Opting out of generative AI: a behavioral experiment examining the role of education in Perplexity AI avoidance

Over the past few years, generative AI has had an increasing impact on society, including an impact on how people learn and work. As a part of preparing students, at AP and bachelor levels, for the generative AI–assisted workplace, small-scale surveys were conducted and subsequently used as parts of task descriptions and structured dialogue with the students. Findings suggest that students see generative AI as a useful tool in their education. However, dialogue with students also indicates a need for further guidance on how to use generative AI in learning processes. Just as more guidance is needed to develop insights into generative AIs understanding of key concepts like relevance, as well as limitations to generative AIs ability to be helpful in more complicated workflows in the workplace. This said, exact answers from surveys are probably less important than using the questions to spark dialogue with students about the assumptions, biases, and implications of using generative AI in education and in the workplace. Any final conclusions at this stage would likely be premature anyway. However, the dialogue with students about generative AI’s role in education and in the workplace is seen as essential to question, analyze, understand, and set future directions.

The emergence of Generative AI (GenAI) in education marks a transformative shift in teaching, learning, and assessment practices. GenAI technologies have evolved from being simple conversational agents to highly advanced systems capable of generating human-like text, solving complex problems, assisting in creative writing, tutoring, and even providing personalized feedback to students. This paper explored the use of GenAI in education with emphasis on its implications towards academic integrity. Information and Communications Technology (ICT) college students (n=30) were purposively sampled to be interviewed regarding their experiences and perceptions about the use of GenAI in their program. Thematic analysis was carried out to identify emerging themes and assess the implications of GenAI use in education, particularly ICT learning processes. Students believed that GenAI offers significant benefits, such as personalized learning, assistance in creative writing, tutoring, coding, and grading, which enhance students’ learning experiences by providing instant feedback and helping them understand difficult concepts. Concerns about over-reliance on AI, plagiarism, and academic dishonesty have emerged, as some students use AI tools to bypass intellectual effort, raising questions about the authenticity of their work. ICT students expressed concerns about GenAI fostering cheating and undermining academic independence. Despite these issues, students remain optimistic about GenAI’s role in education, advocating for clear guidelines on its appropriate use to balance its benefits with the need for academic integrity. The integration of GenAI in educational settings necessitates careful management to ensure that it supports, rather than diminishes, the learning process.

Generative AI (GenAI) technologies have been widely adopted by college students since the launch of ChatGPT in late 2022. While the debate about GenAI’s role in higher education continues, there is a lack of empirical evidence regarding whether and when these technologies can improve the learning experience for college students. This study utilizes data from a survey of 72,615 undergraduate students across 25 universities and colleges in China to explore the relationships between GenAI use and student learning engagement in different learning environments. The findings reveal that over sixty percent of Chinese college students use GenAI technologies in Academic Year 2023–2024, with academic use exceeding daily use. GenAI use in academic tasks is related to more cognitive and emotional engagement, though it may also reduce active learning activities and learning motivation. Furthermore, this study highlights that the role of GenAI varies across learning environments. The positive associations of GenAI and student engagement are most prominent for students in “high-challenge and high-support” learning contexts, while GenAI use is mostly negatively associated with student engagement in “low-challenge, high-support” courses. These findings suggest that while GenAI plays a valuable role in the learning process for college students, its effectiveness is fundamentally conditioned by the instructional design of human teachers.

This self-study highlights the collaborative journey of two elementary teacher educators from a rural institution as they navigated the integration of Generative AI (GenAI) into teaching and research. To grow their AI literacy, they engaged in reflective practices, collaborative discussions, and hands-on implementation of GenAI technologies. Through this process, they documented their experiences with AI-driven chatbots, offering insights into their learnings and concerns. Their reflections underscored the importance of understanding GenAI’s role in education, the challenges of integrating GenAI tools effectively, and the potential of GenAI in teaching and learning. The educators concluded that while GenAI can augment human capabilities, it cannot replace human expertise due to its limitations. By capturing their journey, this study contributed to the growing discourse on AI literacy among teacher educators, emphasizing the need for upskilling and ongoing professional development in the face of rapidly evolving technologies.

The rapid uptake of generative AI (GenAI) tools in academic contexts has prompted a wave of responses regarding pedagogical reconfiguration, assessment, shifting academic norms, values, and practices. While scholarly discourse increasingly examines the benefits, limitations, and ethical implications of GenAI in higher education, students’ perspectives remain underrepresented and often limited to survey-based research focused on academic integrity and plagiarism. To gain a deeper understanding of the multifaceted role GenAI plays in students’ academic lives, this study draws on 14 semi-structured interviews with Humanities (Research) Master’s students at a major Dutch university and is guided by the following research question: How do students navigate their use of GenAI tools in academic contexts? The findings reveal critical self-reflections on skills development, learning trajectories, and the institution’s role in shaping their perspectives, decision-making, and lived experiences. We find that students do not accept GenAI’s role in education as a fait accompli, but instead actively engage in boundary-making practices and legitimization strategies in context-dependent, reflective, and relational ways. These insights serve as a critical counterpoint to dominant techno-solutionist and technologically deterministic discourses, drawing attention to the need for ethical guidelines grounded in the relational dynamics at the intersection of technology and higher education.

