Core AI ethics problems: Bias — if training data reflects historical inequalities, the model makes the same decisions (documented examples of gender, racial, and class discrimination exist). Transparency — "black box" models cannot explain their decisions. This is extremely dangerous in legal, medical, and financial contexts.
The accountability question: who is responsible when AI makes a mistake? The model creator, the user, or both? The EU AI Act (2024) is the world's first comprehensive AI legislation. High-risk systems (employment, credit, courts) face strict oversight. For developers: working by the FATE principles — fairness, accountability, transparency, ethics — is essential.
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