week 10 Flashcards
(8 cards)
What is the key difference between causation and correlation in AI?
Correlation shows a statistical relationship, while causation indicates a direct cause-and-effect link.
What is downward causation in the context of AI?
Higher-level systems influencing and constraining lower-level processes.
Why is causality important for AI decision-making?
AI needs to differentiate causation from correlation to avoid misleading conclusions.
How can AI improve its understanding of causality?
By using causal models like Bayesian networks.
Why is developing causal models in AI important?
Because causal models help AI understand cause-effect relationships rather than just correlations.
How can causal AI improve decision-making in healthcare?
By identifying the root causes of diseases rather than just associations.
What role does causal AI play in ethical decision-making?
It helps determine accountability by identifying whether an AI decision directly caused harm.
How might quantum computing impact causal AI?
By challenging traditional models of causality through quantum entanglement.
