User Experience Design Professionals’ Perceptions of Generative Artificial Intelligence
Abstrak
Among creative professionals, Generative Artificial Intelligence (GenAI) has sparked excitement over its capabilities and fear over unanticipated consequences. How does GenAI impact User Experience Design (UXD) practice, and are fears warranted? We interviewed 20 UX Designers, with diverse experience and across companies (startups to large enterprises). We probed them to characterize their practices, and sample their attitudes, concerns, and expectations. We found that experienced designers are confident in their originality, creativity, and empathic skills, and find GenAI’s role as assistive. They emphasized the unique human factors of “enjoyment” and “agency”, where humans remain the arbiters of “AI alignment’’. However, skill degradation, job replacement, and creativity exhaustion can adversely impact junior designers. We discuss implications for human-GenAI collaboration, specifically copyright and ownership, human creativity and agency, and AI literacy and access. Through the lens of responsible and participatory AI, we contribute a deeper understanding of GenAI fears and opportunities for UXD.
Artikel Ilmiah Terkait
Sijia Li Macy Takaffoli Ville Mäkelä
1 Juli 2024
User Experience (UX) practitioners, like UX designers and researchers, have begun to adopt Generative Artificial Intelligence (GenAI) tools into their work practices. However, we lack an understanding of how UX practitioners, UX teams, and companies actually utilize GenAI and what challenges they face. We conducted interviews with 24 UX practitioners from multiple companies and countries, with varying roles and seniority. Our findings include: 1) There is a significant lack of GenAI company policies, with companies informally advising caution or leaving the responsibility to individual employees; 2) UX teams lack team-wide GenAI practices. UX practitioners typically use GenAI individually, favoring writing-based tasks, but note limitations for design-focused activities, like wireframing and prototyping; 3) UX practitioners call for better training on GenAI to enhance their abilities to generate effective prompts and evaluate output quality. Based on our findings, we provide recommendations for GenAI integration in the UX sector.
T. Jokela Antti Salovaara Severi Uusitalo + 1 lainnya
1 Juli 2024
Generative artificial intelligence (GAI) is transforming numerous professions, not least various fields intimately relying on creativity, such as design. To explore GAI’s adoption and appropriation in design, an interview-based study probed 10 specialists in user experience and industrial design, with varying tenure and GAI experience, for their adoption/application of GAI tools, reasons for not using them, problems with ownership and agency, speculations about the future of creative work, and GAI tools’ roles in design sensemaking. Insight from reflexive thematic analysis revealed wide variation in attitudes toward GAI tools – from threat-oriented negative appraisals to identification of empowerment opportunities – which depended on the sense of agency and perceived control. The paper examines this finding in light of the Coping Model of User Adaptation and discusses designers’ metacognitive skills as possible underpinnings for their attitudes. Avenues for further research are identified accordingly.
M. Khwaja Tiffany Knearem Clara E Kliman-Silver + 2 lainnya
19 April 2023
Recently, artificial intelligence (AI) has been introduced into a variety of consumer applications for creative work. Although AI-driven features in design tooling are nascent, there is growing interest in utilizing AI to support user experience (UX) workflows. In this case study, we surveyed industry UX professionals to understand how they perceive AI-driven assists in their tools, their concerns about accepting AI in design tools and which design-related workflows could be promising for future research. Our results suggest that UX professionals are overall positive about AI-driven features in design tools; looking to AI as a creative partner to iterate with and as an assistant with mundane tasks. We offer practical directions for the future of AI in UX tooling, but caution against developing tools that do not sufficiently address UX professionals’ concerns around bias and trust.
E. Zamani Åsne Stige Yuzhen Zhu + 1 lainnya
29 Agustus 2023
PurposeThe aim of this article is to map the use of AI in the user experience (UX) design process. Disrupting the UX process by introducing novel digital tools such as artificial intelligence (AI) has the potential to improve efficiency and accuracy, while creating more innovative and creative solutions. Thus, understanding how AI can be leveraged for UX has important research and practical implications.Design/methodology/approachThis article builds on a systematic literature review approach and aims to understand how AI is used in UX design today, as well as uncover some prominent themes for future research. Through a process of selection and filtering, 46 research articles are analysed, with findings synthesized based on a user-centred design and development process.FindingsThe authors’ analysis shows how AI is leveraged in the UX design process at different key areas. Namely, these include understanding the context of use, uncovering user requirements, aiding solution design, and evaluating design, and for assisting development of solutions. The authors also highlight the ways in which AI is changing the UX design process through illustrative examples.Originality/valueWhile there is increased interest in the use of AI in organizations, there is still limited work on how AI can be introduced into processes that depend heavily on human creativity and input. Thus, the authors show the ways in which AI can enhance such activities and assume tasks that have been typically performed by humans.
