As AI takes life-and-death decisions, we must ask: Is the algorithm fair? This article explores the dark side of medical AI.

The Bias Problem

If an AI is trained mostly on data from white males, it may fail to diagnose conditions in women or minorities.

Ethical Challenges

  • Algorithmic Bias: Ensuring diverse training datasets.
  • Data Privacy: protecting patient genomic data.
  • Accountability: Who is sued if the AI makes a mistake? Doctor or Developer?
"AI must be transparent. A 'black box' that saves a life is good; one that explains WHY is better." – Treneywann Ethics Panel