IPILM is a learning environment that promotes collaborative knowledge construction among students from diverse cultural backgrounds. Educators and learners from various countries take part in an intercultural learning endeavor.

Tag: possibilities

AI and value propositions for stakeholder groups

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The central aspects of our presentation will give you an introduction into use cases for AI, stakeholder interest and potential benefits AI promises.

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Embedded Youtube-Screencast: “IPILM 2025: AI and value propositions for stakeholder groups”.

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Session report and key aspects:

The presentation started with a brief introduction to AI and generative AI, followed by the section on roles of AI. There, three potential areas were introduced: customer experience, talent management and productivity, as well as risk management and governance.

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Particular attention was given to introducing the stakeholder groups:
individual, organizational, and national and international stakeholders. The interest and power structure of each group was introduced, and showed their connectivity and interdependence.

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The perceived value of AI for individual stakeholders depends on life stage and occupational status, aligning with the distinct priorities of each group (UN Human Development Report 2025).

Used in the right way, AI may offer an opportunity to expand human capabilities. Institutional and social choices can enable AI to expand people’s capabilities and agency, as illustrated through AI’s applications for people with disabilities, care systems and gender equality, as well as in conceptualizing and mitigating AI bias. The following section on value propositions presented potential positive values.

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A part of the presentation also addressed several risks connected to AI. With a critical eye, we highlighted the risk of algorithmic bias, AI’s environmental impact, data privacy breaches, lack of transparency and cognitive debt.

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Discussion

This section addresses the key questions raised during the conference and summarizes the main points of discussion among participants.

The group was asked about their individual views on the personal value of AI tools. A variety of answers was given: while there were participants who did not view AI as particularly valuable, other participants saw great personal value in using the tools. Depending on the use cases and tasks, the majority saw a positive value.

Referencing the keynote speech on mindfulness, an open-ended question wanted the participants to share if they thought of AI as an inevitable feature and if humans would lose innate skills through the use of AI. This question sparked a discussion with different directions and focal points. The art of photography was named as an example for all three issues and sparked a dynamic discussion.

Another question wanted the participants to share their views on whether AI literacy should be introduced at an earlier age. The participants discussed that other types of literacy skills were introduced during childhood to prepare children at an early age and continually increase their skill set. The group members came to the conclusion that it should be similar with AI literacy education.

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Additional resources

AI and Access, e.g. Education, Job Market

Landingpage for conference session on the IPILM blog: 7th IPILM-Conference

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Quick facts and insights

Role of AI
  • AI broadens access via adaptive tutoring, predictive analytics, and multilingual support (Yeo & Lansford, 2025).
  • ITS (Intelligent Tutoring Systems) demonstrate measurable improvements in learning outcomes in diverse contexts (Holmes et al., 2019).
  • UNESCO (2024) stresses AI’s potential in low‑resource environments when supported by policy.
What are important questions?
  • What is AI’s role in improving access to education for diverse learners?
  • How does AI help in personalised learning, and why is it important for inclusive education?
  • In what ways is AI transforming the job market and creating new opportunities?
  • What skills do learners need to stay relevant in an AI-driven job environment?
  • How can AI support equal access to job information and career guidance?

Summary of the topic

This blog examined the role of artificial intelligence in improving access to education and its broader implications for the job market. A key focus was on how AI can support inclusive education through personalized learning, intelligent tutoring systems, adaptive feedback, and multilingual support, thereby addressing diverse learning needs. At the same time, the presentation critically discussed structural and ethical challenges, including algorithmic bias, data protection and privacy risks, limited transparency of AI systems, and generally low levels of AI literacy among users. In addition, the presentation highlighted global inequalities in access to AI, emphasizing that countries with stronger digital infrastructure and higher AI preparedness benefit more from AI adoption, while others risk being left behind. Two empirical case studies were used to support these points: one analyzing teachers’ trust in AI in education across different countries, and another examining the impact of generative AI on employment, skill requirements, and labor market inequalities. Overall, this emphasized that AI offers significant opportunities, but only if implemented responsibly, ethically, and with equal access in mind.

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https://www.youtube.com/watch?v=l6d_0PB0Pbg
The video shows why job losses are occurring in some areas, which professions are particularly affected, and which skills will be crucial in the future. It also discusses how to strategically develop in your current job, the continuing role of education, and why building a strong personal positioning is becoming increasingly important in the age of AI. Finally, a clearly structured three-step approach is presented for remaining professionally relevant in the long term.
https://www.youtube.com/watch?v=l6d_0PB0Pbg

🟢Advantages of AI in Education

(UNESCO, 2024), (Yeo & Lansford, 2025), (Holmes et al., 2019)

Healthcare

AI simulations allow students to practise surgeries and diagnoses safely.

Predictive models help students understand real-world medical decision-making.

Multilingual virtual assistants support global medical learners.

Finance

AI financial modelling tools prepare students for real-market scenarios.

Risk-assessment simulations improve practical decision-making skills.

