Social Media Artificial Intelligence algorithms provide users with engaging and personalized content. Yet, the personalization of algorithms may have a negative impact on users who lack AI literacy. The limited understanding of SM algorithms among the population suggest that adolescents are more likely to place blind trust in the information they consume, exposing them to negative consequences (misinformation, filter bubbles and echo chambers). We therefore propose an intervention with a narrative scripts approach to raise awareness of AI algorithms in SM. To foster an authentic learning experience and question adolescents’ trust in AI, we deploy a low-accuracy AI image classifier. A quasi-experimental study was conducted among 144 high-school students in Barcelona, Spain. The results show that the narrative scripts intervention improved students’ awareness of SM algorithms and shaped more critical attitudes towards them. A comparison of students’ choices between human predictions and those produced by a low-accuracy AI classifier shows a lack of AI overdependence. Information about predictions’ source did not affect students’ trust or learning about AI. These findings contribute towards SM algorithms education and share insight into the effect of deploying low-accuracy detectors in learning technology interventions.

Theophilou, E., Lomonaco, F., Donabauer, G., Ognibene, D., Sanchez-Reina, R., Hernandez-Leo, D. (2023). AI and Narrative Scripts to Educate Adolescents About Social Media Algorithms: Insights About AI Overdependence, Trust and Awareness. In Responsive and Sustainable Educational Futures 18th European Conference on Technology Enhanced Learning, EC-TEL 2023, Aveiro, Portugal, September 4–8, 2023, Proceedings (pp.415-429). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-031-42682-7_28].

AI and Narrative Scripts to Educate Adolescents About Social Media Algorithms: Insights About AI Overdependence, Trust and Awareness

Lomonaco F.;Donabauer G.;Ognibene D.;
2023

Abstract

Social Media Artificial Intelligence algorithms provide users with engaging and personalized content. Yet, the personalization of algorithms may have a negative impact on users who lack AI literacy. The limited understanding of SM algorithms among the population suggest that adolescents are more likely to place blind trust in the information they consume, exposing them to negative consequences (misinformation, filter bubbles and echo chambers). We therefore propose an intervention with a narrative scripts approach to raise awareness of AI algorithms in SM. To foster an authentic learning experience and question adolescents’ trust in AI, we deploy a low-accuracy AI image classifier. A quasi-experimental study was conducted among 144 high-school students in Barcelona, Spain. The results show that the narrative scripts intervention improved students’ awareness of SM algorithms and shaped more critical attitudes towards them. A comparison of students’ choices between human predictions and those produced by a low-accuracy AI classifier shows a lack of AI overdependence. Information about predictions’ source did not affect students’ trust or learning about AI. These findings contribute towards SM algorithms education and share insight into the effect of deploying low-accuracy detectors in learning technology interventions.
paper
Adolescents AI trust; AI overdependence; Low-accuracy image classification; Social media algorithms education;
English
Proceedings of the 18th European Conference on Technology Enhanced Learning, ECTEL 2023 - September 4–8, 2023
2023
Viberg, O; Jivet, I; Muñoz-Merino, PJ; Perifanou, M; Papathoma, T
Responsive and Sustainable Educational Futures 18th European Conference on Technology Enhanced Learning, EC-TEL 2023, Aveiro, Portugal, September 4–8, 2023, Proceedings
9783031426810
2023
14200 LNCS
415
429
none
Theophilou, E., Lomonaco, F., Donabauer, G., Ognibene, D., Sanchez-Reina, R., Hernandez-Leo, D. (2023). AI and Narrative Scripts to Educate Adolescents About Social Media Algorithms: Insights About AI Overdependence, Trust and Awareness. In Responsive and Sustainable Educational Futures 18th European Conference on Technology Enhanced Learning, EC-TEL 2023, Aveiro, Portugal, September 4–8, 2023, Proceedings (pp.415-429). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-031-42682-7_28].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/450880
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