Donna Spiegelman presented the 2026 Donna J. Brogan Lecture in Biostatistics on April 20 at Emory University. Spiegelman’s lecture, titled “Causal Inference: The Limits of Confounding, the Boundlessness of Measurement Error,” examined two central sources of bias in epidemiologic research.
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Spotlight on AI: The Importance of Human-Centered Machine Learning in Safety Critical Systems
Machine learning and data science are transforming decision-making in safety-critical domains such as aerospace, automotive, health care, and industry manufacturing. Though these technological advances have many advantages, they do present issues with transparency and reliability. This is where human-centered machine learning plays a crucial role.
Navigating Challenges, Embracing AI, and Shaping the Future
ASA President Ji-Hyun Lee addresses the real challenges affecting ASA members today.
JEDI, CAUSE Team to Offer Resources for JEDI-Informed Teaching
Recently, a group involved in both JEDI and CAUSE came together to create a space to host resources for JEDI-informed statistics teaching: the JEDI-CAUSE website. Each entry is relevant to statistics and data science education and has a JEDI theme.
Designing Against Bias in Machine Learning and AI
David Corliss examines how shifting the focus to testing for and mitigating bias at the design stage instead of after code is released can help prevent many of the problems seen in machine learning and artificial intelligence.
Measuring and Reducing Bias in Machine Learning, AI
Learning to avoid sources of bias and quantifying and minimizing its impact allow the realization of the promise of machine learning and artificial intelligence to benefit all, David Corliss says.
Equity and Bias in Algorithms: A Discussion of the Landscape and Techniques for Practitioners
Algorithmic bias can occur as a result of decisions made throughout the algorithm development and deployment process. Left unaddressed, it can deeply affect equity. Emily Hadley looks at techniques to consider when developing algorithms.
Justice, Equity, Diversity, and Inclusion
In her column this month, Wendy Martinez announces the formation of the ASA’s Anti-Racism Task Force and talks to the co-chairs, Adrian Coles and David Marker, about their important work and how others can contribute.
Effective Collaboration Between Statisticians and Principal Investigators
Rachel Rogers defines collaboration and lays out what effective collaboration is for a master’s-level biostatistician.