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.
Misinformation
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.