What Is Ethical AI? Why Is It Important?

Problem With AI

AI systems inherit biases from developers or training data, inevitable due to human-produced data. Human-generated data inherently carries biases, posing significant ethical challenges for AI systems.

Types Of Bias

AI systems can acquire five types of biases: Algorithmic bias, Data bias, Confirmation bias, Stereotyping bias, and Exclusion bias.

Ethical AI

Ethical AI is the development and use of artificial intelligence systems in a way that considers and prioritises ethical principles - transparency, justice and fairness, non-maleficence, responsibility & privacy.


Generative AI's progress toward human-like responses has led to misuse, notably with the global rise of deepfakes targeting celebrities. Tools like ChatGPT facilitate more sophisticated fraudulent activities.

How To Make Ethical AI Systems

Establish A Strong Ethical Framework> Implement Fairness & Non-Discrimination> Prioritising Transparency & Explainability> Design For Accountability & Responsibility.

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