Data activism
Data activism is a social practice that uses technology and data. It emerged from existing activism sub-cultures such as hacker an open-source movements.
Data activism can be the act of providing data on events or issues that individuals feel have not been properly addressed by those in power. For example, the first deployment of the Ushahidi platform in 2008 in Kenya visualized the post-electoral violence that had been silenced by the government and the new media.[2] The social practice of data activism revolves around the idea that data is political in nature.[7] Data activism allows individuals to quantify a specific issue.[6] By collecting data for a particular purpose, it allows data activists to quantify and expose specific issues. As data infrastructures and data analytics grow, data activists can use evidence from data-driven science to support claims about social issues.[8][2]
Types
A twofold classification of data activism has been proposed by Stefania Milan and Miren Gutiérrez,[9] later explored more in-depth by Milan[6] according to the type of activists' engagement with data politics. 'Re-active data activism' can be characterized as motivated by the perception of massive data collection as a threat, for instance when activists seek to resist corporate and government snooping, whereas 'pro-active data activism' sees the increasing availability of data as an opportunity to foster social change.[6] These differentiated approaches to datafication result in different repertoires of action, which are not at odds with each other, since they share a crucial feature: they take information as a constitutive force capable of shaping social reality[10] and contribute to generate new alternative ways of interpreting it.[11] Examples of re-active data activism include the development and usage of encryption and anonymity networks to resist corporate or state surveillance, while instances of pro-active data activism include projects in which data is mobilized to advocate for change and contest established social narrative.[9]
Examples
End the Backlog
It was discovered that in the United States between 180,000 and 500,000
DataKind
DataKind is a digital activism organization that brings together data scientists and people from other organizations and governments for the purpose of using big data in similar ways that corporations currently use big data namely to monetize data. However, here big data is used to help solve social problems, like food shortages and homelessness. DataKind was founded in 2011 and today there are chapters in the United Kingdom, India, Singapore and the United States of America.[15] Jake Porway is the founder and executive director of DataKind.[16]
Criticism
While data activists may have good intentions, one criticism is that by allowing citizens to generate data without training or reliable forms of measurement, the data can be skewed or presented in different forms.[17]
Safecast
After the
See also
References
- ^ a b "about – DATACTIVE". Archived from the original on 2022-06-02. Retrieved 2020-01-20.
- ISBN 978-1-5013-0650-1.
- ^ "Citizens' Media Meets big data: the Emergence of Data Activism". Archived from the original on 7 January 2017. Retrieved 6 January 2017.
- S2CID 40297692.
- ^ from the original on 9 October 2022. Retrieved 7 November 2016.
- ISBN 978-1-4462-8747-7.
- ISBN 978-1-4462-8747-7.
- ^ .
- OCLC 83980106.
- S2CID 152166960.
- ^ a b Prevost O'Connor, Katherine L. (2003). "Eliminating the Rape-Kit Backlog: Bringing Necessary Changes to the Criminal Justice System". UMKC Law Review. 72: 193–214. Archived from the original on 2016-12-20. Retrieved 2016-12-01.
- ^ Prevost O'Connor, Katherine L. (2003). "Eliminating the Rape-Kit Backlog: Bringing Necessary Changes to the Criminal Justice System". UMKC Law Review. 72: 196. Archived from the original on 2016-12-20. Retrieved 2016-12-01.
- ProQuest 1711123150.
- ^ "DataKind | About Us". www.datakind.org. Archived from the original on 2020-02-04. Retrieved 2020-01-20.
- ^ "DataKind | Our Team". www.datakind.org. Archived from the original on 2020-02-04. Retrieved 2020-01-20.
- ^ Abe, Yasuhito (2014). "Safecast or the Production of Collective Intelligence on Radiation Risks after 3.11" (PDF). The Asia-Pacific Journal. 12 (7): 5. Archived (PDF) from the original on 2016-12-01. Retrieved 2016-11-07.
- ^ Abe, Yasuhito (February 2014). "Safecast or the Production of Collective Intelligence on Radiation Risks after 3.11" (PDF). The Asia-Pacific Journal. 12 (7): 1–10. Archived (PDF) from the original on 1 December 2016. Retrieved 7 November 2016.
- ^ Abe, Yasuhito (2014). "Safecast or the Production of Collective Intelligence on Radiation Risks after 3.11" (PDF). The Asia-Pacific Journal. 12 (7): 5. Archived (PDF) from the original on 2016-12-01. Retrieved 2016-11-07.
- ^ Abe, Yasuhito (2014). "Safecast or the Production of Collective Intelligence on Radiation Risks after 3.11" (PDF). The Asia-Pacific Journal. 12 (7): 5. Archived (PDF) from the original on 2016-12-01. Retrieved 2016-11-07.