Part 5/14:
Bias-Free Training Data: Ensuring that the datasets used do not perpetuate harmful prejudices.
Transparency and Explainability: Requiring systems to justify their decisions, facilitating error detection.
Assisted Decision-Making: Using AI as an aid rather than a replacement, especially in critical applications like justice or healthcare.
Despite global initiatives—like those by the European Union or United Nations—public awareness remains uneven. Technology’s rapid evolution tests existing frameworks of regulation, exposing vulnerabilities and the need for vigilance.