Landingpage for conference session on the IPILM blog: 7th IPILM-Conference
Published by Fabienne Katharina Müller
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.
🟢Advantages
of AI in Job Market (Cazzaniga et al. 2024), (UNESCO 2024),(Holmes et al. 2019)
- AI enhances task efficiency for high-skilled workers and increases productivity, allowing them to focus on strategic and creative tasks.
- AI creates hybrid roles that integrate human judgment with AI-assisted decision-making, expanding job categories in data analytics, automation management, and AI oversight.
- AI-powered job platforms improve matching accuracy by analysing skills, experience, and job requirements, supporting equal access to opportunities.
- Countries with high AI preparedness gain new employment pathways through digital infrastructure, training, and innovation ecosystems.
- AI adoption pushes workers to acquire modern digital skills, improving long-term employability and adaptability.
🔴Disdvantages
of AI in Job Market (Cazzaniga et al. 2024)
- AI-driven automation replaces repetitive, low-complexity tasks, increasing unemployment risk for low-skilled and ageing workers.
- Differences in AI readiness create unequal job opportunities globally, widening economic and employment gaps.
- AI may disproportionately affect women and certain professional groups, increasing vulnerability to job displacement.
- AI leads to wage inequality, where high-skilled workers gain from productivity increases while low-skilled workers face stagnant or declining wages.
- Workers displaced by AI find it harder to transition into new roles without advanced digital skills, increasing long-term unemployment risks.
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
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.
🗣️Discussion
Which aspects stood out particularly in relation to this topic?
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 .
