AI (122)

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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
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  • Immersive Technology
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  • Year
    • 1916 - 1966
    • 1968 - 2018
    • 2019 - 2069
  • Duration
  • 6 min
  • Wired
  • 2019
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The Toxic Potential of YouTube’s Feedback Loop

Spreading of harmful content through Youtube’s AI recommendation engine algorithm. AI helps create filter bubbles and echo chambers. Limited user agency to be exposed to certain content.

  • Wired
  • 2019
  • 4 min
  • VentureBeat
  • 2020
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Researchers Find that Even Fair Hiring Algorithms Can Be Biased

A study on the engine of TaskRabbit, an app which uses an algorithm to recommend the best workers for a specific task, demonstrates that even algorithms which attempt to account for fairness and parity in representation can fail to provide what they promise depending on different contexts.

  • VentureBeat
  • 2020
  • 7 min
  • CNN
  • 2021
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South Korea has used AI to bring a dead superstar’s voice back to the stage, but ethical concerns abound

The South Korean company Supertone has created a machine learning algorithm which has been able to replicate the voice of beloved singer Kim Kwang-seok, thus performing a new single in his voice even after his death. However, certain ethical questions such as who owns artwork created by AI and how to avoid fraud ought to be addressed before such technology is used more widely.

  • CNN
  • 2021
  • 7 min
  • Venture Beat
  • 2021
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Center for Applied Data Ethics suggests treating AI like a bureaucracy

As machine learning algorithms become more deeply embedded in all levels of society, including governments, it is critical for developers and users alike to consider how these algorithms may shift or concentrate power, specifically as it relates to biased data. Historical and anthropological lenses are helpful in dissecting AI in terms of how they model the world, and what perspectives might be missing from their construction and operation.

  • Venture Beat
  • 2021
  • 10 min
  • The Washington Post
  • 2021
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He predicted the dark side of the Internet 30 years ago. Why did no one listen?

The academic Philip Agre, a computer scientist by training, wrote several papers warning about the impacts of unfair AI and data barons after spending several years studying the humanities and realizing that these perspectives were missing from the field of computer science and artificial intelligence. These papers were published in the 1990s, long before the data-industrial complex and the normalization of algorithms in the everyday lives of citizens. Although he was an educated whistleblower, his predictions were ultimately ignored, the field of artificial intelligence remaining closed off from outside criticism.

  • The Washington Post
  • 2021
  • 7 min
  • Chronicle
  • 2021
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Artificial Intelligence Is a House Divided

The history of AI contains a pendulum which swings back and forth between two approaches to artificial intelligence; symbolic AI, which tries to replicate human reasoning, and neural networks/deep learning, which try to replicate the human brain.

  • Chronicle
  • 2021
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