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Privacy is not Binary: A discussion of data systems, ethics, and human rights
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Marks
Author(s):
Elizabeth Alpert, Amelia Radke
Location
Room 6
Date
jan Wed 15
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Start
14:25
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Duration
0:45:0
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None
End
15:10
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None min.
https://lca2020.linux.org.au/schedule/presentation/48/
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Privacy_is_not_Binary_A_discussion_of_data_systems_ethics_and_human_rights.json
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Description:
In an increasingly digitised world, societal understandings of the intersection between innovative technologies, ethics, and human rights have never been more critical. However, different cultures and different sectors have differing understandings of all these things. A simple categorisation of human data as being either public or private is insufficient to describe the complexities of a single human social group, let alone the full complexity of human life and interaction that is being recorded in more and more detail every day. In Australia, understanding the social impacts of this new regime of digital data is integral to facilitating economic, social and health benefits, without further entrenching inequality for already vulnerable peoples within society. Furthermore, the application and impact of innovative technologies from all sectors including the tech industry is highly dependent on social acceptance, which cannot avoid public debates around ethics, human rights, and responsible innovation. There are currently many conversations about the usage of human data and issues of privacy, ethics, and digital human rights in government, academia, activist communities, technology in general, and the information security and open data communities in particular. Unfortunately, most of these conversations are happening independently of each other, and as such are missing out on the knowledge, experience, and perspectives of other sectors. This presentation is a discussion between an anthropologist (Dr Amelia Radke) specialising in digital human rights and a data infrastructure engineer (Betsy Alpert) on how the notions of privacy, security, and ethics play out in our respective fields. We argue that good data needs collaboration and deliberate design, particularly in an our ever more data-centric world.
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