Interviewer: In your recent paper, you discuss the 'Black Box' problem in Deep Learning. Why is 'Explainable AI' (XAI) so crucial for the future of technological integration? \nResearcher: The issue is trust and accountability. If a neural network denies a medical treatment or a loan, but we cannot t\frace the mathematical weights that led to that decision, we face an ethical vacuum. Without XAI, --- \nWhich statement best synthesizes the consequence of lacking Explainable AI?
Şıklar
the systems will work much faster because they won't have to document their decision-making processes.
we are essentially outsourcing moral agency to opaque algorithms that are immune to judicial or ethical scrutiny.
users will be more likely to accept the AI's decisions because they will perceive them as being purely objective.
the hardware requirements for running such complex simulations will decrease significantly over the next decade.
the integration of AI into daily life will be seamless, as people generally do not care about the underlying logic of technology.
Çözüm Açıklaması
Researcher, 'Kara Kutu' (Black Box) problemine değiniyor; yani kararların nasıl alındığının bilinmemesi. Eğer bu süreç 'açıklanabilir' (Explainable) değilse, ahlaki sorumluluğu şeffaf olmayan ve denetlenemeyen algoritmalara devretmiş oluruz. B şıkkındaki 'outsourcing moral agency to opaque algorithms' (ahlaki temsilciliği opak algoritmalara devretmek) ifadesi, konunun felsefi ve etik ağırlığını tam olarak yansıtır.
Video Çözüm
AI ile video çözüm oluştur
İnteraktif Çözüm
Adım adım, sesli ve animasyonlu çözüm. Quiz ile kendini test et!