Artificial Intelligence for All? Brazilian Teachers on Ethics, Equity, and the Everyday Challenges of AI in Education

TL;DR

The paper investigates Brazilian K-12 teachers' perceptions of Generative AI in education, focusing on ethics, equity, and everyday classroom challenges. Using a nationwide quantitative survey (n=346) mapped to the Framework of Teachers' Digital Competencies, the authors quantify knowledge, interest, perceived benefits, and barriers to adoption. Key findings show high interest in AI for content creation, planning, and assessment, but widespread training gaps and infrastructure limitations persist, reinforcing a bottom-up adoption pattern. The study offers policy-relevant recommendations—online, contextualized teacher training; formal integration of ethics and digital citizenship; and investment in infrastructure and technical support—to enable ethical, inclusive AI adoption in Brazilian schools. Together, the results highlight that achieving 'AI for all' hinges on coordinated public policy and targeted capacity-building to overcome regional and institutional inequities.

Abstract

This study examines the perceptions of Brazilian K-12 education teachers regarding the use of AI in education, specifically General Purpose AI. This investigation employs a quantitative analysis approach, extracting information from a questionnaire completed by 346 educators from various regions of Brazil regarding their AI literacy and use. Educators vary in their educational level, years of experience, and type of educational institution. The analysis of the questionnaires shows that although most educators had only basic or limited knowledge of AI (80.3\%), they showed a strong interest in its application, particularly for the creation of interactive content (80.6%), lesson planning (80.2%), and personalized assessment (68.6%). The potential of AI to promote inclusion and personalized learning is also widely recognized (65.5%). The participants emphasized the importance of discussing ethics and digital citizenship, reflecting on technological dependence, biases, transparency, and responsible use of AI, aligning with critical education and the development of conscious students. Despite enthusiasm for the pedagogical potential of AI, significant structural challenges were identified, including a lack of training (43.4%), technical support (41.9%), and limitations of infrastructure, such as low access to computers, reliable Internet connections, and multimedia resources in schools. The study shows that Brazil is still in a bottom-up model for AI integration, missing official curricula to guide its implementation and structured training for teachers and students. Furthermore, effective implementation of AI depends on integrated public policies, adequate teacher training, and equitable access to technology, promoting ethical, inclusive, and contextually grounded adoption of AI in Brazilian K-12 education.

Figures (2)

• Figure 1: Characteristics of the sample (n = 346). The chart shows the distribution of participants by occupation, gender, age group, region, educational level, years of experience, school location, and institutional affiliation. These data provide an overview of the profile of the professionals who responded to the questionnaire, highlighting the diversity of educational contexts and teaching experiences.
• Figure 2: Summary of respondents’ perceptions regarding AI in education (n=346). The figure illustrates the participants’ knowledge, perceived benefits, and engagement with AI across three dimensions.