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5. Ethical Dilemmas: Bias, Privacy, and Control
The Bias Problem
AI systems often inherit biases from training data. For example:
- Racial bias: Facial recognition errors disproportionately affect people of color.
- Gender bias: Hiring algorithms favor male candidates.
Privacy Risks
AI’s hunger for data raises concerns:
- Health-tracking apps selling user data.
- Governments misusing surveillance AI.
Who Controls AI?
Tech giants like Google and OpenAI currently dominate AI development. Bill Gates has called on governments to regulate AI to ensure its safe and ethical use, but efforts to create global coordination on this issue are progressing slowly.
6. Preparing for the AI Future: Policies and Education
Reskilling the Workforce
- Corporate responsibility: Amazon’s .2 billion upskilling program trains workers in AI management.
- Education reform: Coding and AI literacy in school curricula.
Global Collaboration
- UN’s AI Advisory Body: Advocating for equitable access to AI tools.
- EU’s AI Act: Strict regulations on high-risk AI systems.