Generative AI (GAI) is rapidly transforming the work processes of academic staff of higher education institutions (HEIs). Previous study focused on students’ use of GAI but the impact of GAI on faculty remains underexplored, especially in business schools in which there is a strategic importance in fostering innovation and developing future leaders. The integration of Generative AI tools, such as ChatGPT, is revolutionizing how business educators carry out their work in business schools. This paper presents a scoping review of a structured literature search identifying a core canon of recent articles addressing how GAI is changing the work conducted in business schools of Higher Educational Institutions. Literature searches were conducted in Web of Science (WoS) and Education Resources Information Centre (ERIC) databases from 2019 to 2024, using tailored search terms encompassing GAI, academic staff, business education and HEIs. A total of 502 articles were identified, with 211 from WoS and 291 from ERIC. After several stages of manual screenings, 15 final articles were obtained for this scoping review. The findings of the analysis reveal that GAI tools have integrated in the four major teaching work processes in business education: Curriculum Design, Pedagogical Methods, Student Engagement and Interaction and Assessments. In addition, the study surprisingly figured out that much less emphasis was given to the research side of the duties of academic staff. Our findings suggest that, under the human-GAI collaboration in teaching work processes in business schools, the role of educators have changed to be: Quality Controller, Scenario Facilitator, Strategic Mentor and Ethical Gatekeeper for the four major teaching work. Future research should focus on discipline-specific study, empirical evaluations of teaching work processes at tool-specific level, and in different cultural context. More research should also be conducted on researching work processes and institutional administration. This study contributes to the discourse of digital transformation and the potential of human-GAI collaboration in higher education.

This study examines the role of Generative AI in school art education, focusing on enhancing Creativity and Convergence Competency. It explores a Generative AI-based art education model and proposes an Art Game as a practical tool. Effective Generative AI integration strategies were developed based on school environments and student needs. In elementary education, Generative AI-supported visual exploration and creative idea generation were emphasized. Middle and high school programs focused on critical thinking and art appreciation through historical and analytical approaches. At the university level, experimental Generative AI-driven projects incorporated ethical and philosophical discussions to deepen artistic expression. The Persona-based Artist concept in the Art Game encouraged personal and emotional engagement, fostering creative collaboration with Generative AI. By clarifying Generative AI’s role in education, this study provides a framework for its effective use while addressing implementation challenges. It proposes a practical model that enables students to confidently create and innovate with Generative AI, strengthening their Creativity and Convergence Competency.

This article articulates the nuanced challenges of integrating Generative AI (GenAI) into educational settings, aiming to dispel overly simplistic narratives driven by unwarranted enthusiasm or unfounded apprehensions. It introduces a conceptual framework for the application of GenAI within higher education, delineating four key strategies that leverage the dual roles of educators—as both creators and designers—while positioning GenAI as either a facilitative agent (creature) or a utilitarian tool. The identified strategies—Interactive Co-Creation, Adaptive Design, Learning Scaffold, and Efficient Structuring—underscore GenAI’s potential to revolutionize teaching methodologies by enabling personalized education, enhancing content quality, and expediting course development processes. Emphasizing GenAI’s capacity to cater to diverse student needs, simplify educational content creation, and foster engaging learning environments, the model provides educators with a roadmap for integrating GenAI into their instructional practices to harness the full potential of educational technology.Generative AI; educator’s role; instructional design

The emergence of Generative AI (GAI) in education brings both benefits and challenges. As GAI tools become more common in schools, concerns about ethics, academic honesty, and how well teachers and students adapt to GAI are a major concern. This chapter explored the challenges of using GAI as experienced by teachers and students in rural areas, where access to technology and digital skills may affect AI use. Following a Husserlian phenomenological research design, participants were interviewed, and the transcripts were examined using thematic analysis. The findings show that teachers struggle to balance GAI tools with traditional teaching, while students face challenges with digital literacy and academic integrity. Despite these issues, both teachers and students see the potential of GAI tools in improving learning. The chapter emphasizes the need for clear ethical guidelines, digital skills training, and school support to ensure GAI tools are used responsibly. These findings show the importance of further research on AI's role in education.

The emergence of generative AI technologies has provoked considerable debate among educators regarding their role in education. This study is an investigation of the benefits, disadvantages, and potential strategies for integrating generative AI in educational settings by analyzing societal impacts based on a literature review. We have surveyed the influence of generative AI in education through sources from peer-reviewed journals. The main findings show that generative AI can enhance accessibility and customization in learning for individual learners' needs and pacing. But there are problems with algorithmic biases, discrimination, and data privacy issues, too. This study advocates for mitigating bias, data transparency, and promotion and evaluation of AI policy and research. Generative AI in education hinges on how it is responsibly integrated and observes ethical guidelines, by way of the constant assessment that will guarantee its potential in revolutionizing learning.

