Professional Responsibility (52)

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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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  • Media Type
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  • Year
    • 1916 - 1966
    • 1968 - 2018
    • 2019 - 2069
  • Duration
  • 2 min
  • Kinolab
  • 2019
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Technological Superhighways and Monopolistic Control

In an imagined future of London, citizens all across the globe are connected to the Feed, a device and network accessed constantly through a brain-computer interface. In this clip, Meredith must seek help from the leader of a developing country without the Feed network, because the Feed has become hacked and is bringing down infrastructure with it.

  • Kinolab
  • 2019
  • 6 min
  • Kinolab
  • 2019
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Resisting Realities and Robotic Murder

Eleanor Shellstrop runs a fake afterlife, in which she conducts an experiment to prove that humans with low ethical sensibility can improve themselves. One of the subjects, Simone, is in deep denial upon arriving in this afterlife, and does as she pleases after convincing herself that nothing is real. Elsewhere, another conductor of the experiment, Jason, kills a robot which has been taunting him since the advent of the experiment.

  • Kinolab
  • 2019
  • 7 min
  • The Verge
  • 2019
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AI ‘Emotion Recognition’ Can’t Be Trusted

Reliance on “emotion recognition” algorithms, which use facial analysis to infer feelings. Credibility of the results in question based on inability of machines to recognize abstract nuances.

  • The Verge
  • 2019
  • 20 min
  • UC Research Repository
  • 2018
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Robots and Racism

This 2018 study uses several experiments to demonstrate how human racial bias is imposed upon robots as well, specifically in that racialised black robots are more likely to be perceived as threatening to the group sampled.

  • UC Research Repository
  • 2018
  • 5 min
  • MIT Technology Review
  • 2019
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This is how AI bias really happens—and why it’s so hard to fix

Introduction to how bias is introduced in algorithms during the data preparation stage, which involves selecting which attributes you want the algorithm to consider. Underlines the difficult nature of ameliorating bias in machine learning, given that algorithms are not always perfectly attuned to human social contexts.

  • MIT Technology Review
  • 2019
  • 7 min
  • Mad Scientist Laboratory
  • 2018
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Man Machine Rules

The combination of the profit motive for tech companies and the vague language of non-binding ehtical agreements for coders means that there must be a higher regulation for ethical deployment and use of technology. Argues that there must be clear demarcations between what is considered real and human versus fake and virtual. Digital technologies should be regulated in a manner similar to other technologies, such as guns, cars, or nuclear weapons.

  • Mad Scientist Laboratory
  • 2018
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