Ethical AI

Ethical Data

Definition

Ethical AI refers to the development and deployment of AI systems that prioritize fairness, accountability, transparency, and human rights. It focuses on minimizing harm and aligning AI with societal values.

Purpose

The purpose is to ensure AI benefits people equitably and does not reinforce discrimination or unsafe practices. Ethical frameworks guide responsible AI use.

Importance

  • Builds public trust in AI technologies.
  • Prevents harmful or discriminatory outcomes.
  • Ensures compliance with laws and ethical norms.
  • Overlaps with fairness, responsible AI, and governance.

How It Works

  1. Define ethical guidelines and principles.
  2. Identify risks of harm or bias.
  3. Apply fairness and transparency measures.
  4. Monitor and audit AI systems continuously.
  5. Update policies as AI evolves.

Examples (Real World)

  • EU AI Act: regulates AI use with ethical safeguards.
  • Google AI Principles: corporate guidelines for ethical AI.
  • Partnership on AI: multi-stakeholder group promoting responsible AI.

References / Further Reading

  • OECD AI Principles.
  • NIST AI Risk Management Framework.
  • Jobin, A. et al. “The global landscape of AI ethics guidelines.” Nature.