Data Mining (28)

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Find narratives by ethical themes or by technologies.

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Themes
  • Privacy
  • Accountability
  • Transparency and Explainability
  • Human Control of Technology
  • Professional Responsibility
  • Promotion of Human Values
  • Fairness and Non-discrimination
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Technologies
  • AI
  • Big Data
  • Bioinformatics
  • Blockchain
  • Immersive Technology
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  • Year
    • 1916 - 1966
    • 1968 - 2018
    • 2019 - 2069
  • Duration
  • 7 min
  • Wired
  • 2019
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It’s Time to Switch to a Privacy Browser

Internet users should start considering private browsers such as Duckduckgo to promote privacy and prevent personalized search results and ads. Many different pieces of software, including browsers by larger tech companies, are beginning to take this approach of erasing data, blocking outside tracking, or preventing cookies.

  • Wired
  • 2019
  • 10 min
  • The New Yorker
  • 2019
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The Hidden Costs of Automated Thinking

Great breakdown of the concerns that come with automating the world without understanding why it works. Provides the principal concerns with the “hidden layer” of artificial neural networks, and how the lack of human understanding of some AI decision making makes these machines susceptible to manipulation.

  • The New Yorker
  • 2019
  • 30 min
  • Wired
  • 2019
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Inside China’s Vast New Experiment In Social Ranking

In China, “supercompanies” such as WeChat or Alipay aggregate massive amounts of varied data on users. The Zhima Credit score system directly influences the agency of users by limiting their options in acting in their environment, or determining with whom they interact. The Chinese government interests itself with allying with large tech companies to incorporate a social ranking system which can be used to control and suppress citizens. Although the United States does not have “supercompanies” like those mentioned from China, the large companies that collect user data in the US certainly have the same potential to limit human agency.

  • Wired
  • 2019
  • 10 min
  • MIT Technology Review
  • 2020
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We read the paper that forced Timnit Gebru out of Google. Here’s what it says.

This article explains the ethical warnings of Timnit Gebru against training Natural Language Processing algorithms on large language models developed on sets of textual data from the internet. Not only does this process have a negative environmental impact, it also still does not allow these machine learning tools to process semantic nuance, especially as it relates to burgeoning social movements or countries with lower internet access. Dr. Gebru’s refusal to retract this paper ultimately lead to her dismissal from Google.

  • MIT Technology Review
  • 2020