Challenges with Trustworthiness of Data-Driven and Machine Learning Approaches

Artificial Intelligence (AI) is becoming more and more a part of the activities traditionally covered by the engineering analysis and simulation community. Recent advances in the application of AI, machine learning (deep learning) and predictive analytics, have brought these technologies to the fore in every area of industry.

This seminar hosted by the NAFEMS Americas Steering Committee brought together speakers from the end-user, consultancy, and academic industries to discuss where we are and how these technologies are being used to advance significantly the engineering analysis and simulation capabilities and approaches over the next 10 years.

Resource Abstract

The NAFEMS community is well aware of Verification & Validation (V&V), well developed guidelines meant to ensure that the predictions from computational engineering models can be credible and used with confidence to support decisions. AI techniques such as machine learning have become more prevalent, both within products, and as engineering tools. In this talk, we will cover the challenges associated with developing a similar set of V&V guidelines for data-driven, machine learning modeling approaches.