AI, Inclusion, and Volunteer Practice: An Ethnographic Study of Student Engagement in AINCLUSION
Meeting
Agenda
- Letizia will present AINCLUSION and the research activities related to it
- Each participant is invited to present her/him self and their thoughts about how to approach the research activity.
- Future meetings and plans
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Microsoft Teams meeting
Join: https://teams.microsoft.com/meet/377281282084394?p=4sSNfELbqY4lf1g7Qh
Meeting ID: 377 281 282 084 394
Passcode: L5ej2MB2
Description
This master’s thesis invites motivated Computer Science students at NTNU to combine volunteer work, AI expertise, and societal engagement by contributing to the activities of AINCLUSION (https://ainclusion.com). AINCLUSION is a non-profit association that promotes inclusive, accessible, and responsible approaches to artificial intelligence in society.
The student will participate as a volunteer in AINCLUSION’s ongoing activities (workshops, events, community outreach, digital content, or other initiatives). Through this engagement, the student will conduct an ethnographic study focusing on:
- observing real-world interactions,
- participating in community practices,
- reflecting critically on their own role and experiences,
- analyzing how AI-driven tools, discussions, and educational activities influence different social groups.
Ethnography will serve both as a methodological framework and as a reflexive practice. The student will maintain field notes, document interactions, collect feedback from participants, and analyze how volunteer work contributes to the association’s goals of inclusion, empowerment, and AI awareness.
This thesis is particularly suitable for students who:
- are motivated by volunteer work,
- want to make a positive contribution to society,
- wish to explore AI in real-world, human-centered contexts,
- are comfortable with reflective and qualitative research methods.
Strong foundational knowledge in artificial intelligence is required in order to analyze AI-related content, evaluate the technological aspects of the association’s activities, and interpret how AI impacts the communities AIinclusion engages with.
Research Questions (examples)
- How can volunteer participation in AINCLUSION support inclusive and responsible AI education?
- What challenges and opportunities arise when communicating AI concepts to diverse societal groups?
- How does ethnographic reflection help identify gaps in AI awareness and inclusion?
- In what ways does volunteering shape the student’s own understanding of ethical, social, and human-centered AI?
Methodology
The thesis will use ethnographic methods, such as:
- participant observation during volunteer work,
- reflective journals and field notes,
- qualitative interviews if appropriate,
- analysis of workshop materials, communication, and AI-related activities.
Ethical considerations—especially regarding consent, privacy, and the handling of qualitative data—must be documented and addressed in line with NTNU guidelines.
Expected Contributions
- A deeper understanding of how AINCLUSION efforts work in practice.
- Insight into how AI literacy can be strengthened in society.
- A reflexive account of the student’s own engagement and development as a responsible AI practitioner.
- Recommendations for improving future AINCLUSION activities and similar volunteer-driven initiatives.
Alignment with NTNU Evaluation Criteria
The thesis will be evaluated based on NTNU’s standard criteria, such as:
1. Scientific quality
- Clear research questions rooted in AI and human-centered computing.
- Proper application of ethnographic and qualitative methods.
2. Methodological rigor
- Systematic collection, documentation, and analysis of qualitative data.
- Transparent and well-argued methodological choices.
3. Academic independence
- Ability to plan, carry out, and reflect on volunteer activities and fieldwork.
- Critical, reflective writing grounded in theory.
4. Ethical reflection
- Consideration of research ethics, participant privacy, and responsible use of AI.
5. Contribution and relevance
- Societal relevance through engagement with AINCLUSION and public understanding of AI.
- Practical recommendations and conceptual insights.
6. Communication and structure
- Clear, well-organized thesis with strong academic writing.
- Precise use of AI terminology and qualitative research vocabulary.
Supervision and Collaboration
The student will work closely with:
- NTNU academic supervisor
- AINCLUSION mentors knowledgeable about the association’s activities.
