Alexis Zumwalt portrayed
author

Alexis Zumwalt

Director of Federal Strategy and Growth
,
Snorkel AI

The latest from Alexis

Event recap: Adopting trustworthy AI for government
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Event recap: Adopting trustworthy AI for government

We’re currently experiencing such a rapid AI revolution and adoption of technologies, ranging from autonomous cars to virtual assistants and robotic surgeries and so much more, making it challenging for our government agencies to keep up. Especially when adding AI technologies to the mix, it can be even harder to manage.The crucial adoption of trustworthy AI and its successful integration…

May 23, 2022
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Bill of materials for responsible AI: collaborative labeling
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Bill of materials for responsible AI: collaborative labeling

In our previous posts, we discussed how explainable AI is crucial to ensure the transparency and auditability of your AI deployments and how trustworthy AI adoption and its successful integration into our country’s critical infrastructure and systems are paramount. In this post, we dive into making trustworthy and responsible AI possible with Snorkel Flow, the data-centric AI platform for government and federal agencies. Collaborative labeling and…

Apr 28, 2022
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Explainability through provenance and lineage
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Explainability through provenance and lineage

In our previous post, we discussed how trustworthy AI adoption and its successful integration into our country’s critical infrastructure and systems are paramount. In this post, we discuss how explainability in AI is crucial to ensure the transparency and auditability of your AI deployments. Outputs from trustworthy AI applications must be explainable in understandable terms based on the design and implementation of…

Apr 19, 2022
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Introduction to trustworthy AI
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Introduction to trustworthy AI

The adoption of trustworthy AI and its successful integration into our country’s most critical systems is paramount to achieving the goal of employing AI applications to accelerate economic prosperity and national security. However, traditional approaches to developing AI applications suffer from a critical flaw that leads to significant ethics and governance concerns. Specifically, AI today relies on massive, hand-labeled training datasets…

Apr 07, 2022
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For models that need to be right. Not just good enough.