Algorithmic Bias in AI and Machine Learning

Data collection practices that feed into AI and machine learning models can perpetuate gender stereotypes through algorithmic bias. When datasets are not diverse or are heavily skewed towards traditional gender norms, AI systems learn and replicate these biases, affecting decision-making from job applicant screening to personalized online advertising.

Data collection practices that feed into AI and machine learning models can perpetuate gender stereotypes through algorithmic bias. When datasets are not diverse or are heavily skewed towards traditional gender norms, AI systems learn and replicate these biases, affecting decision-making from job applicant screening to personalized online advertising.

Empowered by Artificial Intelligence and the women in tech community.
Like this article?

Data Privacy and Ethics

Interested in sharing your knowledge ?

Learn more about how to contribute.

More articles on Data Privacy and Ethics

See all

More articles from related categories

Can Ethical Tech Design Bridge the Gender Gap in STEM Fields?
Ethical Tech Design Principles
What Steps Should Be Taken to Incorporate More Women’s Voices in the Ethical Discussions Around Emerging Technologies?
Ethics in Software Development
How Are Gender Stereotypes Perpetuated Through Data Collection Practices?
Data Privacy and Ethics
What Role Do Women in Tech Play in Promoting Digital Privacy?
Ethical Decision Making in Tech