping human-computer interaction. It explores AI's evolution from traditional programming to Machine Learning (ML), highlighting ML's pivotal role facilitating tasks traditionally reserved for human intelligence. text elucidates how ML algorithms, such as Generative Adversarial Networks (GANs) and Neural Style Transfer, have revolutionized artistic creation by enabling computers generate visually captivating artworks autonomously. Furthermore, it discusses democratizing effect AI art design, making tools techniques more accessible individuals diverse backgrounds. While acknowledging ethical implications challenges, bias interpretability concerns, advocates interdisciplinary collaboration address these issues responsibly.

Язык: Английский

Research on key factors influencing Chinese designers’ use of AIGC: An extension based on TAM and TRI DOI Creative Commons
Yu Yao, Xiang Wang, Kuo-Shun Sun

и другие.

PLoS ONE, Год журнала: 2025, Номер 20(2), С. e0314306 - e0314306

Опубликована: Фев. 19, 2025

With the rapid development of AI intelligent technology, AIGC can bring an innovative revolution to art creation, providing designers with unlimited possibilities but also challenges. These challenges affect willingness adopt and constrain sustainable AIGC. The purpose this study is analyse factors designers’ adoption intention behaviours. This reconstructed research model by combining technology characteristics interactivity, acceptance model, readiness etc. empirical was conducted from dual perspectives application psychology, in order predict that behavioural intentions use In study, a questionnaire survey among China 462 valuable responses were received. Through structural equation modelling (SEM) analysis, found that: (1) AIGC’s technical features interactivity positively perceived ease use, usefulness, interactive do not directly usefulness; usefulness applications; (2) optimism innovation adopt; Insecurity negatively affects adopt, insecurity does features; discomfort adopt. further extends theoretical models TAM(Technology Acceptance Model) TRI(Technology Readiness Model), provides basis for studying behaviour AIGC, enriches groups domains TAM TRI. results provide inspiration development, design, marketing applications, contributing realisation as well professional designers.

Язык: Английский

Процитировано

0

Exploring the Integration of Generative AI in Advertising Agencies: A Co-Creative Process Model for Human–AI Collaboration DOI
Wen Cui, Martin J. Liu, Ruizhi Yuan

и другие.

Journal of Advertising Research, Год журнала: 2025, Номер unknown, С. 1 - 23

Опубликована: Март 11, 2025

Язык: Английский

Процитировано

0

Exploration and Practice of Artificial Intelligence Generative Art in Environmental Public Art DOI Open Access
Juan Li

Applied Mathematics and Nonlinear Sciences, Год журнала: 2025, Номер 10(1)

Опубликована: Янв. 1, 2025

Abstract Applying AI generative art to the field of environmental public can improve work efficiency, save money, reduce costs and increase profits. In this paper, an optimized technique is proposed by combining high-level semantic features images underlying color features, while introducing Gestalt visual perception theory. The performance evaluated conducting a questionnaire survey on 50 subjects. Increasing test sample capacity analyzing data, it concluded that mean value scores perceived quality, value, cost, risk, social impact, media barriers, willingness accept are all above 4, technology anxiety lowest at 3.832. This paper provides reference significance for production dissemination image content AI-generated in art.

Язык: Английский

Процитировано

0

AI-Assisted Inheritance of Qinghua Porcelain Cultural Genes and Sustainable Design Using Low-Rank Adaptation and Stable Diffusion DOI Open Access

Qian Bao,

J. Zhao,

Ziqi Liu

и другие.

Electronics, Год журнала: 2025, Номер 14(4), С. 725 - 725

Опубликована: Фев. 13, 2025

Blue-and-white porcelain, as a representative of traditional Chinese craftsmanship, embodies rich cultural genes and possesses significant research value. Against the backdrop generative AI era, this study aims to optimize creative processes blue-and-white porcelain enhance efficiency accuracy complex artistic innovations. Traditional methods crafting encounter challenges in accurately efficiently constructing intricate patterns. This employs grounded theory conjunction with KANO-AHP hybrid model classify quantify core esthetic features thereby establishing multidimensional feature library its Subsequently, leveraging Stable Diffusion platform utilizing Low-Rank Adaptation (LoRA) technology, artificial intelligence (AIGC)-assisted workflow was proposed, capable restoring innovating enhances precision pattern innovation while maintaining consistency original style. Finally, by integrating principles sustainable design, explores new pathways for digital offering viable solutions contemporary reinvention crafts. The results indicate that AIGC technology effectively facilitates integration modern design approaches. It not only empowers inheritance continuation but also introduces ideas possibilities development craftsmanship.

Язык: Английский

Процитировано

0

Understanding Student Engagement in AI-Powered Online Learning Platforms: A Narrative Review of Key Theories and Models DOI
Manuel B. Garcia, Chai Lee Goi, Kate Shively

и другие.

SSRN Electronic Journal, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Art psychotherapy meets creative AI: an integrative review positioning the role of creative AI in art therapy process DOI Creative Commons
Ania Zubala, Alison Pease, Kacper Lyszkiewicz

и другие.

