How can datasets be made more representative to mitigate bias?
How can feedback loops in AI systems reinforce or mitigate bias?
How can organizations ensure their AI systems are accountable to users?
Explain the impact of overfitting and underfitting on AI safety.
How do you balance explainability and model performance?
What are the key challenges in balancing accuracy and fairness in AI systems?
How can organizations ensure compliance with data protection laws like GDPR?
What do you understand by AI safety, and why is it critical?
Explain the importance of inclusive design in reducing AI bias.
What are the long-term consequences of ignoring ethical considerations in AI?
How can preprocessing techniques reduce bias in datasets?
Can AI systems ever be completely free of bias? Why or why not?
What measures should be taken to prevent data misuse in AI?
How can AI developers ensure ethical handling of sensitive data?
What is bias in AI systems? Provide some examples.