27 lines
4.3 KiB
Markdown
27 lines
4.3 KiB
Markdown
---
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title: "Big data ethics"
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chunk: 3/3
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source: "https://en.wikipedia.org/wiki/Big_data_ethics"
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category: "reference"
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tags: "science, encyclopedia"
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date_saved: "2026-05-05T06:58:22.926497+00:00"
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instance: "kb-cron"
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---
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=== Openness ===
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The idea of open data is centered around the argument that data should be freely available and should not have restrictions that would prohibit its use, such as copyright laws. As of 2014 many governments had begun to move towards publishing open datasets for the purpose of transparency and accountability. This movement has gained traction via "open data activists" who have called for governments to make datasets available to allow citizens to themselves extract meaning from the data and perform checks and balances themselves. King and Richards have argued that this call for transparency includes a tension between openness and secrecy.
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Activists and scholars have also argued that because this open-sourced model of data evaluation is based on voluntary participation, the availability of open datasets has a democratizing effect on a society, allowing any citizen to participate. To some, the availability of certain types of data is seen as a right and an essential part of a citizen's agency.
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Open Knowledge Foundation (OKF) lists several dataset types it argues should be provided by governments for them to be truly open. OKF has a tool called the Global Open Data Index (GODI), a crowd-sourced survey for measuring the openness of governments, based on its Open Definition. GODI aims to be a tool for providing feedback to governments about the quality of their open datasets.
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Willingness to share data varies from person to person. Preliminary studies have been conducted into the determinants of the willingness to share data. For example, some have suggested that baby boomers are less willing to share data than millennials.
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== Historical cases ==
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=== Snowden disclosures ===
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The fallout from Edward Snowden's disclosures in 2013 significantly reshaped public discourse around data collection and the privacy principle of big data ethics. The case revealed that governments controlled and possessed far more information about civilians than previously understood, violating the principle of ownership, particularly in ways that disproportionately affected disadvantaged communities. For instance, activists were frequently targeted, including members of movements such as Occupy Wall Street and Black Lives Matter. This revelation prompted governments and organizations to revisit data collection and storage practices to better protect individual privacy while also addressing national security concerns. The case also exposed widespread online surveillance of other countries and their citizens, raising important questions about data sovereignty and ownership. In response, some countries, such as Brazil and Germany, took action to push back against these practices. However, many developing nations lacked the technological independence necessary or were too generally dependent on the nations surveilling them to resist such surveillance, leaving them at a disadvantage in addressing these concerns.
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=== Cambridge Analytica scandal ===
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The Cambridge Analytica scandal highlighted significant ethical concerns in the use of big data. Data was harvested from approximately 87 million Facebook users without their explicit consent and used to display targeted political advertisements. This violated the currency principle of big data ethics, as individuals were initially unaware of how their data was being exploited. The scandal revealed how data collected for one purpose could be repurposed for entirely different uses, bypassing users' consent and emphasizing the need for explicit and informed consent in data usage. Additionally, the algorithms used for ad delivery were opaque, challenging the principles of transaction transparency and openness. In some cases, the political ads spread misinformation, often disproportionately targeting disadvantaged groups and contributing to knowledge gaps. Marginalized communities and individuals with lower digital literacy were disproportionately affected as they were less likely to recognize or act against exploitation. In contrast, users with more resources or digital literacy could better safeguard their data, exacerbating existing power imbalances.
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== Footnotes ==
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== References == |