Frontiers in Psychology, Год журнала: 2025, Номер 16

Опубликована: Март 20, 2025

Background The rise of artificial intelligence (AI) is promising novel contributions to treatment and prevention mental ill health. While research on the use conversational embodied AI in psychotherapy practice developing rapidly, it leaves gaps understanding impact that creative might have art specifically. A constructive dialogue between disciplines needed, establish potential relevance AI-bases technologies therapeutic involving artmaking self-expression. Methods This integrative review set out explore whether how could enhance other psychological interventions utilizing visual communication and/or artmaking. transdisciplinary search strategy was developed capture latest across diverse methodologies stages development, including reviews, opinion papers, prototype development empirical studies. Findings Of over 550 records screened, 10 papers were included this review. Their key characteristics are mapped a matrix stakeholder groups involved, elements belonging therapy domain, types AI-based involved. Themes significance for AT discussed, cultural adaptability, inclusivity accessibility, creativity self-expression, unpredictability imperfection. positioning diagram proposed describe role AT. AI’s process oscillates spectrum from being partner co-creative taking curator personalized visuals with intent. Another dimension indicates level autonomy – supportive tool an autonomous agent. Examples each these situations identified reviewed literature. Conclusion brings opportunities new modes self-expression extended reach therapy, over-reliance presents risks process, loss agency clients therapists. Implications technology relationship demand further investigation, as do its impacts, before can be confirmed.

Язык: Английский

Процитировано

0

Exploring Privacy, Data Painting, and Hidden Biases: Lessons From Contemporary Artists for AI Use in Art Education DOI
Ahran Koo, Borim Song

Art Education, Год журнала: 2025, Номер 78(2), С. 16 - 24

Опубликована: Март 4, 2025

Язык: Английский

Процитировано

0

“Who” Is the Best Creative Thinking Partner? An Experimental Investigation of Human–Human, Human–Internet, and Human–AI Co‐Creation DOI Open Access

Min Tang,

Sebastian Hofreiter, Christian Werner

и другие.

The Journal of Creative Behavior, Год журнала: 2024, Номер unknown

Опубликована: Дек. 10, 2024

ABSTRACT Recent research suggests that working with generative artificial intelligence (AI), such as ChatGPT, can produce more creative outcomes than humans alone. However, does AI retain its edge when have access to alternative information sources, another human or the internet. We explored this question in a between‐group experiment 202 German participants across four conditions (human–human dyads, human–Internet, and two human–AI groups basic specific instructions) creativity tasks (two alternate uses tasks, consequences task, problem‐solving task). Results showed human–human condition obtained higher scores divergent thinking remaining groups. No significant differences were observed task. Moreover, interacting dyads made people creatively confident, an effect not other In addition, we compared human‐rated AI‐based automated scoring (Ocsai). Interestingly, notable discrepancies emerged between assessment human‐judged results, raising concerns about AI's susceptibility “elaboration bias.” These findings highlight benefits of collaboration for call further studies reliability potential biases evaluating performance.

Язык: Английский

Процитировано

2

Understanding Student Engagement in AI-Powered Online Learning Platforms DOI
Manuel B. Garcia, Chai Lee Goi, Kate Shively

и другие.

Advances in educational technologies and instructional design book series, Год журнала: 2024, Номер unknown, С. 1 - 30

Опубликована: Дек. 27, 2024

Online learning has become fundamental to modern academic and professional development. Amidst its widespread adoption, there is increasing integration of artificial intelligence (AI) enhance the experience. Understanding student engagement within these AI-powered digital platforms crucial, as it directly influences outcomes satisfaction. This chapter provides a narrative review key theories models essential for analyzing in virtual contexts. Particularly, focuses on constructivist theory, social cognitive load flow technology acceptance model, self-determination theory multimedia learning, feedback intervention theory. By examining frameworks through an epistemological lens, explores how knowledge acquisition, processing, principles interact AI-enhanced educational The insights reported here can serve guide optimizing AI maximize involvement efficacy.

Язык: Английский

Процитировано

2

An Exploration of Machine Learning in Art and Design DOI

Rumeysa Zeynep Araçlı Dursun,

Uğur Bakan

Advances in human and social aspects of technology book series, Год журнала: 2024, Номер unknown, С. 205 - 236

Опубликована: Окт. 4, 2024

The paper delves into the profound impact of Artificial Intelligence (AI) on various creative domains, emphasizing its transformative potential in reshaping human-computer interaction. It explores AI's evolution from traditional programming to Machine Learning (ML), highlighting ML's pivotal role facilitating tasks traditionally reserved for human intelligence. text elucidates how ML algorithms, such as Generative Adversarial Networks (GANs) and Neural Style Transfer, have revolutionized artistic creation by enabling computers generate visually captivating artworks autonomously. Furthermore, it discusses democratizing effect AI art design, making tools techniques more accessible individuals diverse backgrounds. While acknowledging ethical implications challenges, bias interpretability concerns, advocates interdisciplinary collaboration address these issues responsibly.

Язык: Английский

Процитировано

0