This statistic shows survey respondents answer to a question about how they preferred to learn about nonprofit organizations in the United States. This question was specifically asked to people from generation Y aged 20 to 35 years (also referred to as Millennials). 65 percent of respondents said they preferred to learn about nonprofit organizations through their websites.

Abstract This study aims to identify the predominant career profiles among Generation Y in Brazil and investigate the influence of demographic and professional characteristics in these profiles. Career profiles are defined as combinations of the presence of Boundaryless and Protean career attitudes. This study is descriptive, the sample is non-probabilistic and intentional and consists of 2,376 people. Cluster Analysis and Chi-square tests were used. The results show that people from Generation Y have a high presence of attitudes related to new careers and that these new careers are associated with high education and high income, mainly the Boundaryless career. However, there is a small portion of the sample that doesn’t present new career attitudes, indicating that this is just a movement and cannot be considered a reality for all studied subjects.

In 2020, around **** percent of generation Z internet users in Thailand participated in e-learning. This was followed by generation Y at **** percent. The internet has become an essential part of Thai people's lifestyle of all ages. The number of internet users in Thailand was forecasted to reach almost ** million by 2025.

The rapid integration of data-intensive, AI-powered technologies in education, often driven by non-EU tech industries, has raised concerns about their social impact, sustainability, and alignment with ethical principles (Rivera-Vargas, 2023; Selwyn, 2023; Williamson, 2023). While the EU has advanced regulatory efforts, such as the AI Act and Ethical Guidelines for AI in Education (Directorate-General for Education, 2022), translating ethical principles into practice remains ambiguous and fragmented (Morley et al., 2023). Despite the proliferation of over 80 ethical frameworks by 2019 (Morley, op.cit), operationalizing these into meaningful educational practices is fraught with ambiguities and challenges. Ethical guidelines are often portrayed as “complementary” tools to mitigate technological risks, yet their transformative potential remains limited (Green, 2021). The funding landscape for projects aimed at fostering knowledge generation, innovation, transformation, and research in the educational sector also encounters significant challenges. The European Union, through funding programs such as Erasmus+ and Horizon Europe, supports educational projects addressing key challenges. Recently, these programs have emphasized the ethical dimension, highlighting the need to align technological and educational advancements with robust principles. However, this focus raises questions about how these values are effectively implemented in practice.

In this context, the present study examines how EU-funded educational projects address ethical principles through a Mixed Methods approach embedding Text-mining and Discourse Analysis. Through a documentary investigation of the Erasmus+ project database, four key searches were conducted, revealing significant gaps. Among the more than 2,000 completed projects, few included ethical reflections on AI or data use, and none explicitly addressed critical issues such as digital sovereignty, platformization, or activism. The initiatives predominantly focused on technical skills (e.g., coding, data analysis), while overlooking critical competencies such as resistance and ethical-political engagement.

Preliminary findings suggest a persistent reliance on techno-solutionist narratives, where ethical guidelines are often reduced to mere compliance checklists, offering minimal transformative value. This misalignment between EU ethical frameworks and project outcomes raises critical concerns regarding the reinforcement of corporate interests and techno-deterministic approaches. The study underscores the necessity of bridging this gap, ensuring that public funding supports socially just, sustainable, and inclusive educational practices. It advocates for funding criteria that emphasize critical perspectives on technology, advancing meaningful agency and systemic transformation beyond superficial ethical commitments (Floridi, 2023).

This record contains:

• The presentation used during the Conference
• The dataset adopted with 3204 EU-Project metadata
• An R script with the preliminary analysis adopted - https://rpubs.com/dcalderon/ECCES_2025">This is also published on RPUBS
• A Python script and the resulting HTML with the creation of an interactive bipartite graph.

References

Directorate-General for Education, Y. (2022). Ethical guidelines on the use of artificial intelligence (AI) and data in teaching and learning for educators. Publications Office of the European Union. https://data.europa.eu/doi/10.2766/153756

Floridi, L. (2023). The Ethics of Artificial Intelligence: Principles, Challenges , and Opportunities. Oxford University Press.

Green, B. (2021). The Contestation of Tech Ethics: A Sociotechnical Approach to Ethics and Technology in Action. http://arxiv.org/abs/2106.01784

Jacovkis, J., Rivera-Vargas, P., Parcerisa, L., & Calderón-Garrido, D. (2022). Resistir, alinear o adherir. Los centros educativos y las familias ante las BigTech y sus plataformas educativas digitales. Edutec. Revista Electrónica de Tecnología Educativa, 82, Article 82. https://doi.org/10.21556/edutec.2022.82.2615

Morley, J., Kinsey, L., Elhalal, A., Garcia, F., Ziosi, M., & Floridi, L. (2023). Operationalising AI ethics: Barriers, enablers and next steps. AI & SOCIETY, 38(1), 411–423. https://doi.org/10.1007/s00146-021-01308-8

Raffaghelli, J. E. (2022). Educators’ data literacy: Understanding the bigger picture. In Learning to Live with Datafication: Educational Case Studies and Initiatives from Across the World (pp. 80–99). Routledge. https://doi.org/10.4324/9781003136842

Rivera-Vargas, C. C., Pablo. (2023). What is ‘algorithmic education’ and why do education institutions need to consolidate new capacities? In The New Digital Education Policy Landscape. Routledge.

Selwyn, N. (2023). Lessons to Be Learnt? Education, Techno-solutionism, and Sustainable Development. In Technology and Sustainable Development. Routledge.

Williamson, B. (2023). The Social life of AI in Education. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-023-00342-5