Ethical Machine Learning - Kehsa Williams - NDC Porto 2023

Ai

Discover the critical role of ethics in machine learning, including bias detection, transparency, and explainability, with a focus on human oversight, AI system performance, and societal implications.

Key takeaways
  • Importance of ethical considerations in machine learning
  • Data preprocessing and bias detection during the data prep stage
  • Explainability and transparency in AI decision-making
  • Need for human oversight and feedback in AI systems
  • Impact of AI on people and society, such as biased decision-making and lack of explainability
  • Importance of understanding and addressing bias in AI systems
  • Use of tools like Data Wrangler and SageMaker Clarify to detect and mitigate bias
  • Example of AI system used in police work, highlighting potential for bias and lack of transparency
  • Need for regular monitoring and reporting of AI system performance and results
  • Importance of considering moral and ethical implications of AI systems
  • Example of biased decision-making in hiring, advertising, and lending
  • Need for transparency and explainability in AI decision-making
  • Importance of considering both ethical and technical aspects of AI development
  • Use of AI to identify breast cancer early, but also potential misuse and biased decision-making
  • Need for continuous learning and improvement in AI development