Carol J. Smith
Software Engineering Institute
Publications by Carol J. Smith
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My Story in Computing with Carol Smith
April 15, 2021 • Podcast
Carol J. Smith
Carol Smith, who trained as a photojournalist, transitioned a love of telling people’s stories to a career in human-computer interaction working in artificial intelligence with the SEI’s Emerging Technology Center.
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Ethics in AI Engineering
December 15, 2020 • Video
Carol J Smith
The presentation discusses how to reduce unintended/harmful bias and prevent the inevitable harm that comes from "unknowable" systems.
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Ethics in AI
November 03, 2020 • Presentation
Carol J Smith
The presentation discusses how to reduce unintended/harmful bias and prevent the inevitable harm that comes from "unknowable" systems.
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Designing Trustworthy AI
April 29, 2020 • Podcast
Carol J Smith
Carol Smith discusses a framework that builds upon the importance of diverse teams and ethical standards to ensure that AI systems are trustworthy and able to effectively augment warfighters.
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Implementing Ethics: Developing Trustworthy AI at PyCon 2020
April 28, 2020 • Presentation
Carol J Smith
This presentation introduces the topic of ethics and walks through a user experience (UX) framework to guide AI development teams successfully through this process.
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Designing Trustworthy AI: A User Experience (UX) Framework
March 24, 2020 • Webinar
Carol J Smith
This webcast introduced a new user experience (UX) framework to guide the creation of AI systems that are accountable, de-risked, respectful, secure, honest and usable.
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Human–Machine Teaming and AI
January 29, 2020 • Video
Carol J SmithAndrew O. MellingerRitwik Gupta
In this Cyber Talk, SEI researchers Carol Smith, Andrew Mellinger, and Ritwik Gupta discuss the exciting challenges and opportunities for human–machine teaming and artificial intelligence.
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Designing Trustworthy AI: A Human-Machine Teaming Framework to Guide Development
December 10, 2019 • Conference Paper
Carol J Smith
The Human-Machine Teaming (HMT) Framework for Designing Ethical AI Experiences, when used with a set of technical ethics, will guide AI development teams to create AI systems that are accountable, de-risked, respectful, secure, honest, and usable
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