Understanding AI Ethics

AI Ethics

• AI ethics refers to a system of moral principles and techniques guiding the development and responsible use of artificial intelligence technology.
• Organizations are developing AI codes of ethics as AI becomes integral to products and services.

Bias in AI

• Selection bias in datasets used to develop AI algorithms is common, leading to diminished accuracy in certain populations.
• Buolamwini and Gebru demonstrated bias in automated facial recognition, particularly in recognizing darker-skinned faces, especially women.

Data Ownership

• Machine learning is data-hungry, and deep learning applications require hundreds of thousands of cases for development and testing.
• The demand for patient-derived data in medicine has created a marketplace, but ownership and rights to use these data are complex and vary by jurisdiction.

Addressing Concerns

• Recent collaboration between scientific groups and the National Institutes of Health has identified key research priorities to address concerns, including:
  • Developing image reconstruction and automated image annotation methods to limit human bias.
  • Creating explainable AI to penetrate the "black box" of machine learning algorithms.
  • Developing safe and validated methods to de-identify patient data for large-scale use.

AI in Healthcare

• AI has the potential to revolutionize the healthcare sector by leveraging advanced algorithms and machine learning techniques for data analysis, clinical decision-making, and personalized treatment options.