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Welcome to the safety, security and resilience discussion! Activities for this topic will be facilitated by the BSI team, one…
Many countries, including most developed countries, have an Artificial Intelligence strategy, aware of the enormous potential AI holds for economic…
As part of our journey of building the AI Standards Hub, we conducted workshops with over 140 stakeholders from across…
This blog post provides detail on what the AI Standards Hub is, how we built it, and why we hope…
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Ethically aligned design: a vision for prioritizing human well-being with autonomous and intelligent systems
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Standardization empowering AI-enabled systems in healthcare – workshop report
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Towards auditable AI systems
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Trust and artificial intelligence
The artificial intelligence (AI) revolution is upon us, with the promise of advances such as driverless cars, smart buildings, automated…
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Psychological foundations of explainability and interpretability in artificial intelligence
In this paper, we make the case that interpretability and explainability are distinct requirements for machine learning systems. To make…
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Four principles of explainable artificial intelligence
We introduce four principles for explainable artiļ¬cial intelligence (AI) that comprise fundamental properties for explainable AI systems. We propose that…
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A taxonomy and terminology of adversarial machine learning
This NIST Interagency/Internal Report (NISTIR) is intended as a step toward securing applications of Artificial Intelligence (AI), especially against adversarial…
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Towards a standard for identifying and managing bias in artificial intelligence
As individuals and communities interact in and with an environment that is increasingly virtual they are often vulnerable to the…
