Complex AI Reliability

Complex AI Reliability

Abstract



Dianna (https://accendoreliability.com/about/...) and Fred (http://accendoreliability.com/about/f...) discuss complex AI reliability.



Key Points



Join Dianna and Fred as they discuss complex AI reliability: using AI for complex systems.

Topics include:




• the pitfalls of trusting AI without proper validation and monitoring.


• how small errors in AI decision-making can compound and lead to unreliable outcomes.


• why good data and established practices are essential before implementing AI in maintenance and planning.


• day trading, comedies, and quality scorecards




Enjoy an episode of Speaking of Reliability. Where you can join friends as they discuss reliability topics. Join us as we discuss topics ranging from design for reliability techniques to field data analysis approaches.







Download Audio (http://episodes.reliability.fm/sor/so...) RSS (http://accendoreliability.com/series/...)






Show Notes



In this episode of Speaking of Reliability, Fred and Dianna discuss complex AI reliability, in using AI for complex systems.



They share their experiences with AI, noting that while it can be a helpful start, it’s not always a finished product.



They also talk about a use study of using AI for stock trading. The goal was to use AI as an agent for decision making. It’s an example of compounding probabilities, with risk and uncertainty in those decisions.



The discussion highlights the risk of relying on AI without proper validation, as small errors in AI decision-making can compound and lead to unreliable outcomes. They emphasize that AI is only as good as the data it’s trained on, and that good data and established practices are essential before implementing AI.



They conclude that AI is a tool that needs to be evaluated and monitored.



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