Algorithmic affordances for responsible recommender systemsin education

Suzanne van Rossen (Speaker)
Esther Van der Stappen (Speaker)
Smits, A. (Speaker)

Human Centered Technologies

Activity: Talk or presentation › Invited talk

Description

Discussion of how algorithmic affordances in educational recommender systems can help create responsible AI, but how they also potentially introduce new ethical problems

Period	16 Apr 2025
Event title	nwo ict.open 2025: Building digital bridges
Event type	Conference
Location	Utrecht, NetherlandsShow on map
Degree of Recognition	National

Keywords

human-ai interaction
design
algorithmic affordances
responsible AI
human-computer interaction
recommender systems
education

Research Focus Areas Hanze University of Applied Sciences * (mandatory by Hanze)

Entrepreneurship

Publinova themes

Language, Culture and Arts
ICT and Media
Health
People and Society
Technology

Documents & Links

Recommender systems presentatie - ICT OPEN - opmaak - v6
File: application/octet-stream, 14.2 MB
Type: Text

Artificial Intelligence (AI) increasingly affects the way people work, live, and interact. Over the past years, many high-level principles, and guidelines for ‘responsible’ or ‘ethical’ AI have been developed, and a lot of theoretical research on responsible AI has been done. However, this work often fails to address the challenges that arise when applying AI in practice, including the education of future AI developers. This track covers the design, development, deployment and use of responsible AI applications in practice, and the education of responsible AI practitioners. We welcome submissions that focus on the ethical, social, socio-technical and/or ecological factors of (an) AI-application(s), for example, contributions that discuss the design process for responsible AI (e.g., through co-creation), or the organizational structures and governance needed to ensure responsible application of AI. Contributions can also focus on the knowledge and abilities that need to be taught to students and professionals to prepare them for responsible AI practices. Research in all kinds of application domains is encouraged. We welcome submissions for oral presentations, posters and demos.

Algorithmic affordances for responsible recommender systemsin education

Description

Keywords

Research Focus Areas Hanze University of Applied Sciences * (mandatory by Hanze)

Publinova themes

Documents & Links

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