Definition
AI ethics are the moral principles that guide the design, development, and use of intelligent systems so they benefit humans without bias or harm.

Introduction
From medical diagnosis to recruitment and trading, algorithms now make decisions once reserved for humans. But machines reflect the values we teach them. The question is no longer “What can AI do?” but “What should AI do?”

Explanation
1️⃣ Bias and Fairness – AI trained on biased data can discriminate; ethical developers must test for equity.
2️⃣ Transparency – Users deserve to know how algorithms make decisions.
3️⃣ Accountability – Responsibility remains with humans, not machines.
4️⃣ Privacy Protection – AI must use data lawfully and securely.
5️⃣ Human Oversight – Critical decisions require human review.

Key Takeaways

Ethical AI is transparent and inclusive.

Accountability can never be outsourced to code.

Trust is AI’s true currency.

Real-World Case
IBM Watson for Oncology was accused of recommending unsafe treatments due to biased training data. IBM responded by redesigning the model with clinical oversight and publishing data-quality standards — a lesson that AI must augment, not replace, expertise.
Reference: https://research.ibm.com