Covers: application of Bias in facial recognition algorithms
0Questions this item addresses:
- How can facial racial technologies lead to actual harm?
How to use this item?
This New York Times article presents the real-life case of a faulty facial recognition match that led to a Michigan man’s arrest for a crime he did not commit
Author(s) / creator(s) / reference(s)
Kashmir Hill
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Bias in Facial Recognition Algorithms
Contributors
- 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.
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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