What are the challenges of AI explainability, and how can they be addressed?
Hi everyone,
As AI solutions continue to advance and become more integrated into various industries, one crucial aspect that often comes up is the explainability of these systems. I’m reaching out to understand more about the challenges associated with AI explainability.
What are the main obstacles in making AI solutions ( https://www.lenovo.com/de/de/servers-storage/hybrid-cloud-ai-solutions/ ) systems transparent and understandable, and what strategies or practices can be employed to address these challenges effectively? I’m particularly interested in how we can ensure that AI decisions are interpretable and trustworthy, especially in high-stakes applications like healthcare or finance.
Any insights, experiences, or recommendations on improving AI explainability would be greatly appreciated. Looking forward to a fruitful discussion!
Best regards,
Jonathan Jone