🚀 The mirror: Confronting bias and inequality in artificial intelligence

Online course practice 6/10 from building safe intelligence systems

🚀 The mirror: Confronting bias and inequality in artificial intelligence | Online course practice 6/10 from building safe intelligence systems

The mirror: Confronting bias and inequality in artificial intelligence (online practice)

"Justice consists not in being neutral between right and wrong, but in finding out the right and upholding it, wherever found, against the wrong." - Theodore Roosevelt

AI systems are trained on data that reflects the world, including its biases and inequalities. If left unchecked, AI can amplify these biases, perpetuating discrimination and unfairness.
Decision leaders are responsible for ensuring that their AI systems are fair, equitable, and inclusive.
This requires proactive measures to identify and mitigate biases, promote diversity in data and algorithms, and prioritize ethical considerations.