Culture / Data / Machine Learning

Threads and Threats When Computers Think and Biases Emerge

21 Nov 2019 5:30pm, by

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The threads and threats that come with computer intelligence were apparent to Pamela McCorduck in 1960 as a graduate student in English Literature. Those same threads and threats are apparent today in the biases that can come with black box algorithms and indirect biases that Lauren Maffeo studies in her work as an analyst for GetApp, a software reviews site under Gartner Research that uses proprietary data to help match software buyers with the best tools for their businesses.

In these two episodes of The New Stack Makers, McCorduck and Maffeo each provide their perspectives on artificial intelligence, its power and the threats it poses when unchecked.

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Today, McCorduck is an AI expert and author of Machines Who Think, which helped inform a generation of artificial intelligence researchers, and the newly released memoir, This Could Be Important: My Life and Times with the Artificial Intelligentsia.

In part one of this episode of The New Stack Makers, McCorduck discussed:

  • The early pioneers of AI and what proved to be a turning point for her views about intelligence when a Russian technologist came to visit at Stanford University where she was teaching.
  • The philosophical perspective about the concepts of intelligence and how researchers viewed their work.
  • How the views of the early 1960s still influence her perspectives.
  • The way AI was developed and why now we are seeing shortcomings in face recognition and other AI-influenced technologies.
  • The recklessness of unchecked development in the field. Who is speaking out against the rush to use personal data in AI?
  • The artificial intelligentsia.

In part two, Maffeo discussed:

  • How the top performing companies in the financial markets are using technologies based upon artificial intelligence. These technologies are powerful but can at times prove to pose indirect biases. That can lead to a bank loan getting denied, a passport not issued, a payment getting stopped and a black person getting a longer prison sentence due to the color of their skin.
  • These black-box algorithms can’t be stopped unless the algorithm is scrapped. But if they are used in commercial products, then they pose a commercial loss if taken down. It is leading to an issue of ethical debt, similar to technical debt.
  • The top five big technology companies all use open source but it is uncertain how much they also use black-box algorithms.
  • Documenting algorithms is still a new field, providing a way to address the methods of fairness used.
  • Tensorflow and Drupal are examples of open AI technologies.

Feature image via Pixabay.

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