David Corliss recognizes outstanding accomplishments this year.
Stats4Good
UCS’s Science for Public Good Fund Targets Projects with Local Impact
The Union of Concerned Scientists’ Science for Public Good Fund offers grants up to $1,500 to support science in service to the public, making it ideal for a wide range of data for good advocates and projects.
2023 Peace Award Honors COVID Researcher with Global Impact
Bhramar Mukherjee of the University of Michigan was recently honored with the 2023 Karl E. Peace Award for Outstanding Statistical Contributions for the Betterment of Society, recognizing her commitment to and accomplishments in biostatistics on a global scale.
Ethical AI Groups Spring Up Around the World
This month, David Corliss shares how the Data4Good practitioners are leading the way in developing ethics best practices for artificial intelligence.
United Nations Sustainable Development Goals: A World of Opportunity in Data for Good
This month, David Corliss looks at all 17 United Nations’ sustainable development goals, projects, and resources and proposes ways statisticians can get involved.
JSM 2023: D4G Informing Decisions and Driving Discovery
This month, David Corliss shares some of the Data for Good events happening at JSM 2023. You won’t want to miss these.
COVID on the Cusp: Data for Good Research Expands as Pandemic Phase Ends
With the COVID-19 pandemic phase winding down, now is the time to act on what we have learned from this crisis—the Stats4Good top challenge in biostatistics for 2023.
ASA Committee Defends Statistics, Statisticians Around the World
Data for Good makes the world a safer place through statistical science, and the Committee on Scientific Freedom and Human Rights makes the world a safer place for statisticians engaged in this work.
Earth Day Projects: Measuring Climate Change and Taking Action
It’s April, the flowers are blooming, and the birds are singing, so it must be time for Stats4Good’s annual list of Earth Day project ideas.
Finding Your Voice in Data for Good
David Corliss uncovers how science is not enough. Data for Good needs directors just as much as data, advocates as well as algorithms, and socializing the work in addition to the science.