Algorithmic Bias in Real-world

  1. Predictive Policing:
  • Predicting criminality
  • Predicting Homosexuality
  • Webcams cant recognize people of color: Face tracking systems are also used by companies like Nikon and HP for better adjustment of frames for their users. HP uses this adjustment of the lens focusing on the user's face as one moves, for better video calling and other similar features. Whereas Nikon uses face recognition for skillful capturing of the picture, which has lately found to be having trouble with Asian Faces. Cases have been found where the system was not able to identify people of color. Read More
  • Amazon’s facial recognition system works great much of the time, but when asked to compare the faces of all 535 members of Congress with 25,000 public arrest photos, it found 28 matches, when in reality there were none. A computer program designed to vet job applicants for Amazon was discovered to systematically discriminate against women.
Source: @
  • Microsoft, IBM, and Face++ have now improved this error in detection to 2%**. The main concern here is if companies start using such systems that show bias on human faces, it becomes a matter of concern.
Source: Link


  1. These AI systems have repeatedly shown that they work better with some demographic groups than others. These biases then perpetuate (also known as “bias laundering”) and then lead to consequences that keep on worsening the situation.
  2. Unchecked, Unregulated AI can amplify the bias. Hence the awareness of bias and accountability in AI needs to be developed for preventing the unfavorable use of AI systems.
  3. One must understand why and how decisions are being made by the AI algorithm in order to identify the biases.

Good Read on the Topic:

  2. How to Make a racist AI without really trying





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