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Kandungan disediakan oleh Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff. Semua kandungan podcast termasuk episod, grafik dan perihalan podcast dimuat naik dan disediakan terus oleh Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff atau rakan kongsi platform podcast mereka. Jika anda percaya seseorang menggunakan karya berhak cipta anda tanpa kebenaran anda, anda boleh mengikuti proses yang digariskan di sini https://ms.player.fm/legal.
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Evaluating Trustworthiness of AI Systems

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Manage episode 376935557 series 1264075
Kandungan disediakan oleh Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff. Semua kandungan podcast termasuk episod, grafik dan perihalan podcast dimuat naik dan disediakan terus oleh Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff atau rakan kongsi platform podcast mereka. Jika anda percaya seseorang menggunakan karya berhak cipta anda tanpa kebenaran anda, anda boleh mengikuti proses yang digariskan di sini https://ms.player.fm/legal.

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)
  continue reading

174 episod

Artwork
iconKongsi
 
Manage episode 376935557 series 1264075
Kandungan disediakan oleh Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff. Semua kandungan podcast termasuk episod, grafik dan perihalan podcast dimuat naik dan disediakan terus oleh Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff atau rakan kongsi platform podcast mereka. Jika anda percaya seseorang menggunakan karya berhak cipta anda tanpa kebenaran anda, anda boleh mengikuti proses yang digariskan di sini https://ms.player.fm/legal.

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)
  continue reading

174 episod

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