Joana Casteleiro-Pitrez
17 April 2024
Generative Artificial Intelligence (GenAI) image tools hold the promise of revolutionizing a designer’s creative process. The increasing supply of this type of tool leads us to consider whether they suit future design professionals. This study aims to unveil if three GenAI image tools—Midjourney 5.2, DreamStudio beta, and Adobe Firefly 2—meet future designers’ expectations. Do these tools have good Usability, show sufficient User Experience (UX), induce positive emotions, and provide satisfactory results? A literature review was performed, and a quantitative empirical study based on a multidimensional analysis was executed to answer the research questions. Sixty users used the GenAI image tools and then responded to a holistic evaluation framework. The results showed that while the GenAI image tools received favorable ratings for Usability, they fell short in achieving high scores, indicating room for improvement. None of the platforms received a positive evaluation in all UX scales, highlighting areas for enhancement. The benchmark comparison revealed that all platforms, except for Adobe Firefly’s Efficiency scale, require enhancements in pragmatic and hedonic qualities. Despite inducing neutral to above-average positive emotions and minimal negative emotions, the overall satisfaction was moderate, with Midjourney aligning more closely with user expectations. This study emphasizes the need for significant improvements in Usability, positive emotional resonance, and result satisfaction, even more so in UX, so that GenAI image tools can meet future designers’ expectations.
Daftar Referensi
7 referensiArtificial intelligence (AI) for user experience (UX) design: a systematic literature review and future research agenda
E. Zamani Åsne Stige + 2 lainnya
29 Agustus 2023
PurposeThe aim of this article is to map the use of AI in the user experience (UX) design process. Disrupting the UX process by introducing novel digital tools such as artificial intelligence (AI) has the potential to improve efficiency and accuracy, while creating more innovative and creative solutions. Thus, understanding how AI can be leveraged for UX has important research and practical implications.Design/methodology/approachThis article builds on a systematic literature review approach and aims to understand how AI is used in UX design today, as well as uncover some prominent themes for future research. Through a process of selection and filtering, 46 research articles are analysed, with findings synthesized based on a user-centred design and development process.FindingsThe authors’ analysis shows how AI is leveraged in the UX design process at different key areas. Namely, these include understanding the context of use, uncovering user requirements, aiding solution design, and evaluating design, and for assisting development of solutions. The authors also highlight the ways in which AI is changing the UX design process through illustrative examples.Originality/valueWhile there is increased interest in the use of AI in organizations, there is still limited work on how AI can be introduced into processes that depend heavily on human creativity and input. Thus, the authors show the ways in which AI can enhance such activities and assume tasks that have been typically performed by humans.
Experimental evidence on the productivity effects of generative artificial intelligence
Shakked Noy Whitney Zhang
14 Juli 2023
We examined the productivity effects of a generative artificial intelligence (AI) technology, the assistive chatbot ChatGPT, in the context of midlevel professional writing tasks. In a preregistered online experiment, we assigned occupation-specific, incentivized writing tasks to 453 college-educated professionals and randomly exposed half of them to ChatGPT. Our results show that ChatGPT substantially raised productivity: The average time taken decreased by 40% and output quality rose by 18%. Inequality between workers decreased, and concern and excitement about AI temporarily rose. Workers exposed to ChatGPT during the experiment were 2 times as likely to report using it in their real job 2 weeks after the experiment and 1.6 times as likely 2 months after the experiment. Description Editor’s summary Automation has historically displaced human workers in factories (e.g., automotive manufacturing) or in performing routine computational tasks. Will generative artificial intelligence (AI) tools such as ChatGPT disrupt the labor market by making educated professionals obsolete, or will these tools complement their skills and enhance productivity? Noy and Zhang examined this issue in an experiment that recruited college-educated professionals to complete incentivized writing tasks. Participants assigned to use ChatGPT were more productive, efficient, and enjoyed the tasks more. Participants with weaker skills benefited the most from ChatGPT, which carries policy implications for efforts to reduce productivity inequality through AI. —EEU The assistive chatbot ChatGPT raises productivity in professional writing tasks and reduces productivity inequality.
Deceptive AI Ecosystems: The Case of ChatGPT
Ştefan Sarkadi Yifan Xu + 1 lainnya
18 Juni 2023
ChatGPT, an AI chatbot, has gained popularity for its capability in generating human-like responses. However, this feature carries several risks, most notably due to its deceptive behaviour such as offering users misleading or fabricated information that could further cause ethical issues. To better understand the impact of ChatGPT on our social, cultural, economic, and political interactions, it is crucial to investigate how ChatGPT operates in the real world where various societal pressures influence its development and deployment. This paper emphasizes the need to study ChatGPT "in the wild", as part of the ecosystem it is embedded in, with a strong focus on user involvement. We examine the ethical challenges stemming from ChatGPT’s deceptive human-like interactions and propose a roadmap for developing more transparent and trustworthy chatbots. Central to our approach is the importance of proactive risk assessment and user participation in shaping the future of chatbot technology.