VernacuLab
VernacuLab is a research consultancy dedicated to transforming AI technology into products that provide utility and value across industry and for the public.
About
VernacuLab is a research consultancy dedicated to helping organizations optimize the value of their advanced technology and increase collective understanding of how AI is transforming our culture and society.
At VernacuLab, we think the most pressing questions about AI are human. Our services focus on these factors, including:
Consulting
AI Governance
Trustworthy AI
Risk Management
Operating and Monitoring AI in Deployment
Analysis of Online Narratives
Markup of Human Dialogues with AI Chatbot
Feedback Loops in Technology Use
Securing Proprietary Content
Research
Testing and Evaluation
AI Risk Management
Proving AI Uses Cases
Experience and Expertise
Advisory
American Bar Association President’s Task Force on Artificial Intelligence and the Law
National Academy of Sciences
Evaluation Programs
Program Lead: NIST Assessing Risks and Impacts of AI (ARIA)
The Assessing Risks and Impacts of AI (ARIA) Program Evaluation Design Document (2024)
The NIST Assessing Risks and Impacts of AI (ARIA) Pilot Evaluation Plan (2024)
Documents
Guidance
Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile, NIST Trustworthy and Responsible AI, National Institute of Standards and Technology, (2024)
Towards a Standard for Identifying and Managing Bias in Artificial Intelligence, Special Publication (NIST SP), National Institute of Standards and Technology, (2024)
Video Presentations
AI Governance: A Conversation with Reva Schwartz of the National Institute of Standards and Technology (NIST) about NIST's new AI Risk Management Framework, American Bar Association (September 2023)
International Association of Privacy Professionals about NIST AI RMF (March 2023)
Podcast Appearances
Resources
Recent Presentations
Keynote Speaker, IEEE ProComm June 2024
Featured Speaker, Carnegie Mellon Convening on Operationalizing the NIST Risk Management Framework (July 2023)
Invited Workshop Presenter: Sociotechnical Approaches to Measurement and Validation for Safety in AI (July 2023)
Fireside Chat: Using the AI RMF, 2023 Insurance Public Policy Summit (May 2023)
Fireside Chat: Using AI RMF to manage the risks of Generative AI, Harvard Berkman Klein Center (May 2023)
Schwartz, R. (2024) Informing an Artificial Intelligence risk aware culture with the NIST AI Risk Management Framework. Chapter. Artificial Intelligence: Legal Issues, Policy, and Practical Strategies Edited by Cynthia H Cwik, Christopher A Suarez, and Lucy L Thomson. American Bar Association.
Slaughter, I., Greenberg, C., Schwartz, R., & Caliskan, A. (2023). Pre-trained Speech Processing Models Contain Human-Like Biases that Propagate to Speech Emotion Recognition. Conference on Empirical Methods in Natural Language Processing.
Recent Publications
Qin, H., Kong, J., Ding, W., Ahluwalia, R., El Morr, C., Engin, Z., Effoduh, J.O., Hwa, R., Guo, S.J., Seyyed-Kalantari, L., Muyingo, S.K., Moore, C.M., Parikh, R., Schwartz, R., Zhu, D., Wang, X., & Zhang, Y. (2023). Towards Trustworthy Artificial Intelligence for Equitable Global Health. ArXiv, abs/2309.05088.
Daniel Atherton, Reva Schwartz, Peter C. Fontana, Patrick Hall (2023) The Language of Trustworthy AI: An In-Depth Glossary of Terms. (National Institute of Standards and Technology, Gaithersburg, MD), NIST Artificial Intelligence AI 100-3
Gleaves, L.P., Schwartz, R., and Broniatowski, D.A. (2020) The Role of Individual User Differences in Interpretable and Explainable Machine Learning Systems, arXiv:2009.06675
Contact
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Resources
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