Covers: theory of Facial recognition technologies
Estimated time needed to finish: 20 minutes
Questions this item addresses:
  • What are facial recognition technologies?
  • How and where are facial recognition technologies used?
  • How does a machine recognize an individual face?
  • How accurate are facial recognition technologies?
How to use this item?

Read this short guide to understand the basics of how facial recognition technologies work

Author(s) / creator(s) / reference(s)
Joy Buolamwini, Vicente Ordóñez, Jamie Morgenstern, Erik Learned-Miller
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Bias In Facial Recognition Algorithms

Contributors
Total time needed: ~2 hours
Objectives
To understand the social biases embedded in facial recognition technologies: why they arise, how they affect people, and what can be done to address them
Potential Use Cases
Facial recognition / processing technologies, image classification algorithms more broadly
Who is This For ?
BEGINNER
Click on each of the following annotated items to see details.
Resources5/6
ARTICLE 1. The Myth of the Impartial Machine
  • What do we mean when we say that algorithmic systems "biased"?
  • Where does the bias in algorithmic systems come from?
15 minutes
ARTICLE 2. Facial Recognition Technologies: A Primer
  • What are facial recognition technologies?
  • How and where are facial recognition technologies used?
  • How does a machine recognize an individual face?
  • How accurate are facial recognition technologies?
20 minutes
VIDEO 3. Joy Buolamwini: "How I'm fighting bias in algorithms"
  • What does bias in facial recognition algorithms look like?
  • What can we do about bias in facial recognition algorithms?
8 minutes
PAPER 4. Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification
  • How do we know that facial recognition algorithms can discriminate on the basis of race and gender?
30 minutes
PAPER 5. Saving Face: Investigating the Ethical Concerns of Facial Recognition Auditing
  • Can we audit facial recognition algorithms for bias?
20 minutes
ARTICLE 6. "Wrongfully Accused by an Algorithm"
  • How can facial racial technologies lead to actual harm?
10 minutes

Concepts Covered

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