Artificial Intelligence: Sociological Approaches
Artificial Intelligence: Sociological Approaches
Wednesday, 9 July 2025: 11:00-12:45
Location: FSE025 (Faculty of Education Sciences (FSE))
RC26 Sociotechnics, Sociological Practice (host committee) Language: English
Artificial Intelligence (AI) is a tool for coping with several criticalities of the contemporary world: increase of work productivity, improvement of global health and food security, social and environmental sustainability etc.
On the other side, Ai is related to several risks, that it is important to keep into consideration. AI might cause loss of jobs, especially among the so called white-collars: as a matter of fact, lawyers, journalists, authors etc. perform functions that now several and largely spread software can apparently perform better.
Furthermore, AI entails several risks for privacy, due to massive data collection activities, the risk of privacy violation and lack of transparency. This might also undermine the necessary trust in the expert systems, such as health or legal systems.
Thirdly, social and cultural hurdles can delay or even prevent the provision of effective AI services: staff’s lack of adequate preparation, perpetuation of inequalities (sex, gender, ethnicity etc.), lack of transparency and trust in the algorithms writing.
This panel includes contributions that highlight, the role of sociology in undertesting AI-related social phenomena and show how crucial this role is: namely, being AI governance essential to ensure a full deployment of the good sides and mitigate the criticalities, contributions are welcome, that focus on AI policy making.
On the other side, Ai is related to several risks, that it is important to keep into consideration. AI might cause loss of jobs, especially among the so called white-collars: as a matter of fact, lawyers, journalists, authors etc. perform functions that now several and largely spread software can apparently perform better.
Furthermore, AI entails several risks for privacy, due to massive data collection activities, the risk of privacy violation and lack of transparency. This might also undermine the necessary trust in the expert systems, such as health or legal systems.
Thirdly, social and cultural hurdles can delay or even prevent the provision of effective AI services: staff’s lack of adequate preparation, perpetuation of inequalities (sex, gender, ethnicity etc.), lack of transparency and trust in the algorithms writing.
This panel includes contributions that highlight, the role of sociology in undertesting AI-related social phenomena and show how crucial this role is: namely, being AI governance essential to ensure a full deployment of the good sides and mitigate the criticalities, contributions are welcome, that focus on AI policy making.
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Oral Presentations