Sarah Bargal provides an overview of AI, machine learning, and deep learning, illustrating their potential for both positive and negative applications, including authentication, adversarial attacks, deepfakes, generative models, personalization, and ethical concerns.
The NIST Risk Management Framework (RMF) Introductory Courses offer free, self-paced online training on managing cybersecurity and privacy risks using NIST’s RMF methodology and related publications.
National Institute of Standards and Technology (NIST)
Hear perspectives on topics including centering beneficiaries and workers in new ways, digital service delivery, digital identity, and automation.This video was recorded at the Digital Benefits Conference (BenCon) on June 14, 2023.
The Beeck Center for Social Impact + Innovation's Digital Service Network (DSN) maintains a Government Digital Service Team Tracker: a living database for those seeking to learn more about the locations, structures, mandates, and more of government digital service teams across the United States.
A panel of experts discuss the application of civil rights protections to emerging AI technologies, highlighting potential harms, the need for inclusive teams, and the importance of avoiding technology-centric solutions to social problems.
The article discusses the phenomenon of model multiplicity in machine learning, arguing that developers should be legally obligated to search for less discriminatory algorithms (LDAs) to reduce disparities in algorithmic decision-making.
User research requires working as a team, since it necessitates running sessions with participants, observing and moderating research sessions, analyzing and synthesizing results, as well as communicating results effectively.
This blog explains how to provide culturally and linguistically appropriate services to individuals who have experienced trafficking, emphasizing the importance of cultural competence and the CLAS Standards.
U.S. Department of Health and Human Services (HHS)
