Lack of Transparency

AI systems often operate as "black boxes," where the decision-making process is opaque. This lack of transparency makes it difficult to assess fairness and identify biases. Overcoming this challenge requires the development of explainable AI (XAI) techniques that make the workings of AI models understandable to humans, facilitating scrutiny and accountability.

AI systems often operate as "black boxes," where the decision-making process is opaque. This lack of transparency makes it difficult to assess fairness and identify biases. Overcoming this challenge requires the development of explainable AI (XAI) techniques that make the workings of AI models understandable to humans, facilitating scrutiny and accountability.

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

Fairness in AI Algorithms

Interested in sharing your knowledge ?

Learn more about how to contribute.

More articles on Fairness in AI Algorithms

See all

More articles from related categories

AI Bias: What Role Should Community Networks Play in Its Awareness?
Community Awareness of AI Bias
Is It Possible to Create a Bias-Free AI? Insights from Women Leaders in Technology
Detecting and Mitigating AI Bias
What Are the Unseen Challenges of AI Bias for Women Pursuing Careers in Tech?
Detecting and Mitigating AI Bias
How Can AI Empower Women in Developing Countries?
AI for Social Good