CS103F: Ethical Foundations of Computer Science

Before beginning this blog post, please watch Ethical Fading and Incrementalism from Ethics Unwrapped.

For this blog post, we would like you to consider the how technology, algorithms, and algorithmic bias is affecting policing and banking in our society. Please also consider proposed solutions that eliminate or reduce algorithmic bias.

Consider:

• What is the place of AI in our society?
• When do its advantages outweigh its disadvantages? and vice versa?
• Do the proposed solutions solve the problem or help solve the problem? Why or why not?
• As computer scientists, what is our ethical responsibility in this situation? Is it different if we are working in AI or an AI-related area of not? Why or why not?
• As we bulid this technology, how susceptible are we to ethical fading and incrementalism?

In considering these questions, you may consider a specific example from the news or suggested sources, or you may consider these ideas more generally.

These resources may be helpful to you:

• Algorithmic Bias.
  • Fussell, Sidney. AI Professor Details Real-World Dangers of Algorithm Bias. Gizmodo, December 8, 2017.
  • Pierson, Emma. Hey, Computer Scientists! Stop Hating on the Humanities. Wired, April 24, 2017.
  • Spielkamp, Matthais. Inspecting Algorithms for Bias MIT Technology Review, June 12, 2017.
  • Biesinger, Raymond. Is your software racist? Politico, February 7, 2018.
• Policing.
  • Winston, Ali. Palantir has secretly been using New Orleans to test its predictive policing technology, The Verge, February 27, 2018.
  • Angwin, Julia, Jeff Larson, Surya Mattu, and Lauren Kirchner. Machine Bias, ProPublica, May 23, 2016.
  • Koren, James. Some Lenders Are Judging You On Much More Than Finances, Los Angeles Times, December 19, 2015.
• Banking.
  • Petrasic, Kevin, Benjamin Saul, James Greig, Matthew Bornfreund. Algorithms and bias: What lenders need to know, White & Case, January, 20, 2017.
  • Crosman, Penny. Is it OK for lending algorithms to favor Ivy League schools?, American Banker, March 9, 2017.

• Proposed solutions.
  • Sharma, Kriti. Can We Kepp Our Biases from Creeping into AI?, Harvard Business Review, February 9, 2018.
  • Robitzski, Dan. Microsoft Is Making a Tool a Track Down Biased AI, But That's Just Half the Problem. Science Alert, May 26, 2018.
  • Johnson, Khari. MIT Resarchers Show How To Detect and Address AI Bias Without Loss in Accuracy. Venture Beat, Noember 16, 2018.