Adaptive learning helps students strengthen weak conceptual areas.

Education

Personalised learning using reinforcement-learning models.

ITS improves learning outcomes across diverse learners.

AI improves accessibility for learners with disabilities through speech-to-text, translation, etc

Aktivieren Sie JavaScript um das Video zu sehen.
https://www.youtube.com/watch?v=hJP5GqnTrNo
Al Khan, founder of Khan Academy, is convinced that artificial intelligence can greatly improve the education system. He shows how AI can support students through personalized learning assistance and teachers through digital assistance systems, and introduces new features of the educational chatbot Khanmigo.
https://www.youtube.com/watch?v=hJP5GqnTrNo

🔴Disadvantages of AI in Education

(Marín et al., 2025), (Sahar & Munawaroh, 2025), (Al-Zahrani & Alasmari, 2024)

Healthcare

In the healthcare sector, bias, data protection issues, and a lack of transparency can lead to incorrect or unfair AI decisions, while a lack of human contact and low AI literacy further complicate care.

Finance

In the financial sector, bias, data protection risks, and non-transparent AI models have a significant impact on fairness and trust, especially when professionals lack AI expertise.

Education

In education, the disadvantages of AI mainly concern academic integrity, data protection, algorithmic fairness, lack of human support, and generally low AI literacy.


Key findings from two relevant case studies

Case Study 1 Job Market
Gen-AI: Artificial Intelligence and the Future of Work.
(Cazzaniga et al. 2024)
  • Highly skilled jobs are most affected by AI, but also benefit the most (increased productivity, better wages).
  • Low-skilled and older workers are at greatest risk of being disadvantaged by AI.
  • Women and knowledge workers are particularly exposed to AI.
  • AI can exacerbate inequalities, especially in countries with poor digital preparedness.
  • The US/UK are well prepared, emerging markets less so, resulting in large global differences.
Case Study 2 Education
What Explains Teachers’ Trust in AI in Education Across Six Countries?“(Viberg et al., 2025)
  • Perceived benefits ↑ → Trust ↑; Concerns ↑ → Trust ↓. These two were the strongest predictors of trust.
  • AI self-efficacy & AI understanding strongly increased perceived benefits and reduced concerns — indirectly boosting trust.
  • Demographics (age, gender, education) did not significantly influence trust.
  • Cultural values mattered: High uncertainty avoidance, collectivism, and masculinity were associated with differences in trust and concerns.
  • Cross-country variation: Brazil, Israel, and Japan showed higher trust; Norway, Sweden, and USA showed lower trust after adjustments.

Watch our Screencast here🔽

https://www.youtube.com/watch?v=6FHxBVBWicE


📖References

Click here for references
  • Al-Zahrani, A.M., Alasmari, T.M. (2024): Exploring the impact of artificial intelligence on higher education: The dynamics of ethical, social, and educational implications. Humanit Soc Sci Commun 11, 912 https://doi.org/10.1057/s41599-024-03432-4.
  • Cazzaniga et al. (2024): “Gen-AI: Artificial Intelligence and the Future of Work.” IMF Staff Discussion Note SDN2024/001, International Monetary Fund, Washington, DC. https://doi.org/10.5089/9798400262548.006 .
  • Holmes, W., Bialik, M., & Fadel, C. (2019): Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.https://curriculumredesign.org/wp-content/uploads/AIED-Book-Excerpt-CCR.pdf .
  • Marín, Y. R., Caro, O. C., Rituay, A. M. C., Llanos, K. A. G., Perez, D. T., Bardales, E. S., Tuesta, J. N. A. & Santos, R. C. (2025): Ethical Challenges Associated with the Use of Artificial Intelligence in University Education. Journal Of Academic Ethics, 23(4), 2443–2467. https://doi.org/10.1007/s10805-025-09660-w .
  • Sahar, R. & Munawaroh, M. (2025): Artificial intelligence in higher education with bibliometric and content analysis for future research agenda. Discover Sustainability, 6(1). https://doi.org/10.1007/s43621-025-01086-z .
  • UNESCO. (2024): AI and inclusive education: Policy guidance for promoting equity. United Nations Educational, Scientific and Cultural Organization. https://doi.org/10.54675/PCSP7350 .
  • Viberg, O., Cukurova, M., Feldman-Maggor, Y., Alexandron, G., Shirai, S., Kanemune, S., Wasson, B., Tømte, C., Spikol, D., Milrad, M., Coelho, R. & Kizilcec, R. F. (2025): What Explains Teachers’ Trust in AI in Education Across Six Countries? International Journal of Artificial Intelligence in Education, 35, 1288–1316. https://doi.org/10.1007/s40593-024-00433-x.
  • Yeo, G. & Lansford, J. E. (2025): Effects of Artificial Intelligence on Educational Functioning: A Review and Meta-Analysis. Educational Psychology Review, 37(4). https://doi.org/10.1007/s10648-025-10085-5 .