915 lines
83 KiB
Text
915 lines
83 KiB
Text
<!DOCTYPE html>
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<p dir="ltr"><span>A multidisciplinary team of computer scientists, cognitive scientists, mathematicians, and specialists in AI and machine learning with varied backgrounds and research specialties, explore and define the core tenets of explainable AI (XAI). The team aims to develop measurement methods and best practices that support the implementation of those tenets. Ultimately, NIST intends to develop a metrologist’s guide to AI systems that address the complex entanglement of terminology and taxonomy as it relates to the myriad layers of the AI field. AI must be explainable to society to enable understanding, trust, and adoption of new AI technologies, the decisions produced, or guidance provided by AI systems.</span></p><h2><strong>Explainable AI</strong></h2><h3><strong>Workshop </strong></h3><p>NIST held a <a href="/news-events/events/2021/01/explainable-ai-workshop" data-entity-type="node" data-entity-uuid="4a8133ec-38cd-4fb7-bc44-a80d3edf5ed4" data-entity-substitution="canonical" title="Explainable AI Workshop">virtual workshop on Explainable Artificial Intelligence (AI)</a> on January 26-28, 2021. Explainable AI is a key element of trustworthy AI. As part of NIST’s efforts to provide foundational tools, guidance, and best practices for AI-related research, NIST released a draft report, <a href="/publications/four-principles-explainable-artificial-intelligence-draft" data-entity-type="node" data-entity-uuid="dd5742fa-3321-42ee-a4ca-6f2ebc376fb0" data-entity-substitution="canonical" title="Four Principles of Explainable Artificial Intelligence (Draft)">Four Principles of Explainable Artificial Intelligence</a>, for public comment. Inspired by <a href="/artificial-intelligence/comments-received-four-principles-explainable-artificial-intelligence-nistir" data-entity-type="node" data-entity-uuid="102e4b6b-1fa7-485e-b3d8-8c1037fc6468" data-entity-substitution="canonical" title="Comments Received on Four Principles of Explainable Artificial Intelligence (NISTIR 8312 DRAFT)">comments received</a>, this workshop delved further into developing an understanding of explainable AI. A <a class="media-link-ga " data-entity-substitution="canonical" data-entity-type="media" data-entity-uuid="ac1aa9c2-ac39-481e-a4d5-8e83e0d2a073" data-file-url="/system/files/documents/2021/09/24/XAI_Workshop_Summary_Final_20210922.pdf" href="/document/explainable-ai-workshop-summary-held-january-2021" title="Explainable AI Workshop Summary - held January 2021">summary of the workshop</a> is available. </p><p><span>The final version of the report was published in September 2021. See below.</span></p><h3><strong>Related Publications </strong></h3><ul><li><a href="https://doi.org/10.6028/NIST.IR.8312">Four Principles of Explainable Artificial Intelligence <span>(NISTIR 8312)</span></a><span> (September 2021) </span></li><li><p dir="ltr"><a href="https://nvlpubs.nist.gov/nistpubs/ir/2021/NIST.IR.8367.pdf"><span>Psychological Foundations of Explainability and Interpretability in Artificial Intelligence (NISTIR 8367</span></a>) (April 2021) </p></li></ul><div class="nist-callout"><h2><strong>Video: Psychology of Interpretable and Explainable AI</strong></h2>
|
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<div class="align-left nist-video-thumbnail--small nist-video-thumbnail--lightbox nist-video-thumbnail" data-lightbox="https://www.kaltura.com/p/684682/embedPlaykitJs/uiconf_id/55674542?iframeembed=true&entry_id=1_v7i4e45h" data-media-id="630861">
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<img alt="Psychology of Interpretable and Explainable AI" loading="lazy" src="https://cdnsecakmi.kaltura.com/p/684682/sp/68468200/thumbnail/entry_id/1_v7i4e45h/width/1280" typeof="foaf:Image">
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<p> </p><p dir="ltr"><span>Interview between Dr. David Broniatowski and Natasha Bansgopaul addressing insights from</span><strong> </strong><a href="https://nvlpubs.nist.gov/nistpubs/ir/2021/NIST.IR.8367.pdf"><strong>Psychological Foundations of Explainability and Interpretability in Artificial Intelligence (NISTIR 8367) (</strong><span>April 2021</span></a><span>), authored by Broniatowski.</span></p></div><h2><strong>Updates and Contact Information</strong></h2><p>Stay tuned for further NIST announcements and related activity by checking this page or by <a href="https://public.govdelivery.com/accounts/USNIST/subscriber/new">subscribing to Artificial Intelligence updates</a>.</p><p>Please direct questions to <span class="spamspan"><span class="u">ai-inquiries</span> [at] <span class="d">nist.gov</span><span class="t"> (ai-inquiries[at]nist[dot]gov)</span></span>. </p>
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Created April 6, 2020, Updated February 7, 2025
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