Welcome to Stats4Good’s annual list of leading questions and challenges in Data for Good. The list is a call to action to the statistics and data science community to help inspire new research, projects, collaborations, and applications to address these issues. The items listed here can be the focus of student projects, presentations and panel discussions at conferences, and webinars. All intersect with the public interest, offering opportunities for government advocacy, legislation, and collaboration with organizations addressing these important issues.
Biostatistics: AI and Intelligent Systems in Biostatistics
The large language model revolution is just one part of the explosion of artificial intelligence and intelligent systems in all areas of science. So much more than writing, intelligent systems have grown to include machine perception of their surroundings, automated data collection and decision support in biological systems, more advanced algorithms for medical diagnosis, and human-machine interfaces for prosthetics. Yet, through all this, one thing has remained the same: Statistical science remains the beating heart of AI. This Data for Good challenge focuses on the biostatistics theory, models, and practices that make the AI work, making possible the benefits gained from intelligent systems.
Environmental Advocacy: Analytics for Healthier Oceans
At the end of every waste disposal system, every manufacturing process, and every human activity are our oceans. The vast, multifaceted intersectionality of this ecosystem affects all life on this planet in so many ways. At the same time, so much more can be done to better understand our oceans, the risks they face, and their effect on all life systems—from weather and climate change to biological systems and human impacts and consequences. New data collection methods and systems, innovative predictive models that describe how the oceans respond to changing input, collaboration between research teams, and funding priorities to make it all possible will power important advances for the benefit of all.
Data: Resiliency and Hardening of Critically Important Data Sets
In Norway’s remote Svalbard archipelago, a storage facility known as the Global Seed Vault contains samples of more than 20 million species of seeds to protect the biodiversity they represent. This challenge for 2025 looks at data the same way, calling on the analytic community to identify important data sets and preserve copies. Risks include potential deletion, damage, or discontinuation due to lack of support, tampering by special interests, and data sources now available to the public going dark. This is an area especially well-suited to action by the Data for Good community, as different people, research teams, and organizations can identify the publicly available data most important to their work and consider whether independent secure storage is desirable.
Data for Good Organization and Infrastructure: Open-Source Tools to Address the Digital Divide
The digital divide creates a world of haves and have nots, where people most in need of the power of advanced analytics have limited access. Open-source tools available for use or download through a web browser address this divide. As statistical science continues to advance, the importance of developing new open tools doesn’t diminish. Open-source packages for emerging analytic methods are constantly needed. Every dissertation defended or overseen offers an opportunity to contribute to the good of others. Especially important today is access to large language models. All open-source tools offer a way to support the key D4G principle of analytics for all.
Human Rights: Statisticians at Risk
The work of the ASA Committee on Scientific Freedom and Human Rights includes “violations of and threats to the scientific freedom and human rights of statisticians and other scientists throughout the world.” Sadly, this mission has become an active concern with the global increase in the number of governments seeking to control information available to the public by censoring statisticians and their work. This challenge is an invitation to learn more about statisticians at risk around the world, working with the CSFHR to help through advocacy and promoting public awareness.
Now that the areas of special interest for this year have been identified, it is time to take up your own challenge. Chose an area that interests you, investigate data sources, reach out to potential collaborators, and start planning your 2025 Data for Good projects!
Getting Involved
In opportunities this month, look at the ASA conferences for the year and start making your plans. In addition to the Joint Statistical Meetings, there are opportunities for every area of interest.
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