With a PhD in statistical astrophysics, David Corliss is lead, Industrial Business Analytics, and manager, Data Science Center of Excellence, Stellantis. He serves on the steering committee for the Conference on Statistical Practice and is the founder of Peace-Work, a volunteer cooperative of statisticians and data scientists providing analytic support for charitable groups and applying statistical methods in issue-driven advocacy.
As a new year begins, Stats4Good is starting a new feature. Just as last month reviewed the past year in Data for Good, the January column will look ahead. Glancing at many of the highest priorities in D4G, some stand out as opportunities of the moment. Some are areas in which statistical science has advanced, while others are areas in which the needed technology doesn’t yet exist. Some are fairly unglamorous—the hard work on infrastructure needed to lay the analytic foundation of the future.
This whole column has been about new opportunities; however, the ASA’s Conference on Statistical Practice will be in San Francisco February 2–4. With keynotes from 2023 ASA President Dionne Price and the Human Rights Data Analytics Group’s Megan Price, the annual ethics panel, and much more, CSP is the place to be in February. I hope to see many of you there.
This challenge list shines a light on exciting new opportunities and is meant to encourage the D4G community to tackle overlooked or under-resourced concerns. Lifting up a single challenge in each area, the goal is to highlight opportunities with the most potential impact for the greater good.
Biostatistics: Leveraging COVID Learnings
The COVID-19 pandemic changed the world and science. Not since the Manhattan Project’s invention of big science have world events (sadly, inexpressibly tragic ones) had such an impact on how science is done. The number of papers has exploded, even as the time to publish—driven by the urgency of the crisis—has become far less. The scientific community has done more than stop a pandemic faster than was ever imaginable; it has also created ways of working to empower rapid response to future events—but only if we go above and beyond once again to document and teach how Data for Good has changed so these new models of working can be leveraged. This moment is the last of the COVID crisis and the first of the next! We, as a community, must rise to meet the challenge.
Environmental Advocacy: Climate Change Impacts and Remediation
Forget about climate change as maybe, if, or when. The damaging effects of anthropogenic climate change are all around us right now! Identifying the impacts that have already been realized and developing strategies and methods to address them are desperately needed. Prevention is, of course, still needed. However, the sad truth is that climate change has already caused widespread damage and is getting worse every day. The problem has grown beyond prevention to include identification and mitigation. This is one area in which a small number of researchers focused on a specific problem can have the greatest impact through hackathons, capstone projects, and public outreach and mobilization. The opportunities and challenges are all around us and all around the world.
Data: Unique, Secure, Transferable Identifiers
Research on better methods can lack wow factor. However, it is vitally needed to support everything else on the list, making it one of the most important endeavors we have in this or any other year. This year’s top challenge in the data category will allow individuals to be tracked across multiple projects by different stakeholders, enabling propensity studies and wider collaborations. It will leverage experts from other areas. In the never-ending arms race for more secure data, people who exploit others by exploiting their data have been gaining. Now is the time for renewed effort in the science of sharing data in a secure and trustworthy manner. In the final analysis, nearly everything we do will depend in part on this.
Data for Good Organization and Infrastructure: More Project Managers
I’ve said it before but it’s going to continue to be a top challenge until there are even half as many as are desperately needed. Speaking frankly, dear friends, this is our single greatest weakness today. Maybe substitute your annual hackathon for a day to train new D4G project managers? Absolutely! Add a leadership and project management track to your university’s data science program? Get started on it! When we look back on 2023, this may have the greatest impact of all.
Human Rights: Critical Race Theory as a Statistical Practice
Critical Race Theory began as legal and historical questions about structural disadvantages by race and how to address them. In the years following the civil rights movement, scholars looked further into the mechanisms of how disadvantage has been built into our society and carried forward. Connecting the dots between historical oppression and modern disadvantages inherently includes statistical science. The last few years have seen the dawn of CRT as a statistical practice. Now is the time for new projects and collaborations—especially with experts in legal, historical, and sociological research—to more firmly establish the statistics and data science need to carry CRT forward.
The 2023 Challenge List is intended to inspire both discussion and action as ideas for research are shared, debated, and developed into conference papers, presentations, posters, and panel discussions. Capstone, master’s, and PhD projects can focus on these areas of greatest need. Special issues of journals can be developed to focus on a D4G top challenge. This list can be used to launch new collaborations, inspire hackathon themes, and much more.
At the end of the year, I will announce a 2023 Hall of Fame for leading accomplishments in each area. This is our opportunity, and now is the time to take new high-impact action in Data for Good.
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