Evaluating Trustworthiness of AI Systems

Software Engineering Institute (SEI) Webcast Series

Konten disediakan oleh Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff. Semua konten podcast termasuk episode, grafik, dan deskripsi podcast diunggah dan disediakan langsung oleh Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff atau mitra platform podcast mereka. Jika Anda yakin seseorang menggunakan karya berhak cipta Anda tanpa izin, Anda dapat mengikuti proses yang diuraikan di sini https://id.player.fm/legal.

2y ago 1:02:08

MP4•Beranda episode

AI system trustworthiness is dependent on end users' confidence in the system's ability to augment their needs. This confidence is gained through evidence of the system's capabilities. Trustworthy systems are designed with an understanding of the context of use and careful attention to end-user needs. In this webcast, SEI researchers discuss how to evaluate trustworthiness of AI systems given their dynamic nature and the challenges of managing ongoing responsibility for maintaining trustworthiness.

What attendees will learn:

Basic understanding of what makes AI systems trustworthy
How to evaluate system outputs and confidence
How to evaluate trustworthiness to end users (and affected people/communities)

174 episode

#Tech #Cybersecurity #Securecoding #Softwarearchitecture #Softwaredevelopment #Softwareengineering #Carnegie Mellon University Software Engineering Institute #SEI Members of Technical Staff #Video #Podcasting Education