Technological artifacts represent the historical-cultural products able to mediate our relationship with a world in continuous and rapid transformation (Vygotsky, 2008). They, therefore, act as intermediaries with the environment around us and especially with the Other (Irigaray, 2017; Hall, 2015) with which we are in "connection". Therefore, while technology is affected by the cultural influences of those who produce it, it also directly affects the process of individuation of subjects, social organization and politics, re-proposing and amplifying power relations. In a digitalized capitalist universe, where the dominant paradigms of reference are still white, cisgender, and able-bodied men (Bocci, 2019; Parker, 2020; Apple, 2020), the proposal is to adopt an intersectional approach - one that simultaneously takes into account variables of gender, race, class, sexuality, and ability (Davis, 2018; James, 2012) - to reread the bias of cultural choices and responses provided by algorithms (Zona & De Castro, 2020; Finn, 2018; Zona & Bocci, 2018; Cardon, 2016; O'Neil, 2017; Bogost, 2015). The hypothesis of our research, then, is that the Web and new digital technologies are not neutral, but that they convey sexist, racist, and ableist stereotypes (Noble et al., 2016; Noble, 2018; Buolamwini and Gebru, 2018; UNESCO, 2019). As the boundaries between formal and informal education become increasingly blurred in technological societies, the risk is that these stereotypes will have cultural and social implications on the lives and worldviews of Net "surfers." The non- probabilistic sample chosen is made up of teachers of pre-school, primary and secondary schools involved in traineeship and students of the Degree Course (CdL) in Primary Education Sciences (SFP) at Roma Tre University who participated in the Laboratory of Didattica Inclusiva in the A.Y. 2020/2021. The choice to conduct the research with a sample of teachers and future teachers is motivated by the fact that their culture and beliefs, derived at least in part from the media content they prefer and enjoy, could have direct effects on the students with whom they are/will be interacting in formal educational contexts. Accordingly, the aims that guided the research were: to map teachers' and future teachers' stereotypes and biases toward the variables of gender, race, sexual orientation, and ability/disability and to detect their trust in mass media; to analyze algorithms as cultural constructs; and to track and build a database of sexist, racist, and ableist stereotypes conveyed in Google Image searches. The experimentation was carried out by submitting an Intersectional Questionnaire (IQ) consisting of 62 questions (10 on the sex/gender variable, 12 on race, 11 on sexual orientation, 10 on ability/disability, 10 on the pandemic crisis and its possibility of modifying or maintaining traditional social hierarchies and 9 on the media) aimed at recording the thoughts and opinions of the 134 teachers involved (94.8% women and 5.2% men; average age 48.1 years; 37.2% preschool; 41.8% primary; 21% secondary). Subsequently, the 50 students of the CdL in SFP involved answered the questions of the same IQ proposed to the teachers. In order to obtain a detailed "cultural snapshot" of the group, they were also given a Questionnaire on Cultural Consume (QCC) consisting of 41 questions and aimed at highlighting their preferences in music, literature, cinema, TV series, youtubers, vloggers/bloggers and influencers.

DE CASTRO, M., Zona, U., Bocci, F. (2021). Digital Artifacts as Cultural Machines: for an Intersectional Critical Analysis of the Relationship between Power and Technology,. In ATEE Spring Conference 2020-2021. Book of Abstracts (pp.36-39). Firenze : Firenze University Press.

Digital Artifacts as Cultural Machines: for an Intersectional Critical Analysis of the Relationship between Power and Technology,

DE CASTRO Martina;Zona Umberto;BOcci Fabio
2021

Abstract

Technological artifacts represent the historical-cultural products able to mediate our relationship with a world in continuous and rapid transformation (Vygotsky, 2008). They, therefore, act as intermediaries with the environment around us and especially with the Other (Irigaray, 2017; Hall, 2015) with which we are in "connection". Therefore, while technology is affected by the cultural influences of those who produce it, it also directly affects the process of individuation of subjects, social organization and politics, re-proposing and amplifying power relations. In a digitalized capitalist universe, where the dominant paradigms of reference are still white, cisgender, and able-bodied men (Bocci, 2019; Parker, 2020; Apple, 2020), the proposal is to adopt an intersectional approach - one that simultaneously takes into account variables of gender, race, class, sexuality, and ability (Davis, 2018; James, 2012) - to reread the bias of cultural choices and responses provided by algorithms (Zona & De Castro, 2020; Finn, 2018; Zona & Bocci, 2018; Cardon, 2016; O'Neil, 2017; Bogost, 2015). The hypothesis of our research, then, is that the Web and new digital technologies are not neutral, but that they convey sexist, racist, and ableist stereotypes (Noble et al., 2016; Noble, 2018; Buolamwini and Gebru, 2018; UNESCO, 2019). As the boundaries between formal and informal education become increasingly blurred in technological societies, the risk is that these stereotypes will have cultural and social implications on the lives and worldviews of Net "surfers." The non- probabilistic sample chosen is made up of teachers of pre-school, primary and secondary schools involved in traineeship and students of the Degree Course (CdL) in Primary Education Sciences (SFP) at Roma Tre University who participated in the Laboratory of Didattica Inclusiva in the A.Y. 2020/2021. The choice to conduct the research with a sample of teachers and future teachers is motivated by the fact that their culture and beliefs, derived at least in part from the media content they prefer and enjoy, could have direct effects on the students with whom they are/will be interacting in formal educational contexts. Accordingly, the aims that guided the research were: to map teachers' and future teachers' stereotypes and biases toward the variables of gender, race, sexual orientation, and ability/disability and to detect their trust in mass media; to analyze algorithms as cultural constructs; and to track and build a database of sexist, racist, and ableist stereotypes conveyed in Google Image searches. The experimentation was carried out by submitting an Intersectional Questionnaire (IQ) consisting of 62 questions (10 on the sex/gender variable, 12 on race, 11 on sexual orientation, 10 on ability/disability, 10 on the pandemic crisis and its possibility of modifying or maintaining traditional social hierarchies and 9 on the media) aimed at recording the thoughts and opinions of the 134 teachers involved (94.8% women and 5.2% men; average age 48.1 years; 37.2% preschool; 41.8% primary; 21% secondary). Subsequently, the 50 students of the CdL in SFP involved answered the questions of the same IQ proposed to the teachers. In order to obtain a detailed "cultural snapshot" of the group, they were also given a Questionnaire on Cultural Consume (QCC) consisting of 41 questions and aimed at highlighting their preferences in music, literature, cinema, TV series, youtubers, vloggers/bloggers and influencers.
978-88-5518-412-0
DE CASTRO, M., Zona, U., Bocci, F. (2021). Digital Artifacts as Cultural Machines: for an Intersectional Critical Analysis of the Relationship between Power and Technology,. In ATEE Spring Conference 2020-2021. Book of Abstracts (pp.36-39). Firenze : Firenze University Press.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11590/393350
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