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You are here: Home / Additional Features / Journal Highlights / CHANCE highlights / Newest Issue Focuses on AI, 2024 Data Challenge Expo

Newest Issue Focuses on AI, 2024 Data Challenge Expo

June 2, 2025 Leave a Comment

Donna LaLonde and Wendy Martinez

The latest issue of CHANCE includes two special themes: artificial intelligence and the 2024 ASA Data Challenge Expo. To better understand members’ needs and investigate efforts for the use and adoption of AI within the statistical community, the American Statistical Association Committee on Data Science and Artificial Intelligence conducted a survey on how ASA members use AI. Committee members Mark Glickman and Jun Yan discuss the results of the survey in “ASA Members’ Perspectives on the Use of Generative AI.”

Next is an essay written by Edward Melnick and Ron Melnick titled “Comparing Traditional Statistical Modeling to AI Approaches.” Edward passed away in September 2024 while the article was under review, but it is included in this issue, along with memories of his achievements.

The last article related to AI is titled “Statistical Decision Theory: Using a 1940s Idea to Fix a Problem in 21st Century AI.” Jeff Dominitz and Charles Manski offer their perspective on how and why statistical decision theory should replace out-of-sample approaches for assessing model performance.

The ASA Data Challenge Expo is an annual contest cosponsored by the Statistical Computing, Government Statistics, and Statistical Graphics sections of the ASA. Contestants are challenged to analyze a specific data set using statistical, machine learning, and visualization tools and methods. The submissions are presented and judged at the Joint Statistical Meetings, and awards are presented in two categories: students and professionals. This issue includes articles written by all the winners in the student category.

To set the stage, Jodie Smylie of NORC and colleagues write an introduction to the General Social Survey, which was the 2024 challenge data set. Then, first-place winners Ujjayini Das and Andrew Forrester contribute “Do People Trust Enough to Respond to Surveys?” This is followed by “Analysis of Mental Health and Substance Use Disorders Pre- and Post-COVID-19,” written by second-place winners Bryanna Schaffer and Yichi (Christie) Song. The final article is titled “Investigating American Optimism: Evidence from 2022 General Social Survey (GSS) Data” and is written by third-place winners Md Mahedi Hasan, Wooyoung Kim, Jacqueline Carlton-Wargo, and David Rice.

In addition to the articles about AI and the data expo are an article by Bahareh Zahirodini and Moinak Bhaduri, “Marking Contemporary America’s Attitudinal Stance Toward Modern Businesses: A Bayesian Attempt to Detect Deviation Patterns Based on Demographics and Politics,” that addresses societal attitudes and an article by Jitendra Ganju, “When Bias in Interpreting a Clinical Trial Result in a Press Release Crosses a Line,” that discusses the reporting of clinical trial results.

The issue wraps up with a few columns. Eric-Jan Wagenmakers responds to the Taking a Chance in the Classroom column in the September 2024 issue (“Puzzling Probabilities of Probability Puzzles”). His letter is titled “Why Bayesians Need Not Be Puzzled by Probability Puzzles.” In the One Thing About… column, Miguel de Carvalho discusses why we need to know the answer to the question, “R, Python, and calculus: Are they on the same page?” Finally, History Chronicles editor, Penny Reynolds, offers her second column of a series, “Best of Three: Three Women Who Revolutionized Statistical Practice,” in which she describes the life and contributions of Jessamine Whitney (1880–1941).

The editors welcome all ideas and contributions, which can be emailed to chancemag.editor@gmail.com.

ASA members can view CHANCE by visiting the member portal.

Filed Under: CHANCE highlights, Previous Features Tagged With: Bahareh Zahirodini and Moinak Bhaduri, Donna LaLonde and Wendy Martinez, Edward Melnick and Ron Melnick, Eric-Jan Wagenmakers, Jeff Dominitz and Charles Manski

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