Abstract
What are the new questions raised by AI for the prevention and detection of crime? How can we rationalise the Amazon Ring doorbell and Tesla’s Sentry Mode? How can algoracism be identified, and what should we think of data donation?
Surveillance today cannot be understood without an awareness of how AI and algorithms have become increasingly central in the governance of security. They have led to a substantial expansion in the depth and breadth of surveillance, ranging from mass data collection to mass invasion of privacy. In Making Surveillance Public, Marc Schuilenburg explores the deployment of AI applications, asking who is using them, what their aims are, what outcomes and societal impacts they lead to, and against whom they are used. To this end, he makes a case for a digital criminology centred on sociological questions of power, knowledge and AI-experiences.
Surveillance today cannot be understood without an awareness of how AI and algorithms have become increasingly central in the governance of security. They have led to a substantial expansion in the depth and breadth of surveillance, ranging from mass data collection to mass invasion of privacy. In Making Surveillance Public, Marc Schuilenburg explores the deployment of AI applications, asking who is using them, what their aims are, what outcomes and societal impacts they lead to, and against whom they are used. To this end, he makes a case for a digital criminology centred on sociological questions of power, knowledge and AI-experiences.
| Original language | English |
|---|---|
| Place of Publication | The Hague |
| Number of pages | 196 |
| ISBN (Electronic) | 978-94-0011-392-3 |
| Publication status | Published - 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 16 Peace, Justice and Strong Institutions
Research programs
- SAI 2005-04 MSS
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