AI Ethics and Bias: Building Responsible AI Systems
Understanding AI Ethics As AI systems become more prevalent, understanding their ethical implications is crucial. Common Bias Sources Training Data Bias Algorithm Bias Interaction Bias Confirmation Bias Example: Bias in Data # Example of potential bias in data preprocessing import pandas as pd def preprocess_data(df): # Removing certain demographics might introduce bias df = df[df['age'] > 18] # Income thresholds might affect different groups differently df = df[df['income'] > 50000] return df # Better approach: Consider impact on different groups def fair_preprocess(df): # Analyze impact across demographics demographics = df.groupby('demographic_group').agg({ 'age': 'mean', 'income': 'mean' }) # Adjust thresholds based on group characteristics return df Ethical Guidelines Transparency ...