This systematic literature review rigorously evaluates the impact of Generative AI (GenAI) on academic integrity within higher education settings. The primary objective is to synthesize how GenAI technologies influence student behavior and academic honesty, assessing the benefits and risks associated with their integration. We defined clear inclusion and exclusion criteria, focusing on studies explicitly discussing GenAI’s role in higher education from January 2021 to December 2024. Databases included ABI/INFORM, ACM Digital Library, IEEE Xplore, and JSTOR, with the last search conducted in May 2024. A total of 41 studies met our precise inclusion criteria. Our synthesis methods involved qualitative analysis to identify common themes and quantify trends where applicable. The results indicate that while GenAI can enhance educational engagement and efficiency, it also poses significant risks of academic dishonesty. We critically assessed the risk of bias in included studies and noted a limitation in the diversity of databases, which might have restricted the breadth of perspectives. Key implications suggest enhancing digital literacy and developing robust detection tools to effectively manage GenAI’s dual impacts. No external funding was received for this review. Future research should expand database sources and include more diverse study designs to overcome current limitations and refine policy recommendations.

"Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions," edited by Beth Buyserie and Travis N. Thurston, is a timely and essential addition to the ongoing dialogue about AI's role in education. This book thoroughly examines the opportunities and challenges that AI technologies bring to both traditional and online classroom environments. This comprehensive volume delves into the multifaceted impact of AI on educational practices, offering insights into how these technologies can enhance learning experiences and pedagogical strategies. The editors, Buyserie and Thurston, have curated a collection of essays and studies that highlight the transformative potential of AI in personalizing learning, automating administrative tasks, and providing real-time feedback to students.

Generative AI has seen major developments in recent years, enhancing the realism of synthetic images, also known as computer-generated images. In addition, generative AI has also made it possible to modify specific image characteristics through image editing. Previous work has developed methods based on generative adversarial networks (GANs) for generating realistic images, in particular faces, but also to modify specific features. However, this work has never been applied to specific animal species. Moreover, the assessment of the results has been generally done subjectively, rather than quantitatively. In this article, we propose an approach based on methods for generating images of faces of male or female mandrills, a non-human primate. The main novelty of proposed method is the ability to edit their sex by identifying a sex axis in the latent space of a specific GAN. In addition, we have developed an assessment of the sex levels based on statistical features extracted from real image distributions. The experimental results we obtained from a specific database are not only realistic, but also accurate, meeting a need for future work in behavioral experiments with wild mandrills.

This publication explores the potential and actual use of generative AI (GAI) in business education at Arcada University of Applied Sciences, with a particular focus on the teacher’s role in integrating GAI into course modules. Research suggests that GAI can enhance teaching and student learning by offering personalized and engaging experiences. The aim of the study is to contribute to a deeper understanding of AI in education and to promote knowledge about the responsible integration of AI into business education. A further objective is to develop teaching practices that prepare students to engage with the technology responsible in their future professional lives.We investigate teachers’ perceptions of AI and their reflections on working with it. Additionally, we describe our collaborative work on these issues over the course of a year. During spring and autumn 2024, we conducted research into our own teaching practices in relation to AI within our teaching team. In parallel, we collected data from workshops where current AI practices, tools, challenges, and educational needs were discussed.The project also provides insights into how AI can be integrated across various areas of business education and lays the foundation for future research on optimizing AI use in educational contexts.We identify challenges related to safety, bias, and academic integrity. Finally, we discuss future trends and the evolving role of teachers in an educational landscape where AI is embedded in the learning environment. A balanced use of AI is recommended, and continued work is needed to ensure responsible, reliability, and ethical integration.The publication aligns with strategic goals concerning sustainable digital solutions and responsible AI. We argue that the publication contributes to the broader discourse on high-quality, sustainable, and responsible education. Our project supports Sustainable Development Goals 4 and 11, and peer learning has been central throughout our process.

Launched in November 2022, OpenAI’s ChatGPT garnered over 100 million users within two months, sparking a surge in research and concern over potential risks of extensive AI experiments. The article, originating from a conference presentation by Tsinghua University and NTHU, Taiwan, provides a nuanced overview of Generative AI. It explores the classifications, applications, governance challenges, societal implications, and development trajectory of Generative AI, emphasizing its transformative role in employment and education. The piece highlights ChatGPT’s significant impact and the strategic adaptations required in various sectors, including medical education, engineering, information management, and distance education. Furthermore, it explores the opportunities and challenges associated with incorporating ChatGPT in educational settings, emphasizing its support in facilitating personalized learning, developing 21st-century competencies, fostering self-directed learning, and enhancing information accessibility. It also illustrates the integration of ChatGPT and text-to-image models in high school language courses through the lens of new literacies. The text uniquely integrates three layers of discourse: introductions to Generative AI by experts, scholarly debates on its merits and drawbacks, and practical classroom applications, offering a reflective snapshot of the current and potential states of Generative AI applications while emphasizing the interconnected discussions across various layers of discourse.