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HomeHomework Helpcomputer-scienceAlgorithmic Bias

Algorithmic Bias

The instances where automated systems contribute to unjustified different treatment or impacts disfavoring people based on their actual or perceived characteristics, such as race, gender, or age, and the measures to prevent and address such biases in AI systems

intermediate
3 hours
Computer Science
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Overview

Algorithmic bias is a critical issue in today's technology-driven world, where algorithms influence many aspects of our lives, from hiring to law enforcement. Understanding how bias can seep into algorithms through flawed data is essential for creating fair and equitable systems. By recognizing the ...

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Key Terms

Algorithm
A set of rules or instructions for solving a problem or completing a task.

Example: Sorting a list of names alphabetically.

Bias
A tendency to favor one group over another, often leading to unfair treatment.

Example: Favoring candidates from a specific demographic in hiring.

Discrimination
Unjust treatment of different categories of people, often based on race, age, or gender.

Example: Denying loans based on race.

Machine Learning
A subset of artificial intelligence that enables systems to learn from data and improve over time.

Example: Spam filters that learn to identify unwanted emails.

Fairness
The quality of being free from bias, favoritism, or injustice.

Example: Ensuring equal opportunity in job applications.

Data Curation
The process of organizing and maintaining data to ensure its quality and usability.

Example: Cleaning and validating data before analysis.

Related Topics

Data Ethics
The study of moral issues related to data collection and usage.
intermediate
Artificial Intelligence
The simulation of human intelligence processes by machines.
advanced
Machine Learning Fairness
Exploring fairness in machine learning models and their applications.
intermediate

Key Concepts

Bias in DataDiscriminationMachine LearningFairness