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Bias in AI

Video Module 6: AI, ETHICS & RESPONSIBLE USE

Bias in AIDiagram: Bias in Machine Learning

Bias in AI means an AI system gives unfair or unequal results for some people or groups because of the data or design behind it. AI does not “hate” or “prefer” anyone by itself but it learns from human data, and if that data is unbalanced or unfair, the AI also becomes unfair.

Where Bias Can Appear

  • AI bias can show up in:
    • Hiring systems
    • Loan approval tools
    • Face recognition
    • College admissions screening
    • Medical diagnosis tools
    • Chatbots and language systems

Why Does AI Bias Happen?

  1. Biased Training Data:- If the dataset is not diverse, results will not be fair.
  2. Human Bias in Design:- Developers may unknowingly build assumptions into systems.
  3. Missing Data:- Some groups may be under-represented.
  4. Feedback Loops:- Wrong predictions get repeated and reinforced.

Risks of Biased AI

  • Unfair decisions
  • Social inequality increases
  • Loss of trust in technology
  • Legal and ethical problems
  • Harm to vulnerable groups
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